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Saleem, Muhammad. "Location Analytics for Location-Based Social Networks." Doctoral thesis, Universite Libre de Bruxelles, 2018. https://dipot.ulb.ac.be/dspace/bitstream/2013/271131/5/contratMS.pdf.
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The popularity of location empowered devices such as GPS enabled smart-phones has immensely amplified the use of location-based services in social networks. This happened by allowing users to share Geo-tagged contents such as current locations/check-ins with their social network friends. These location-aware social networks are called Location-based Social Networks (LBSN), and examples include Foursquare and Gowalla. The data of LBSNs are being used for providing different kinds of services such as the recommendation of locations, friends, activities, and media contents, and the prediction of user's locations. To provide such services, different queries are utilized that exploit activity/check-in data of users. Usually, LBSN data is divided into two parts, a social graph that encapsulates the friendships of users and an activity graph that maintains the visit history of users at locations. Such a data separation is scalable enough for processing queries that directly utilize friendship information and visit history of users. These queries are called user and activity analytic queries. The visits of users at locations create relationships between those locations. Such relationships can be built on different features such as common visitors, geographical distance, and mutual location categories between them. The process of analysing such relationships for optimizing location-based services is termed Location Analytics. In location analytics, we expose the subjective nature of locations that can further be used for applications in the domain of prediction of visitors, traffic management, route planning, and targeted marketing.In this thesis, we provide a general LBSN data model which can support storage and processing of queries required for different applications, called location analytics queries. The LBSN data model we introduce, segregates the LBSN data into three graphs: the social graph, the activity graph, and the location graph. The location graph maintains the interactions of locations among each other. We define primitive queries for each of these graphs. In order to process an advanced query, we express it as a combination of these primitive queries and process them on corresponding graphs in parallel. We further provide a distributed data processing framework called GeoSocial-GraphX (GSG). GSG implements the aforementioned LBSN data model for efficient and scalable processing of the queries. We further exploit the location graph for providing novel location analytics queries in the domain of influence maximization and visitor prediction. We introduce a notion of location influence. Such influence can capture the interactions of locations based on their visitors and can be used for propagation of information between them. The applications of such a query lie in the domain of outdoor marketing, and simulation of virus and news propagation. We also provide a unified system IMaxer that can evaluate and compare different information propagation mechanisms. We further exploit the subjective nature of locations by analysing the mobility behaviour of their visitors. We use such information to predict the individual visitors as well as the groups of visitors (cohorts) in future for those locations. The prediction of visitors can be used for better event planning, traffic management, targeted marketing, and ride-sharing services.In order to evaluate the proposed frameworks and approaches, we utilize data from four real-life LBSNs: Foursquare, Brightkite, Gowalla, and Wee Places. The detailed LBSN data mining and statistically significant experimental evaluation results show the effectiveness, efficiency, and scalability of our proposed methods. Our proposed approaches can be employed in real systems for providing life-care services.Doctorat en Sciences de l'ingénieur et technologie
The portal is not showing my complete name. The name (my complete name), I want to have on the diploma is "Muhammad Aamir Saleem". Please correct this issue.
info:eu-repo/semantics/nonPublished
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NETO, JOSE ANTONIO CASEMIRO. "LOCATION BASED ROUTING IN AD-HOC NETWORKS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2007. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=11484@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOUm avanço importante gerado pela tecnologia de TV digital é a possibilidade de interatividade com os usuários, realizada por meio do assim chamado canal de retorno. As redes ad hoc têm um grande potencial para atender esse tipo de serviço, pois podem ser empregadas em diversas áreas geográficas e idealmente de forma independente de infra- estrutura. Isso diminui o seu custo e propícia o aumento da velocidade de implantação deste tipo de rede. Uma das principais questões técnicas a serem resolvidas no contexto das redes móveis ad hoc é a necessidade de algoritmos eficientes para a realização do roteamento dos pacotes. O projeto Terminodes, desenvolvido pelo Instituto Federal de Tecnologia da Suíça, desenvolveu um protocolo de roteamento que utiliza a informação de localização. Este método de roteamento é freqüentemente proposto como um meio para prover escalabilidade em redes ad hoc distribuídas sobre áreas geográficas extensas. O roteamento baseado em localização é difícil quando há áreas de exclusão na topologia da rede e os nós são móveis ou freqüentemente desconectados para fins de economia de bateria. Portanto, a investigação da robustez do protocolo para esses casos é fundamental para avaliar seu uso em redes que podem servir como canal de retorno de TV digital.
An important advance generated by the technology of digital TV is the possibility of interactivity with the users, what is done by means of the return channel. The mobile ad hoc networks have a great potential to provide this type of service, because it can ideally be used in diverse geographic areas and independent of any infrastructure. This minimizes the costs and the time needed to implement the network for this canal. One of the main questions techniques in the context of the mobile ad hoc networks is the necessity of efficient routing algorithms. The Terminodes project, developed by the Federal Institute of Technology of Switzerland, developed a routing protocol that is based in location information. This routing method frequently is a way to provide scalability in large ad hoc networks. The routing based on location is difficult when it has areas of exclusion in the topology of the network and the nodes are mobile or they are frequently disconnected to save battery. Therefore, assess the robustness of the protocol for these cases is basic to evaluate its use in networks for the digital TV return channel.
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Rebaza, Jorge Carlos Valverde. "Mining user behavior in location-based social networks." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-16112017-085356/.
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Online social networks (OSNs) are Web platforms providing different services to facilitate social interaction among their users. A particular kind of OSNs is the location-based social network (LBSN), which adds services based on location. One of the most important challenges in LBSNs is the link prediction problem. Link prediction problem aims to estimate the likelihood of the existence of future friendships among user pairs. Most of the existing studies in link prediction focus on the use of a single information source to perform predictions, i.e. only social information (e.g. social neighborhood) or only location information (e.g. common visited places). However, some researches have shown that the combination of different information sources can lead to more accurate predictions. In this sense, in this thesis we propose different link prediction methods based on the use of different information sources naturally existing in these networks. Thus, we propose seven new link prediction methods using the information related to user membership in social overlapping groups: common neighbors within and outside of common groups (WOCG), common neighbors of groups (CNG), common neighbors with total and partial overlapping of groups (TPOG), group naïve Bayes (GNB), group naïve Bayes of common neighbors (GNB-CN), group naïve Bayes of Adamic-Adar (GNB-AA) and group naïve Bayes of Resource Allocation (GNB-RA). Due to that social groups exist naturally in networks, our proposals can be used in any type of OSN.We also propose new eight link prediction methods combining location and social information: Check-in Observation (ChO), Check-in Allocation (ChA), Within and Outside of Common Places (WOCP), Common Neighbors of Places (CNP), Total and Partial Overlapping of Places (TPOP), Friend Allocation Within Common Places (FAW), Common Neighbors of Nearby Places (CNNP) and Nearby Distance Allocation (NDA). These eight methods are exclusively for work in LBSNs. Obtained results indicate that our proposals are as competitive as state-of-the-art methods, or better than they in certain scenarios. Moreover, since our proposals tend to be computationally more efficient, they are more suitable for real-world applications.Redes sociais online (OSNs) são plataformas Web que oferecem serviços para promoção da interação social entre usuários. OSNs que adicionam serviços relacionados à geolocalização são chamadas redes sociais baseadas em localização (LBSNs). Um dos maiores desafios na análise de LBSNs é a predição de links. A predição de links refere-se ao problema de estimar a probabilidade de conexão futura entre pares de usuários que não se conhecem. Grande parte das pesquisas que focam nesse problema exploram o uso, de maneira isolada, de informações sociais (e.g. amigos em comum) ou de localização (e.g. locais comuns visitados). Porém, algumas pesquisas mostraram que a combinação de diferentes fontes de informação pode influenciar o incremento da acurácia da predição. Motivado por essa lacuna, neste trabalho foram desenvolvidos diferentes métodos para predição de links combinando diferentes fontes de informação. Assim, propomos sete métodos que usam a informação relacionada à participação simultânea de usuários en múltiples grupos sociais: common neighbors within and outside of common groups (WOCG), common neighbors of groups (CNG), common neighbors with total and partial overlapping of groups (TPOG), group naïve Bayes (GNB), group naïve Bayes of common neighbors (GNB-CN), group naïve Bayes of Adamic-Adar (GNB-AA), e group naïve Bayes of Resource Allocation (GNB-RA). Devido ao fato que a presença de grupos sociais não está restrita a alguns tipo de redes, essas propostas podem ser usadas nas diversas OSNs existentes, incluindo LBSNs. Também, propomos oito métodos que combinam o uso de informações sociais e de localização: Check-in Observation (ChO), Check-in Allocation (ChA), Within and Outside of Common Places (WOCP), Common Neighbors of Places (CNP), Total and Partial Overlapping of Places (TPOP), Friend Allocation Within Common Places (FAW), Common Neighbors of Nearby Places (CNNP), e Nearby Distance Allocation (NDA). Tais propostas são para uso exclusivo em LBSNs. Os resultados obtidos indicam que nossas propostas são tão competitivas quanto métodos do estado da arte, podendo até superá-los em determinados cenários. Ainda mais, devido a que na maioria dos casos nossas propostas são computacionalmente mais eficientes, seu uso resulta mais adequado em aplicações do mundo real.
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Li, Yafei. "Efficient group queries in location-based social networks." HKBU Institutional Repository, 2015. https://repository.hkbu.edu.hk/etd_oa/203.
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Nowadays, with the rapid development of GPS-equipped mobile devices, location-based social networks have been emerging to bridge the gap between the physical world and online social networking services. Various types of data, such as personal locations, check-ins, microblogs and social relations, have been available in location-based social networks. Efficiently managing and analyzing such data to meet users' daily query requirements become a challenging task. Among all the existing works in location-based social networks, group query is one of the most important research topics. In this thesis, we investigate query techniques for location-based services in social networking applications. Specifically, considering a location-based social network, we study spatial-aware interest group queries, geo-social {dollar}k{dollar}-cover group queries, and social-aware ridesharing group queries. Firstly, we study the spatial-aware interest group queries in location-based social networks. Recently, most of the location-based social networks release check-in services that allow users to share their visiting locations with their friends. These locations, considered as spatial objects, are usually associated with a few tags that describe the features of those locations. Utilizing such information, we propose a new type of \emph{Spatial-aware Interest Group} (SIG) query that retrieves a user group of size {dollar}k{dollar} where each user is interested in the query keywords and the users are close to each other in the Euclidean space. We prove this query problem is NP-complete, and develop two efficient algorithms IOAIR and DOAIR based on the IR-tree for the processing of SIG queries. We also validate the performance efficiency of the proposed query processing algorithms by empirical evaluation. Secondly, we study the problem of geo-social {dollar}k{dollar}-cover group queries for collaborative spatial computing. In this problem, we propose a novel type of geo-social queries, called \emph{Geo-Social K-Cover Group} (GSKCG) query, which is based on spatial containment and a new modeling of social relationships. Intuitively, given a set of spatial query points and an underlying social network, a GSKCG query finds a minimum user group in which the members satisfy certain social relationship and their associated regions can jointly cover all the query points. Albeit its practical usefulness, the GSKCG query problem is NP-complete. We consequently explore a set of effective pruning strategies to derive an efficient algorithm for finding the optimal solution. Moreover, we design a novel index structure tailored to our problem to further accelerate query processing. Extensive experiments demonstrate that our algorithm achieves desirable performance on real-life datasets. Thirdly, we study the problem of social-aware ridesharing group queries. With the deep penetration of smartphones and geo-locating devices, ridesharing is envisioned as a promising solution to transportation-related problems such as congestion and air pollution for metropolitan cities. Despite the potential to provide significant societal and environmental benefits, ridesharing has not so far been as popular as expected. Notable barriers include the social discomfort and safety concerns when traveling with strangers. To overcome these barriers, in this thesis, we propose a new type of \emph{Social-aware Ridesharing Group} (SaRG) query which retrieves a group of riders by taking into account their social connections besides traditional spatial proximities. Because the SaRG query problem is NP-hard, we design an efficient algorithm with a set of powerful pruning techniques to tackle this problem. We also present several incremental strategies to accelerate the search speed by reducing the repeated computations. Moreover, we propose a novel index tailored to the proposed problem to further speed up the query processing. Experimental results on real datasets show that our proposed algorithms achieve desirable performance. The works of this thesis show that the group query processing techniques are effective, which would facilitate the wider deployment of such query services in real applications
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Nilsson, Joackim. "Dynamic Personal Networks for Location-Based Applications : Within MediaSense." Thesis, Mid Sweden University, Department of Information Technology and Media, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-11782.
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As the development of context aware applications has evolved, there has been a corresponding increase in need for more sophisticated system. The aim for this thesis is the development of a dynamical P2P network system which is based on locations. The P2P network is self organizing and in a lightweight format. Modern technical solutions including AGPS have facilitated the work associated with the ability to position users and modern mathematical solutions such as spherical trigonometry provides the P2P system with the necessary accuracy even for short distances. The P2P system works on different Java platforms including JSE, JME and Android. Unfortunately the 3G network distributor has not yet solved a NAT traversal problem, which means that the P2P network self organization and architecture has only been proved by means of simulations. Another problem is that certain mathematical formulas are required for the spherical trigonometry and the limitation for JME is that it is unable to handle inverse trigonometry. However, the Android and JSE versions can form a correct P2P network, under the condition that the Android device uses a WIFI connection point outside the 3G distributor network system. This thesis reports the successful testing of the locations-based P2P network.
MediaSense
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Chen, Chi. "Location-based data aggregation in mobile ad hoc networks." [S.l. : s.n.], 2003. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB11144241.
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Siebert, Matthias. "Interworking of wireless and mobile networks based on location information /." Aachen : Mainz, 2006. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=016147498&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.
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Wong, Hak Lim. "Signal strength-based location estimation in two different mobile networks." HKBU Institutional Repository, 2006. http://repository.hkbu.edu.hk/etd_ra/700.
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Ciurana, Adell Marc. "Contributions to TOA-based location with wlan." Doctoral thesis, Universitat Politècnica de Catalunya, 2010. http://hdl.handle.net/10803/77902.
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Location techniques that satisfy the requirements of advanced Location-Based Services (LBS) in environments where GPS fails are needed, therefore accurate indoor positioning is becoming increasingly important. This PhD Thesis is devoted to the research on location of mobile devices employing WLAN (IEEE 802.11). The use of this kind of wireless networks infrastructures for positioning enables a powerful synergy between communications and location and allows solutions with good performances at moderated costs. However the adopted WLAN location methods suffer from important limitations that prevents from applying them to some fields that need more flexible and robust solutions. The main objective of this PhD is exploring precise WLAN location methods that allow overcoming these limitations. The researched methods here are based on measuring the Time Of Arrival (TOA), which is the time that takes the signal propagating from the transmitter to the receiver. TOA-based location works in two stages: ranging and positioning. The ranging consists of estimating the distances between the targeted terminal and several WLAN access points, each distance obtained measuring the TOA and then multiplying it by the speed of the WLAN signal. After that, the positioning takes as inputs the estimated distances and the known coordinates of the involved access points and calculates the position of the terminal by means of a trilateration or tracking algorithm. The key problem is that the characteristics of the IEEE 802.11 protocols difficult to perform accurate TOA measurements. The main challenge that faces the research work reported here is demonstrating the feasibility of achieving this while keeping the modifications over standard WLAN consumer equipment at minimum. The objective of this work can be understood as exploring the current limits of TOA-based methods over WLAN, making contributions that form a complete TOA-based location method that goes a step forward with respect to the other existing proposals. First, research on TOA-based ranging -the key component of TOA-based location methods- is reported. The general adopted approach consists of performing Round Trip Time (RTT) measurements employing IEEE 802.11 MAC frames, taking the maximum advantage of the combination of IEEE 802.11 protocol and WLAN consumer devices mechanisms. After that, the performed research on trilateration/tracking -the second stage of TOA-based location methods- is explained. Finally some performed studies about the achieved location method are presented.
Lloc i data
SignaturaActualment existeix la necessitat de disposar de tècniques de localització que satisfacin els requeriments de serveis avançats basats en localització en entorns on GPS no està disponible, de manera que el posicionament precís en interiors d’edificis és cada vegada més important. Aquesta tesi doctoral està dedicada a la investigació sobre la localització de dispositius mòbils que utilitzen WLAN (IEEE 802.11). L'ús d'aquest tipus de xarxes sense fils per al posicionament permet una profitosa sinèrgia entre les comunicacions i la localització i permet solucions amb un bon rendiment a un cost moderat. No obstant això, els mètodes basats WLAN proposats fins el moment pateixen de limitacions importants que impedeix la seva aplicació a alguns camps que requereixen solucions més flexibles i robustes. L'objectiu principal d'aquesta tesi és explorar mètodes de localització precisa WLAN que permetin superar aquestes limitacions. Els mètodes que s’han investigat durant la tesi es basen en la mesura del time of arrival (TOA), que és el temps que tarda el senyal en propagar-se des del transmissor fins al receptor. En les tècniques de posicionament basades en TOA s’hi poden diferenciar dues fases: ranging i posicionament. El ranging consisteix en l’estimació de distàncies entre el terminal a localitzar i diversos punts d'accés WLAN; cada estimació de distància s’obté mesurant el TOA i multiplicant-lo després per la velocitat de propagació del senyal IEEE 802.11. Un cop fet això, el posicionament pren com a inputs les distàncies estimades per a, conegudes les coordenades dels punts d'accés involucrats, calcular la posició del terminal per mitjà d'un algoritme de tracking o trilateració. El problema clau és que les característiques dels protocols IEEE 802.11 a dia d’avui fan difícil la realització de mesures precises de TOA d’una manera senzilla. El principal repte que afronta el present treball de recerca és demostrar la viabilitat d’això darrer, minimitzant en la major mesura possible les modificacions sobre els equips WLAN comercials. L'objectiu d'aquest treball pot ser entesa com l'exploració dels límits actuals dels mètodes de posicionament basats en TOA sobre WLAN, realitzant contribucions que conformen un mètode complet de localització basat en TOA que pretén anar un pas endavant respecte a les propostes existents. En primer lloc, la investigació sobre ranging basat en TOA -el component clau dels mètode de localització TOA- és explicada en detall. El mètode general adoptat per a calcular el TOA consisteix en la mesura del temps d'anada i tornada del senyal, round trip time (RTT), utilitzant trames MAC IEEE 802.11 per tal de treure el màxim profit de la combinació del protocol IEEE 802.11 i els mecanismes dels dispositius WLAN comercials. Després d'això, es detalla la investigació realitzada sobre trilateració i tracking, la segona etapa dels mètodes de localització basats en TOA. Finalment es descriuen alguns estudis realitzats sobre les prestacions, possibles millores i encaix en futurs estàndars del mètode de localització explorat.
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Ayyagari, Suhaas Bhargava. "ARTIFICIAL NEURAL NETWORK BASED FAULT LOCATION FOR TRANSMISSION LINES." UKnowledge, 2011. http://uknowledge.uky.edu/gradschool_theses/657.
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This thesis focuses on detecting, classifying and locating faults on electric power transmission lines. Fault detection, fault classification and fault location have been achieved by using artificial neural networks. Feedforward networks have been employed along with backpropagation algorithm for each of the three phases in the Fault location process. Analysis on neural networks with varying number of hidden layers and neurons per hidden layer has been provided to validate the choice of the neural networks in each step. Simulation results have been provided to demonstrate that artificial neural network based methods are efficient in locating faults on transmission lines and achieve satisfactory performances.
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Noulas, Anastasios. "Human urban mobility in location-based social networks : analysis, models and applications." Thesis, University of Cambridge, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648354.
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Scourias, John. "Dynamic location management and activity-based mobility modelling for cellular networks." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq21539.pdf.
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Erpek, Tugba. "Location-based propagation modeling for opportunistic spectrum access in wireless networks." Fairfax, VA : George Mason University, 2007. http://hdl.handle.net/1920/2934.
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Thesis (M.S.)--George Mason University, 2007.Title from PDF t.p. (viewed Jan. 17, 2008). Thesis director: Brian L. Mark Submitted in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering. Vita: p. 60. Includes bibliographical references (p. 58-59). Also available in print.
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Wang, Yikun. "Design of a Fast Location-Based Handoff Scheme for Vehicular Networks." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/26259.
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IEEE 802.11 is an economical and efficient standard that has been applied to vehicular networks. However, the long handoff latency of the standard handoff scheme for IEEE 802.11 has become an important issue for seamless roaming in vehicular environments, as more handoffs may be triggered due to the higher mobility of vehicles.
This thesis presents a new and fast location-based handoff scheme particularly designed for vehicular environments. With the position and movement direction of a vehicle and the locations of the surrounding APs, our protocol is able to accurately predict several possible APs that the vehicle may visit in the future and to assign these APs different priority levels. APs on higher priority levels will be first scanned. Once a response to scanning from an AP is received, the scanning process ends immediately. A blacklist scheme is also used to exclude those APs that showed no response to the scanning during previous handoffs. Thus, time spent on scanning APs is supposed to be significantly reduced. The simulation results show that the proposed scheme attains not only a lower prediction error rate, but also a lower MAC layer handoff latency, and that it has a smaller influence on jitter and throughput; moreover, these results show that the proposed scheme has a smaller total number of handoffs than other handoff schemes.
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Samii, Etienne. "Usability design for location based mobile services in wireless metropolitan networks." Hamburg Diplomica-Verl, 2006. http://d-nb.info/987370928/04.
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Newbry, Joe S. "Samantha: A Social Location-Based Framework for iOS Applications." Scholarship @ Claremont, 2014. http://scholarship.claremont.edu/cmc_theses/939.
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One challenge associated with developing location-based social applications for iOS devices is building a framework on top of Apple’s Core Bluetooth Framework to drive user discovery. Many applications on Apple’s App Store use Bluetooth to enable location-based user discovery. These Social Location-Based Frameworks are private and often are lacking. An ideal Social Location-Based Bluetooth Framework would be public, would be responsive while the application is minimized, have a light battery footprint, and securely transfer the necessary data to enable social interaction. Samantha, a Social Location-Based Framework, meets all of these characteristics.
In a Test Application, Samantha took no more than 5 seconds to start up and discover all nearby users. The average discovery time was 3.5 seconds. In addition the battery draw, measured using Apple’s Battery Monitoring Instrument, during testing never exceed 1/20. This means an application running Samantha in the background for a 12-hour period would not significantly drain the battery.
In terms of security, Samantha transfers a Unique User Identifier (UUID) across Bluetooth than contains no sensitive information. This UUID, a string of random characters, contains no personal information and it is only useful because it allows specific identification of a nearby user in a database holding additional information. This two-step process ensures that confidential information is never exposed.
An example application, Ripple, uses Samantha to create a location-based social application and highlights the framework’s intended use.
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NASCIMENTO, FERNANDO NEY DA COSTA. "A LOCATION INFERENCE SERVICE FOR MOBILE DEVICES BASED ON IEEE 802.11 NETWORKS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2005. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=7872@1.
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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIORDispositivos portáteis e redes sem fio vem tornando-se cada vez mais populares e comuns em nosso dia-a-dia, criando assim uma demanda pelo desenvolvimento de serviços e aplicações sensíveis à localização. Em paralelo, houve o desenvolvimento de diversas tecnologias de localização para viabilizar tais serviços, sendo o GPS a mais difundida. O principal problema desta e de várias outras tecnologias é que requerem a implantação de uma infra- estrutura específica para a localização, como por exemplo sensores e satélites, o que aumenta o seu custo ou limita a sua aplicabilidade. Por isto, técnicas de localização que se baseiam exclusivamente na própria infra-estrutura de rede sem fio tem sido bastante exploradas. Neste trabalho apresentamos um serviço para a localização de dispositivos móveis baseado na intensidade de sinal (de radio-freqüência) de pontos de acesso de redes IEEE 802.11. Verificamos também a viabilidade de seu uso para aplicações que demandam a informação de localização em termos de regiões simbólicas (ao invés de coordenadas) e com uma tolerância de erro de poucos metros. O serviço permite também o aninhamento dessas regiões para a formação de regiões maiores, criando o conceito de uma hierarquia de regiões simbólicas.
Portable devices and wireless networks are becoming common place in our daily lives. This has created a demand for the development of locationbased services and applications, i.e. Location-based Services. In parallel, several positioning technologies enabling such services have been developed, where GPS is the most popular one. The main drawback of this and other technologies is that they require the deployment of a specific infra-structure for the positioning, such as sensors and satellites, which in turn raises their cost or restricts their applicability. Therefore, other positioning technologies, which are based merely on the wireless infra-structure, have been explored. In this work we present a service which infers the location of mobile devices using the radio-frequency signal strength of Access Points of IEEE 802.11 wireless networks. We have also verified the viability of its use by applications that require location information in terms of symbolic regions, instead of coordinates, and which tolerate inference errors of a few meters. The service also supports the aggregation of regions into larger symbolic regions using the notion of a hierarchy of symbolic regions.
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Oladimeji, Henry. "Factors influencing the use of privacy settings in location-based social networks." Master's thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/27449.
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The growth of location-based social networks (LBSN) such as Facebook and Twitter has been rapid in recent years. In LBSNs, users provide location information on public profiles that potentially can be used in harmful ways. LBSNs have privacy settings that allow users to control the privacy level of their profiles, thus limiting access to location information by other users; but for various reasons users seldom make use of them. Using the protection motivation theory (PMT) as a theoretical lens, this dissertation examines whether users can be encouraged to use LBSN privacy settings through fear appeals. Fear appeals have been used in various studies to arouse fear in users, in order to motivate them to comply to an adaptive behaviour through the threat of impending danger. However, within the context of social networking, it is not yet clear how fear-inducing arguments will ultimately influence the use of privacy settings by users. The purpose of this study is to investigate the influence of fear appeals on user compliance, with recommendations to enact the use of privacy settings toward the alleviation of privacy threats. Using a survey methodology, 248 social-network users completed an instrument measuring the variables conceptualized by PMT. Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to test the validity and reliability, and to analyze the data. Analysis of the responses show that PMT provides an explanation for the intention to use privacy settings by social-network users. Risk susceptibility, response efficacy, self-efficacy and response cost were found to have a positive impact on the intention to use privacy settings, while sharing benefits and maladaptive behaviours were found to have a negative impact on the intention to use privacy settings. However, risk severity and fear were not found to be significant predictors of the intention to use privacy settings. This study contributes to existing research on PMT in a sense that fear appeal should focus more on coping appraisal, rather than on threat appraisal which is consistent with the results of most studies on protection motivation.
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Ballesteros, Jaime. "Mixed Spatial and Nonspatial Problems in Location Based Services." FIU Digital Commons, 2013. http://digitalcommons.fiu.edu/etd/930.
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With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases.
Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features.
Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.
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Ma, Chang Yi. "Functional region based daily-life activity recommendation." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3950696.
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Kaul, Manohar. "Frequent Route Based Continuous Moving Object Location and Density Prediction on Road Networks." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-155759.
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Emerging trends in urban mobility have accelerated the need for effective traffic management and prediction systems. Simultaneously, the widespread adoption of GPS-enabled mobile devices has opened radical new possibilities for such systems. Motivated by this development, this thesis proposes an end-to-end streaming approach for traffic management that encompasses a novel prediction model. The stream processing is achieved by a sliding window model. In particular, the approach performs online 1) management of the current evolving trajectories, 2) incremental mining of closed frequent routes and 3) prediction of near-future locations of the moving objects based on the current object trajectories and historical frequent routes. The approach proposes storage of closed frequent routes and all possible turns a moving object can make at a junction, in a FP-tree like structure. This structure is created on the-fly from the buffered contents of each constituent window of the trajectories stream and then used to determine probabilistic future locations of each moving object. It additionaly calculates the densities of moving objects and parked objects for the entire road network. The prototype implements the approach as extensions to SCSQ - a data stream management system (DSMS) developed at UDBL. SCSQ is an extension of Amos II which is an extensible, mainmemory OO DBMS. The solution utilizes SCSQ’s stream manipulation and windowing capabilities coupled with Amos II’s functionality to efficiently store, index and query frequent routes for prediction. The approach is empirically evaluated on a large real-world data set of moving object trajectories, originating from a fleet of taxis, showing that detailed closed frequent routes can be efficiently discovered and used for prediction.
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Loureiro, Renzo Zamprogno. "Content location for in-flight entertainment systems based on peer-to-peer networks." Instituto Tecnológico de Aeronáutica, 2009. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1271.
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In this work we introduce a peer-to-peer approach for in-flight entertainment video on-demand systems. Such applications are traditional ways for the airline to improve profit from its operation and attract customers. We outline how a peer-to-peer system should be organized to address this specific application and reduce operational costs for the airline. Furthermore, we discuss in details the problem of content discovery that rises in such environment and propose two feasible solutions. These solutions are analyzed in the terms of network bandwidth demand and amount of data transmitted over the network infrastructure. Our conclusions show that the content location problem can be solved without significant use of bandwidth, and ultimately the peer-to-peer paradigm is a worth-taking and feasible path for the next in-flight entertainment system generations.
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Braga, Reinaldo. "LIDU : Location-based approach to IDentify similar interests between Users in social networks." Thesis, Grenoble, 2012. http://www.theses.fr/2012GRENM055/document.
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Grâce aux technologies web et mobiles, le partage de données entre utilisateurs a considérablement augmenté au cours des dernières années. Par exemple, les utilisateurs peuvent facilement enregistrer leurs trajectoires durant leurs déplacements quotidiens avec l'utilisation de récepteurs GPS et les mettre en relation avec les trajectoires d'autres utilisateurs. L'analyse des trajectoires des utilisateurs au fil du temps peut révéler des habitudes et préférences. Cette information peut être utilisée pour recommander des contenus à des utilisateurs individuels ou à des groupes d'utilisateurs avec des trajectoires ou préférences similaires. En revanche, l'enregistrement de points GPS génère de grandes quantités de données. Par conséquent, les algorithmes de clustering sont nécessaires pour analyser efficacement ces données. Dans cette thèse, nous nous concentrons sur l'étude des différentes solutions pour analyser les trajectoires, extraire les préférences et identifier les intérêts similaires entre les utilisateurs. Nous proposons un algorithme de clustering de trajectoires GPS. En outre, nous proposons un algorithme de corrélation basée sur les trajectoires des points proches entre deux ou plusieurs utilisateurs. Les résultats finaux ouvrent des perspectives intéressantes pour explorer les applications des réseaux sociaux basés sur la localisationSharing of user data has substantially increased over the past few years facilitated by sophisticated Web and mobile applications, including social networks. For instance, users can easily register their trajectories over time based on their daily trips captured with GPS receivers as well as share and relate them with trajectories of other users. Analyzing user trajectories over time can reveal habits and preferences. This information can be used to recommend content to single users or to group users together based on similar trajectories and/or preferences. Recording GPS tracks generates very large amounts of data. Therefore clustering algorithms are required to efficiently analyze such data. In this thesis, we focus on investigating ways of efficiently analyzing user trajectories, extracting user preferences from them and identifying similar interests between users. We demonstrate an algorithm for clustering user GPS trajectories. In addition, we propose an algorithm to correlate trajectories based on near points between two or more users. The final results provided interesting avenues for exploring Location-based Social Network (LBSN) applications
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Scellato, Salvatore. "Spatial properties of online social services : measurement, analysis and applications." Thesis, University of Cambridge, 2012. https://www.repository.cam.ac.uk/handle/1810/265547.
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Online social networking services entice millions of users to spend hours every day interacting with each other. At the same time, thanks to the widespread and growing popularity of mobile devices equipped with location-sensing technology, users are now increasingly sharing details about their geographic location and about the places they visit. This adds a crucial spatial and geographic dimension to online social services, bridging the gap between the online world and physical presence. These observations motivate the work in this dissertation: our thesis is that the spatial properties of online social networking services offer important insights about users' social behaviour. This thesis is supported by a set of re.sults related to the measurement and the analysis of such spatial properties. First, we present a comparative study of three online social services: we find that geographic distance constrains social connections, although users exhibit heterogeneous spatial properties. Furthermore, we demonstrate that by considering only social or only spatial factors it is not possible to reproduce the observed properties. Therefore, we investigate how these factors are jointly influencing the evolution of online social services. The resulting observations are then incorporated in a new model of network growth which is able to reproduce the properties of real systems. Then, we outline two case studies where we exploit our findings in real application scenarios. The first concerns building a link prediction system to find pairs of users likely to connect on online social services. Even though spatial proximity fosters the creation of social ties, the computational challenge is accurately and efficiently to discern when being close in space results in a new social connection. We address this problem with a system that uses, alongside other information, features based on the places that users visit. The second example presents a method to extract geographic information about users sharing online videos to understand whether such videos are going to become locally or globally popular. This information is then harnessed to build caching policies that consider which items should be prioritised in memory, thus improving performance of content delivery networks. We summarise our findings with a discussion about the implications of our results, debating potential future research trends and practical applications.
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Satti, Narendra Siva Prasad Reddy, and Saket Vikram Singh. "Analysis of Location based QoE for Mobile video streaming from YouTube in 4G Networks." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-1939.
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Mobile Video streaming has become popular with the arrival of high capability smart phones on Mobile Networks. Users are streaming high definition (HD) videos and have high expectations on Mobile Quality of Experience (QoE). Fourth Generation Mobile Networks are being deployed recently in many regions of the world and have capability to efficiently handle high definition video traffic. YouTube is one of the most extensively used Video on Demand Service on smart phones where wide range of people do video streaming. Most of the QoE experiments on 4g networks have been conducted in lab environment but they do not capture the daily routine of user experience on viewing videos. The user experiments in this thesis are conducted in natural life settings to capture Quality of Experience based on context of the user location. User experiments are designed and conducted for collecting Mean Opinion scores (MOS) in four different context based locations and have been collected using Experience Sampling Method (ESM). The Contribution of thesis is applying linear mixed effect Modeling on data collected to develop Quality of Experience (QoE) models of video streaming for Mobile YouTube on 4G Network. This thesis is one of the first works on modeling QoE experience at different context based physical locations in natural settings for mobile YouTube video streaming in 4G networks.
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Khater, Shaymaa. "Personalized Recommendation for Online Social Networks Information: Personal Preferences and Location Based Community Trends." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/64283.
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Online social networks are experiencing an explosive growth in recent years in both the number of users and the amount of information shared. The users join these social networks to connect with each other, share, find content and disseminate information by sending short text messages in near realtime. As a result of the growth of social networks, the users are often experiencing information overload since they interact with many other users and read ever increasing content volume. Thus, finding the "matching" users and content is one of the key challenges for social networks sites. Recommendation systems have been proposed to help users cope with information overload by predicting the items that a user may be interested in.
The users' preferences are shaped by personal interests. At the same time, users are affected by their surroundings, as determined by their geographically located communities. Accordingly, our approach takes into account both personal interests and local communities. We first propose a new dynamic recommendation system model that provides better customized content to the user. That is, the model provides the user with the most important tweets according to his individual interests. We then analyze how changes in the surrounding environment can affect the user's experience. Specifically, we study how changes in the geographical community preferences can affect the individual user's interests. These community preferences are generally reflected in the localized trending topics. Consequently, we present TrendFusion, an innovative model that analyzes the trends propagation, predicts the localized diffusion of trends in social networks and recommends the most interesting trends to the user. Our performance evaluation demonstrate the effectiveness of the proposed recommendation system and shows that it improves the precision and recall of identifying important tweets by up to 36% and 80%, respectively. Results also show that TrendFusion
accurately predicts places in which a trend will appear, with 98% recall and 80% precision.Ph. D.
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Yasheen, Sharifa. "Evaluation of Markov Models in Location Based Social Networks in Terms of Prediction Accuracy." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-13039.
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Location Based Social Networks has attracted millions of mobile internet users. On their smart phones people can share their locations using social network services. The main purpose of check-ins is to provide other users’ information about places they visit. Location Based Social Network with thousands of check-ins allows users to learn social behavior through spatial-temporal effect, which provides different services such as place recommendation and traffic prediction. Through this information, we can have an idea about important locations in the city and human mobility. The main purpose of this thesis is to evaluate Markov Models in Location Based Social Networks in terms of prediction accuracy. Location Based Social Network features and basic information’s will be analyzed before modeling of human mobility. Afterwards with the use of three methods human mobility will be modeled. In all the models the check-ins are analyzed based on prior category. After estimation the user’s possible next check-in category, and according to the user’s check-ins in the following category, it predicts the next possible check-in location. Finally a comparison will be made considering the models prediction accuracy.
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Agarwal, Aarti Subhash. "Use of Query Control and Location for Routing in Mobile Ad Hoc Networks." University of Cincinnati / OhioLINK, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1018645216.
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Lim, Yu-Xi. "Efficient wireless location estimation through simultaneous localization and mapping." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28219.
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Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.Committee Chair: Owen, Henry; Committee Member: Copeland, John; Committee Member: Giffin, Jonathon; Committee Member: Howard, Ayanna; Committee Member: Riley, George.
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Lout, Kapildev. "Development of a fault location method based on fault induced transients in distribution networks with wind farm connections." Thesis, University of Bath, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.678845.
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Electrical transmission and distribution networks are prone to short circuit faults since they span over long distances to deliver the electrical power from generating units to where the energy is required. These faults are usually caused by vegetation growing underneath bare overhead conductors, large birds short circuiting the phases, mechanical failure of pin-type insulators or even insulation failure of cables due to wear and tear, resulting in creepage current. Short circuit faults are highly undesirable for distribution network companies since they cause interruption of supply, thus affecting the reliability of their network, leading to a loss of revenue for the companies. Therefore, accurate offline fault location is required to quickly tackle the repair of permanent faults on the system so as to improve system reliability. Moreover, it also provides a tool to identify weak spots on the system following transient fault events such that these future potential sources of system failure can be checked during preventive maintenance. With these aims in mind, a novel fault location technique has been developed to accurately determine the location of short circuit faults in a distribution network consisting of feeders and spurs, using only the phase currents measured at the outgoing end of the feeder in the substation. These phase currents are analysed using the Discrete Wavelet Transform to identify distinct features for each type of fault. To achieve better accuracy and success, the scheme firstly uses these distinct features to train an Artificial Neural Network based algorithm to identify the type of fault on the system. Another Artificial Neural Network based algorithm dedicated to this type of fault then identifies the location of the fault on the feeder or spur. Finally, a series of Artificial Neural Network based algorithms estimate the distance to the point of fault along the feeder or spur. The impact of wind farm connections consisting of doubly-fed induction generators and permanent magnet synchronous generators on the accuracy of the developed algorithms has also been investigated using detailed models of these wind turbine generator types in Simulink. The results obtained showed that the developed scheme allows the accurate location of the short circuit faults in an active distribution network. Further sensitivity tests such as the change in fault inception angle, fault impedance, line length, wind farm capacity, network configuration and white noise confirm the robustness of the novel fault location technique in active distribution networks.
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Yu, Zehao. "Towards location-awareness in next generation wireless networks : a new approach based on channel state information." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127117.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, May, 2020Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 69-78).
Location-awareness in next generation wireless networks will be a key enabler for numerous emerging applications. Recently, a novel approach to localization based on soft information (SI), exploiting all positional information inherent in measurement and contextual data, has been proposed. This thesis further develops SI-based localization by establishing a new approach relying on channel state information (CSI) measurements. In particular, we design an efficient joint message-passing (MP) localization algorithm, which consists of two layers: the transformation layer and the estimation layer. The transformation layer extracts SI of the channel impulse response (CIR) from CSI measurements using a sparsity promoting prior model, which addresses the difficulty of unknown number of multipath in estimating the CIR. The estimation layer infers node positions based on the SI of the CIR using a delay-origin uncertainty model, which describes the conditional distribution of the delays in the CIR given node positions. Simulation results using QuaDriGa channel simulator show that our localization algorithm achieves decimeter-level localization accuracy for both Wi-Fi and mmWave signals, which outperforms conventional algorithms.
by Zehao Yu.
S.M.
S.M. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics
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Zhang, Rui. "Sink localization and topology control in large scale heterogeneous wireless sensor networks." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002048.
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Vo, Jacqueline H. "Check-In Frequency with Friends on Location-Based Social Networks: A Look at Homophily and Relational Closeness." PDXScholar, 2015. https://pdxscholar.library.pdx.edu/open_access_etds/2630.
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This study examines factors associated with the frequency with which users of location-based social networks (LBSNs) "check-in" with their "friends." In addition to a variety of control factors (i.e., sex homophily, race homophily, geographic proximity, length of friendship, and "friendship" type, including non-romantic friend, romantic partner, and family), the central factors of interest were users' background and attitude homophily with, and relational closeness to, their "friends." Results demonstrate that relational closeness and "friendship" type (i.e., romantic partner) were significantly, positively associated with "check-in" frequency.
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Andersson, Christer. "Enhancing Privacy for Mobile Networks : Examples of Anonymity Solutions and Their Analysis." Licentiate thesis, Karlstad University, Division for Information Technology, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-1560.
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Internet and mobile communications have had a profound effect on today’s society. New services are constantly being deployed, in which an increasing amount of personal data is being processed in return for personally tailored services. Further, the use of electronic surveillance is increasing. There is the risk that honest citizens will have their privacy invaded for “the greater good”. We argue that it is of uttermost importance to retain the individuals’ control over their personal spheres.
One approach for enhancing the users’ privacy is to deploy technical measures for safeguarding privacy, so-called Privacy-Enhancing Technologies (PETs). This thesis examines a set of PETs for enabling anonymous communication, so-called anonymous overlay networks,which eliminate the processing of personal data altogether by allowing the users act anonymously when communicating in a networked environment.
This thesis focuses mainly on mobile networks. These are of great interest because on the one hand they lay the groundwork for new innovative applications, but on the other hand they pose numerous novel challenges to privacy. This thesis describes the implementation
and performance evaluation of mCrowds – an anonymous overlay network for mobile Internet that enables anonymous browsing. It also describes the ongoing investigation on how to design anonymous overlay networks in order to make them suitable for mobile ad hoc
networks, a required building block for ambient intelligence.
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Hai, Nguyen Thanh, and 阮清海. "Location Promotion based on Human Mobility on Location-based Social Networks." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/77108721959836980191.
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碩士國立交通大學
資訊科學與工程研究所
102
Maximizing the spread of influence was recently studied in several models of social networks. For location-based social networks, it also plays an important role, so a further research about this fields is necessary. In this study, based on users’ movement histories and their friendships, we first design the Predicting Mobility in the Near Future (PMNF) model to capture human mobility. Human mobility is inferred from the model by taking into account the following three features: (1) the regular movement of users, (2) the movement of friends of users, (3) hot regions, the most attractive places for all users. Second, from the result of predicting movements of users at each location, we determine influence of each user on friends with the condition that friends are predicted to come to the location. Third, the Influence Maximization (IM) algorithms are proposed to find a set of k influential users who can make the maximum influence on their friends according to either the number of influenced users (IM num) or the total of probability of moving the considered location of influenced users (IM score). The model and algorithms are evaluated on three large datasets collected by from 40,000 to over 60,000 users for each dataset over a period of two years in the real world at over 500,000 checked-in points as well as 400,000 to nearly 2,000,000 friendships also considered. The points are clustered into locations by density-based clustering algorithms such as OPTICS and GRID. As a result, our algorithms give an order of magnitude better performance than baseline approaches like choosing influential users based on the number of check-ins of users and selecting influential users by the number of friends of users. From the result of experiments, we are able to apply to some areas like advertisement to get the most efficient with the minimum costs. We show that our framework reliably determines the most influential users with high accuracy.
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Lu, Chang-che, and 呂長哲. "Location-based Network Management System for Heterogeneous Mobile Networks." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/35186404723344553357.
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碩士國立中央大學
資訊工程研究所
95
With the improvement of society, the technology of internet is growing constantly. New wireless internet agreement like IEEE 802.11 (Wi-Fi) 、 IEEE 802.16 (WiMAX) and 3GPP (3rd Generation Partnership Project) provide internet users have different options for different broadband, different internet field and different prices. Many different wireless internet form an internet environment. We called it Heterogeneous wireless network environment. With new internet agreement getting mature, a variety of broadband wireless equipment is developed. To administer heterogeneous wireless network is becoming a significant issue when we face so many internet equipment at the same time. Traditional internet administration should be improved to manage heterogeneous wireless network environment. The most important problem in the administration of heterogeneous wireless network is how to administer many wireless networks at the same time. And it’s quite difficult to let internet administration center know the status of each wireless internet correctly and fast. Therefore, the essay offers a management system which applied to Heterogeneous wireless network. (Heterogeneous Mobile Network Management System，call the HMNMS). The system uses separated construction to set up a HMNMS on every different mobile wireless network. Every HMNMS will be able to share the information of Mobile Network with neighboring HMNMS. To measure intensity of message for bigger shooting range base with the location of smaller shooting range base. Making good use of several interfaces to decrease unnecessary cost on measurement. The system not only offers a convenient monitoring and manages wireless network equipment under Heterogeneous Mobile Network, but also analyze covering range of base through the intensity of message of the users and the location of users. With proper adjustment and the setting up of base location, to create the environment that internet exists everywhere.
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Wen, Zi-Yi, and 温子毅. "Promoting Multi-location via Viral Marketing in Location-based Social Networks." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/62976327637525774837.
Full textAbstract:
碩士國立交通大學
多媒體工程研究所
104
As the social networks has rapidly grown and become increasingly popular providing important platform for people to share their activities, interest and so on. The location-based social networking platform (e.g., Facebook, Foursquare) allow a user to check-in at a locations of interest with her mobile device, which reports visited locations to the LBSN. This information is then shared with other users who are socially related (e.g., friends, families). In view of the social influences of friends, recently, many POIs (Points of Interests) have explored check-in sharing to attract users to stay or visit. Location promotion is also popular with chain marketing, and many proprietors expect that many people will shop in their chain stores. To do this, we advertise the set of target locations to individuals, so that they can get the information about the set of target locations, which they are interested in. Therefore, we formulate this problem as a multi-location promotion problem. That is, given a set of target location and a set of seeds, the purpose is to maximize the number of influenced users. This paper proposes multi-location-aware propagation models to truly reflect the information propagation in LBSNs. Extensive experiments based on real LBSN datasets have demonstrated the superior effectiveness and performance of our proposals, which outperform the state-of-the-art algorithms.
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Haque, Israat Tanzeena. "Location-based routing and indoor location estimation in mobile ad hoc networks." Phd thesis, 2011. http://hdl.handle.net/10048/1841.
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In Mobile Ad Hoc NETworks (MANETs) autonomous nodes act both as traffic originators
and forwarders to form a multi-hop network.
Out-of-range nodes are reachable through a process called routing,
which is a challenging task due to the constraints of bandwidth and battery power.
Stateless location-based routing schemes have been proposed to avoid complex route
discovery and maintenance, whereby nodes make routing decisions based solely
on the knowledge of their location, the location of their neighbors, and the location of the destination.
Natural routing schemes based on these prerequisites suffer from problems like local maxima or loops.
We mitigate those problems by proposing randomized routing algorithms,
which outperform others in terms of the packet delivery ratio and throughput.
The prerequisite for location-based routing is knowing the location of a node.
Location information is more widely useful anyway for
location-aware applications like security, health care, robotics, navigation etc.
Locating a node indoors remains a challenging problem due to the unavailability of GPS signals under the roof.
For this goal we choose the RSS (Received Signal Strength)
as the relevant attribute of the signal due to its minimal requirements on the RF technology
of the requisite modules. Then profiling based localization is considered that does not
rely on any channel model (range-based) or the connectivity information (range-free),
but rather exploits the context of a node to infer that information into the estimation.
We propose a RSS profiling based indoor localization system, dubbed LEMON,
based on low-cost low-power wireless devices that offers better accuracy than other RSS-based schemes.
We then propose a simple RSS scaling trick to further improve the accuracy of LEMON.
Furthermore, we study the effect of the node orientation, the number and the arrangement
of the infrastructure nodes and the profiled samples, leading us to further
insights about what can be effective node placement and profiling.
We also consider alternate formulations of the localization problem,
as a Bayesian network model as well as formulated in a combinatorial fashion.
Then performance of different localization methods is compared and again LEMON ensures better accuracy.
An effective room localization algorithm is developed, and both single and multiple
channels are used to test its performance. Furthermore, a set of two-step localization
algorithms is designed to make the LEMON robust in the presence of noisy RSS and faulty device behavior.
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Wen, Yu-Ting, and 溫郁婷. "Exploring social influence on location-based social networks." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/99336810230166308365.
Full textAbstract:
碩士國立交通大學
資訊科學與工程研究所
102
Recently, with the advent of location-based social networking services (LBSNs), e.g., Foursquare, Yelp, Geolife and Flickr, travel planing and location-aware information recommendation based on LBSN have attracted research attentions, such as Point-of-interest (POI) recommendation or travel routes recommendation. Most of the existing works mainly address on mining POIs by crowd power in LBSN and generate the recommendation on demand. For example, extracting personal preferences from individual’s location history to score the POIs in query region. However, they ignore the impact of social relations hidden in LBSN, i.e., the social influence from friends. We suppose that the location-aware recommendation with favorable comments from friends should be more reliable than that from unfamiliar crowd.In this paper, we propose a new social influence-based user recommender framework (SIR) which differs from prior works by aiming to discover the potential value addition from reliable users (i.e. close friends and travel experts). Explicitly, our SIR framework is able to infer influential users from LBSN. We claim to capture the interaction among virtual community, physical mobility activities and time effects to infer the social influence between user pairs. Furthetmore, we intend to model the propagation of influence in terms of diffusion-based mechanism. Third, we design a dynamic fusion framework to integrate the features mined into an united follow probability score. Finally, our framework provides personalized top-k user recommendation for individuals. To evaluate the recommendation results, we conduct extensive experiments on real datasets (i.e., Flicker dataset and Gowalla datasets). The experimental results shows the performance of our SIR framework is better than a state-of-the-art user recommendation mechanisms in terms of accuracy and reliability.
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"Personalized POI Recommendation on Location-Based Social Networks." Doctoral diss., 2014. http://hdl.handle.net/2286/R.I.27381.
Full textAbstract:
abstract: The rapid urban expansion has greatly extended the physical boundary of our living area, along with a large number of POIs (points of interest) being developed. A POI is a specific location (e.g., hotel, restaurant, theater, mall) that a user may find useful or interesting. When exploring the city and neighborhood, the increasing number of POIs could enrich people's daily life, providing them with more choices of life experience than before, while at the same time also brings the problem of "curse of choices", resulting in the difficulty for a user to make a satisfied decision on "where to go" in an efficient way. Personalized POI recommendation is a task proposed on purpose of helping users filter out uninteresting POIs and reduce time in decision making, which could also benefit virtual marketing.
Developing POI recommender systems requires observation of human mobility w.r.t. real-world POIs, which is infeasible with traditional mobile data. However, the recent development of location-based social networks (LBSNs) provides such observation. Typical location-based social networking sites allow users to "check in" at POIs with smartphones, leave tips and share that experience with their online friends. The increasing number of LBSN users has generated large amounts of LBSN data, providing an unprecedented opportunity to study human mobility for personalized POI recommendation in spatial, temporal, social, and content aspects.
Different from recommender systems in other categories, e.g., movie recommendation in NetFlix, friend recommendation in dating websites, item recommendation in online shopping sites, personalized POI recommendation on LBSNs has its unique challenges due to the stochastic property of human mobility and the mobile behavior indications provided by LBSN information layout. The strong correlations between geographical POI information and other LBSN information result in three major human mobile properties, i.e., geo-social correlations, geo-temporal patterns, and geo-content indications, which are neither observed in other recommender systems, nor exploited in current POI recommendation. In this dissertation, we investigate these properties on LBSNs, and propose personalized POI recommendation models accordingly. The performance evaluated on real-world LBSN datasets validates the power of these properties in capturing user mobility, and demonstrates the ability of our models for personalized POI recommendation.Dissertation/Thesis
Doctoral Dissertation Computer Science 2014
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Buczkowski, Aleksander. "Location-based Marketing: the academic framework." Master's thesis, 2012. http://hdl.handle.net/10362/8314.
Full textAbstract:
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Over the last several years one could observe revolution in location-based technologies and geospatial information. Location awareness of mobile devices resulted in development of Location-Based Services (LBS) that are realization of that revolution in the most personal and contextual way. The ability to reach consumers in the highly targeted manner based on spatio-temporal criteria, attracted marketers from the early beginning of LBS creating field called Location-Based Marketing. Today decreasing prices of smartphones and wireless internet, as well as integration of location-aware mobile solutions and social media is leading to new possibilities and opportunities. The academic and professional interests of the author made him noticed that although the industry has challenged a significant development, there is lack of publications that would put an academic framework on that progress. The research has fulfilled this gap by extensive investigation of the current state of the art of Location-Based Marketing and its foundations - Location Based Services. The dissertation provides academic framework by comprehensive analysis of the Location-Based Marketing from LBS and marketing perspective. Further the thesis is addressing the issue of significant discrepancy between theoretical concepts of measurable Location-Based Social Media data and the actual data than can be legally accessed and used for marketing analysis purposes by investigation a case study of Location-Based Social Network - Foursqaure and Location-Based Analytics platform VenueLabs.
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Lai, Wei-Cheng, and 賴韋呈. "A Study of User Check-in Location Privacy in Location Based Social Networks." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/57875793255182245814.
Full textAbstract:
碩士國立中興大學
資訊管理學系所
104
In recent years, as the Internet and mobile devices like smartphones and pads becoming popular, communications have become more and more convenient between people. Internet and mobile devices derive the rapid rise of online social networks. And the social networks also hide many privacy threats. The well-known location based social networks, for example, users may expose their location privacy information when they check in at a location or search a place. And the exposure of location privacy may cause some other privacy violation such as identity or daily living condition. With the Data transmission between users, it also derived more and more communication security problems, like key leakage, eavesdropping, stealing and tampering, etc. Therefore, how to guarantee the security of location privacy is an important issue in location based social networks. In this thesis, we propose a series of techniques and protocols for join, check-in, search and revocation based on the Zhao’s research. We develop a search method that followers can search for user’s check-in records in follower’s interest. Hide location information and check-in records from server to let users check in without worrying privacy leakage. And we improve the check-in index structure to reduce the storage load to let server efficiently search for user’s check-in records. Remove some encryption keys to reduce computation burden on user and server side. Our proposed framework improve the efficiency of structure and the security of location information.
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"Prediction and influence maximization in location-based social networks." 2012. http://library.cuhk.edu.hk/record=b5549174.
Full textAbstract:
基于地理位置的社交网络近年得到了非常多的关注。为了提升用戶粘性和吸引用戶，社交問路提供商会提供給用戶基于地理信息的广告和优惠券等服务。方了让广告和优惠券的投递更有效， 预测用戶下个可能访问的地点变得尤为重要。但是，预测地点一个不可避免的挑战就是數一百万计的候选地点构成了庞大的預測空间，使得整个预测过程变成复杂且缓慢。在本论文中，我們利用用戶签到的类別信息对潜在的用戶运动模式進行了建模并提出了一个混合隐马尔可夫模型去预测用戶下个可能访问的地点类别。基于预测出的类别，我們继而对用戶可能访问的地点进行了預測。在类別层次进行建模的好处是能有效地減少候选地点的个數并且能准确地描述用戶行动的实际意义。一般来說，用戶的行为会受到令人偏好的影响，基于这个現象，我們还运用分类的方法对用戶根据其令人愛好的不同進行了划分并对每个组群制定各自的隐马尔可夫模型。实验結果表示如果先预测用可能访问的地点类别，能使得地点预测空间极大地减少预测精度也会变高。在预测用可能访问的地点之后，另外一个很重要的问题是选择将优惠券投递给哪些用从而将产品或地点的影响最大化。在实际运用中，这种将影响最大化的算法会遇到速度上的壁垒。在本论文中，我们研究了在基于地理位置的社交网络中的影响最大化问题，并提出了一个分割方法能有效地提升算法的运行速度。实验结果显示我们的算法在于业界标准方法达到几乎一致的影响力的前提下，能更快地运行。
Location-based social networks have been gaining increasing popularity in recent years. To increase users’ engagement with location-based services, it is important to provide attractive features, one of which is geo-targeted ads and coupons. To make ads and coupons delivery more effective, it is essential to predict the location that is most likely to be visited by a user at the next step. However, an inherent challenge in location prediction is a huge prediction space, with millions of distinct check-in locations as prediction target. In this thesis we exploit the check-in category information to model the underlying user movement pattern. We propose a framework which uses a mixed hidden Markov model to predict the category of user activity at the next step and then predicts the most likely location given the estimated category distribution. The advantages of modeling on the category level include a significantly reduced prediction space and a precise expression of the semantic meaning of user activities. In addition, as user check-in behaviors are heavily influenced by their preferences, we take a clustering approach to group users with similar preferences, and train a separate hidden Markov model for each group. Extensive experimental results show that, with the predicted category distribution, the number of location candidates for prediction is much smaller, while the location prediction accuracy becomes higher.
Choosing the right users to deliver the coupons and maximizing the influence spread is also an important problem in LBSN, which is called influence maximization problem. In practice speed is an important issue to solve the influence maximization problem. In this thesis, we study the influence maximization problem in location-based social networks and propose a scalable partition approach to solve the influence maximization problem efficiently. Experimental results show that our partition approach achieves quite similar influence spread performance with the original influence maximization approach, while running much faster.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Zhu, Zhe.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2012.
Includes bibliographical references (leaves 93-101).
Abstracts also in Chinese.
Abstract --- p.i
Acknowledgement --- p.vi
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Background Study --- p.11
Chapter 2.1 --- Location prediction --- p.11
Chapter 2.2 --- Influence maximization --- p.16
Chapter 3 --- User Activity and Location Prediction in Location-based Social Networks --- p.20
Chapter 3.1 --- Data Analysis --- p.20
Chapter 3.1.1 --- Data Collection --- p.21
Chapter 3.1.2 --- Dataset Properties --- p.22
Chapter 3.2 --- User Activity Prediction --- p.26
Chapter 3.2.1 --- Definitions --- p.27
Chapter 3.2.2 --- Category Prediction based on HMM --- p.28
Chapter 3.2.3 --- Mixed HMM with Temporal and Spatial Covariates --- p.34
Chapter 3.2.4 --- User Preference Modeling --- p.41
Chapter 3.3 --- Location Prediction --- p.43
Chapter 3.4 --- Experimental Evaluation --- p.45
Chapter 3.4.1 --- Data Preparation --- p.46
Chapter 3.4.2 --- Category Prediction --- p.47
Chapter 3.4.3 --- Location Prediction --- p.51
Chapter 3.5 --- Summary --- p.58
Chapter 4 --- A Partition Approach to Scalable Influence Maximization in Location-based Social Networks --- p.60
Chapter 4.1 --- Problem definition --- p.60
Chapter 4.2 --- Influence probability --- p.62
Chapter 4.2.1 --- Base model --- p.62
Chapter 4.2.2 --- Distance and similarity model --- p.65
Chapter 4.2.3 --- Location entropy model --- p.72
Chapter 4.3 --- Partition approach --- p.74
Chapter 4.4 --- Evaluation --- p.79
Chapter 4.4.1 --- Data preparation --- p.79
Chapter 4.4.2 --- Precision evaluation --- p.80
Chapter 4.4.3 --- Influence spread evaluation --- p.83
Chapter 4.4.4 --- Running time --- p.86
Chapter 4.5 --- Summary --- p.88
Chapter 5 --- Conclusion --- p.90
Bibliography --- p.93
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Shih-Wei, Lin. "Dynamic Profile-Based Location Management Scheme for PCS Networks." 2006. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0002-1207200613212900.
Full text
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Liu, You-Ting, and 劉祐廷. "Location-Based Directory Service in Vehicular Ad-Hoc Networks." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/46855123286978388598.
Full textAbstract:
碩士國立暨南國際大學
資訊管理學系
100
The development of VANETs becomes mature in the recent years. Many academatic and industrial researches on VANET are focused on how to enhance the safety of road traffic to ensure a more convenient, comfortable and pleasant environment of dirving for both drivers and passengers. VANETs can be regarded as a special kind of mobile ad hoc networks composed of OBUs (On Board Units) and RSUs (Road Side Units). OBUs and RSUs communicate with each other. This thesis aims to study how to effectively provide location-based services (LBS) over VANETs. For better routing effcicency, this paper proposed the configuration of location-based IP addresses. An RSU with the support of DHCP (called DHCP-RSU) will allocate location-based IPv6 addresses to all vehicles within the local area. The vehicles can use the assigned IPv6 addresses to access the location-based services as well as other Internet services. This paper also proposed a mechanism of service discovery for LBS over VANETs. Through the proposed LBS discovery scheme, vehicles can easily and quickly discover location-dependent services and applications as soon as these vehicles are entering a new area. It is assumed that each county and city is associated with a directory server, which is responsible for the management of local service providers. According to preferences, drivers can download the directory of services of their interest, with the IP addresses of corresponding service providers. Then, drivers can access to the service providers via the provided IP addresses.
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Liu, Yu-Cheng, and 劉又誠. "Location-Based IP Assignment Protocol for Ad Hoc Networks." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/33853622703027155434.
Full textAbstract:
碩士國立中央大學
資訊工程研究所
93
In traditional wired networks, hosts are assigned IP-related information by a centralized server like Dynamic Host Configuration Protocol (DHCP) server, but it is not suitable for Mobile Ad Hoc Networks (MANETs). Due to each host will move and leave the network dynamically, the DHCP server cannot guarantee to be accessed by each host in the MANETs. Several decentralized solutions have been proposed for the issue of IP assignment. A new IP-address allocation algorithm, namely location-based IP assignment protocol, is proposed in this thesis. We divide the entire network into several disjoint and the same size cells and allocate each cell a segment of available IP-addresses. The first host appears in each cell becomes the role of coordinator which take over the available IP-addresses of the cell. A coordinator is responsible for assigning an IP-address to the new host and maintaining the IP-address pool of its own cell. Therefore, when a non-coordinator host enters any cell, it can easily get one IP-address from the coordinator. Since the distribution of the hosts is not uniform in the network, some coordinators may not have enough available IP-addresses for the new hosts. Thus, a dynamic IP-address redistribution mechanism is proposed to adjust the number of IP-addresses in each cell. With location information of each host, the scheme proposed in this thesis can avoid the problems of network partitioning and merger. The IP-addresses can be fully utilized and the latency time on invoking an IP-address is acceptable.
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Tseng, Chih-Hsiung, and 曾志雄. "Integrated Location-based Service Management Scheme for Wireless Networks." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/56129682013966246164.
Full textAbstract:
博士國立成功大學
資訊工程學系碩博士班
97
Over the last decade there has been a rapid growth of wireless communication technology. Among numerous wireless network architectures, the personal communication services (PCS) networks and wireless local area networks (WLAN) have attracted lots of attention. One of the core functionalities in wireless networks is the location service that provides location information for subscriber services, emergency services, and various mobile networks’ internal operations. In this paper, an integrated location management mechanism is proposed for heterogeneous wireless networks that combine PCS networks and WLAN. Three major functionalities in the integrated location management are the determination of the WLAN connectivity for a mobile terminal, the development of a local area location scheme for WLAN, and the location prediction module for PCS networks. This mechanism not only determines the location of a mobile client more precisely, but also reduces the cost of locating. The performance evaluation is conducted to demonstrate the effectiveness of the proposed mechanism for heterogeneous wireless networks. One of the core functionalities in wireless networks is the location service that provides location information for subscriber services, emergency services, and various mobile networks’ internal operations. In this paper, an integrated location management mechanism is proposed for heterogeneous wireless networks that combine PCS networks and WLAN. Three major functionalities in the integrated location management are the determination of the WLAN connectivity for a mobile terminal, the development of a local area location scheme for WLAN, and the location prediction module for PCS networks. The location management scheme provides location information to obtain from a hierarchical location database to mobile users and LBS providers. Additionally, a signal-based positioning algorithm is developed for indoor positioning based on WLAN Received Signal Strength Indication (RSSI). Approximated distribution modeling is applied to calculate the probability of users appearing in training points. This mechanism not only determines the location of a mobile client more precisely, but also reduces the cost of locating. The performance evaluation is conducted to demonstrate the effectiveness of the proposed mechanism for heterogeneous wireless networks. This investigation also presents the Location-based services scheduling mechanism in the Agent-based Smart (ABS) Home System that automates home service operations. The ABS home system comprises three subsystems, namely user interface, home gateway and home functionality. ABS home users can demand services with handheld devices through ABS user interface, and receive them through an agent cooperation mechanism. Three agents are designed and implemented in the agent platform: the manager agent schedules the service processes; the service agent manages service requests, and the task agent executes service operations. The Universal Plug and Play (UPnP) technology is applied for home and building control in ABS home. The proposed service scheduling mechanism provides services that are conveniently-provided, efficient, and comfortably-manipulated. An implementation of the ABS home system is introduced to illustrate the feasibility of the proposed architecture. A performance evaluation is performed to demonstrate the effectiveness of the proposed mechanism.
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Chen, Chun-Jie, and 陳浚桀. "Mobility-aware Influence Maximization in Location-based Social Networks." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/2n5476.
Full textAbstract:
碩士國立交通大學
資訊科學與工程研究所
105
Influence maximization is the problem that find the set of small seed users who can influence maximum number of users. The most popular application of influence maximization is viral marketing. Based on different promoted location, the preference of user will change, but most of works only consider the static propagation model and do not take properties of promoted location into consideration. For example, users are more likely go to the location which satisfy his historical movement behavior(user mobility). Thanks to the explosion of smartphones and web 2.0 techniques, users can post check-in records on location-based social networks (LBSNs) platform and share the experience with their friends. In this paper, we focus on geospatial properties between user and promoted location and propose the mobility-based influence maximization, which combine user mobility with traditional influence maximization problem for location promotion. To perform the query contained promoted location, the naive approach is to learn the probability from check-in records and then utilize the existing influence maximization algorithms to extract seed. To speed up the procedure, firstly, we propose CELF-based method and Estimation-based method with three index methods with 1-1⁄e guarantee. Further, we provide a approximation approach to get better efficiency with ε*(1-1⁄e) guarantee. Experiment results on two real datasets to demonstrate the effectiveness and efficiency of our methods and state-of-art algorithms.
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Lin, Shih-Wei, and 林世偉. "Dynamic Profile-Based Location Management Scheme for PCS Networks." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/67341762778371450626.
Full textAbstract:
博士淡江大學
資訊工程學系博士班
94
The personal communication service (PCS) networks can provide ubiquitous and customized services for mobiles users. The key issue is the location management, which affects the performance of PCS networks. In this thesis, we propose a profiles-based multi-location management scheme by using user mobility profile (UMP) to reduce the cost of location update and paging in the wireless networks. In this thesis, we use two management schemes to manage location of users: Profile-based (UMP mode) and LA-based (LA mode). If mobile users have regular walk paths, we use Profile-based management scheme to manage his/her location. Under the UMP mode, if mobile user enters a new cell and the cell id is out of his UMP, then location update is executed and the location management mode changes to the LA mode. When a call arrivals, the networks first check the mobility management mode, if the called user is under the UMP mode, then the system paging the user according to paging rules. The rules of change mode between UMP and LA are also presented in this thesis. In the performance evaluation, the system can reduce 14% location update cost and 15% paging cost by comparing with traditional PCS networks, if the system has 20% users have their profiles and those users follow their profiles with 71% probability.
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Lu, Shao-Ming, and 陸紹民. "A Novel Location Management in IP-Based Cellular Networks." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/24963772235741917797.
Full textAbstract:
碩士國立中正大學
通訊工程研究所
91
Mobile IP provides a simple and scalable global mobility solution that supports users to access the Internet anytime and anywhere. As the number or the velocity of the Mobile IP users grows, Cellular IP decreases the signaling overhead associated with mobility management in IP-based networks. In this thesis, we introduce a novel location management approach which has two enhancements of Location Area paging mechanism. First, it can further reduce unnecessary registrations by a new construction of paging area groups (PAG) and the configuration of paging area identifiers (PAI). Second, it uses Pointer Forwarding (PF) strategy to limit the paging flooding. Finally, this paper also shows a signaling cost analysis and simulation results with and without such enhancements.