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Journal articles on the topic 'Mobile opportunistic networks'

Author: Grafiati

Published: 4 June 2021

Last updated: 7 September 2023

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1

Ciobanu, Radu Ioan, and Ciprian Dobre. "Opportunistic Networks." International Journal of Virtual Communities and Social Networking 5, no. 2 (2013): 11–26. http://dx.doi.org/10.4018/jvcsn.2013040102.

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When mobile devices are unable to establish direct communication, or when communication should be offloaded to cope with large throughputs, mobile collaboration can be used to facilitate communication through opportunistic networks. These types of networks, formed when mobile devices communicate only using short-range transmission protocols, usually when users are close, can help applications still exchange data. Routes are built dynamically, since each mobile device is acting according to the store-carry-and-forward paradigm. Thus, contacts are seen as opportunities to move data towards the d

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2

Vidhya Lakshmi, Vimitha R., and Gireesh Kumar T. "Opportunistic mobile social networks: architecture, privacy, security issues and future directions." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 2 (2019): 1145. http://dx.doi.org/10.11591/ijece.v9i2.pp1145-1152.

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Mobile Social Networks and its related applications have made a very great impact in the society. Many new technologies related to mobile social networking are booming rapidly now-a-days and yet to boom. One such upcoming technology is Opportunistic Mobile Social Networking. This technology allows mobile users to communicate and exchange data with each other without the use of Internet. This paper is about Opportunistic Mobile Social Networks, its architecture, issues and some future research directions. The architecture and issues of Opportunistic Mobile Social Networks are compared with that

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3

Patra, Tapas Kumar, and Albert Sunny. "Forwarding in Heterogeneous Mobile Opportunistic Networks." IEEE Communications Letters 22, no. 3 (2018): 626–29. http://dx.doi.org/10.1109/lcomm.2018.2790393.

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4

Abouaroek, Musaeed, and Khaleel Ahmad. "Node Authentication Using NTRU Algorithm in Opportunistic Network." Scalable Computing: Practice and Experience 20, no. 1 (2019): 83–92. http://dx.doi.org/10.12694/scpe.v20i1.1481.

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The demand for using wireless paradigms for performing various information and communication operations has been exploded. The opportunistic networks is a special type of delay tolerant networks proposed to operate in an emergency manner to facilitate mobile connectivity between the nodes when there is no connectivity. These emergencies are caused either by human-made or natural disasters. Opportunistic Networks depend on mobile phones and other mobile devices that carry wireless technology. This paper is an attempt to expand the opportunistic network through the authentication nodes. We propo

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Zhao, Yan, and Farzana Akter. "Adaptive Clustering Algorithm for IIoT Based Mobile Opportunistic Networks." Security and Communication Networks 2022 (May 6, 2022): 1–11. http://dx.doi.org/10.1155/2022/3872214.

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The clustering algorithms play a crucial role for energy saving solutions in mobile opportunistic networks. If the selection of cluster head is made appropriately, then the energy can be consumed optimally. The existing clustering algorithms do not consider the optimal selection of the cluster head resulting in low survival rates and high energy consumption rates in nodes. The adaptive clustering is required in Industrial Internet of Things (IIoT) based sophisticated networks where seamless connectivity is imperative for rapid communication. In order to meet this research gap, an adaptive clus

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Yan, Yeqing, Zhigang Chen, Jia Wu, and Leilei Wang. "An Effective Data Transmission Algorithm Based on Social Relationships in Opportunistic Mobile Social Networks." Algorithms 11, no. 8 (2018): 125. http://dx.doi.org/10.3390/a11080125.

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With the popularization of mobile communication equipment, human activities have an increasing impact on the structure of networks, and so the social characteristics of opportunistic networks become increasingly obvious. Opportunistic networks are increasingly used in social situations. However, existing routing algorithms are not suitable for opportunistic social networks, because traditional opportunistic network routing does not consider participation in human activities, which usually causes a high ratio of transmission delay and routing overhead. Therefore, this research proposes an effec

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Dash, Sanjit Kumar, Aiswaryalaxmi Pradhan, Sasmita Mishra, and Jibitesh Mishra. "Lightweight Opportunistic Mobile Data Offloading." International Journal of Mobile Devices, Wearable Technology, and Flexible Electronics 9, no. 1 (2018): 1–15. http://dx.doi.org/10.4018/ijmdwtfe.2018010101.

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Current cellular networks are overloaded due to the increasing number of smartphones and demands for bandwidth-eager multimedia content. Upgrading the existing infrastructure of the cellular system is the most straight forward solution to meet the growing demand. Apart from this, offloading mobile data through Wi-Fi can be a feasible solution. Mobile offloading via Wi-Fi is the latest emerging trend in research and industry. In this article, the authors have proposed a framework for mobile data offloading for both cellular and Wi-Fi networks. The authors have introduced a daemon process-based

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8

Zhang, Junbao, Haojun Huang, Geyong Min, Wang Miao, and Dapeng Wu. "Social-Aware Routing in Mobile Opportunistic Networks." IEEE Wireless Communications 28, no. 2 (2021): 152–58. http://dx.doi.org/10.1109/mwc.001.2000189.

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9

Mtibaa, Abderrahmen. "Towards Node Cooperation in Mobile Opportunistic Networks." Qatar Foundation Annual Research Forum Proceedings, no. 2011 (November 2011): CSO12. http://dx.doi.org/10.5339/qfarf.2011.cso12.

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10

Li, He, Kaoru Ota, Mianxiong Dong, and Minyi Guo. "Mobile Crowdsensing in Software Defined Opportunistic Networks." IEEE Communications Magazine 55, no. 6 (2017): 140–45. http://dx.doi.org/10.1109/mcom.2017.1600719.

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11

Saha, Barun Kumar, and Sudip Misra. "Named Content Searching in Opportunistic Mobile Networks." IEEE Communications Letters 20, no. 10 (2016): 2067–70. http://dx.doi.org/10.1109/lcomm.2016.2587281.

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12

Radenkovic, Milena, Abderrahim Benslimane, and Derek McAuley. "Reputation Aware Obfuscation for Mobile Opportunistic Networks." IEEE Transactions on Parallel and Distributed Systems 26, no. 1 (2015): 230–40. http://dx.doi.org/10.1109/tpds.2013.265.

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13

Wang, Xia, Shengling Wang, Wenshuang Liang, Rongfang Bie, and Feng Zhao. "The dissemination distance of mobile opportunistic networks." Personal and Ubiquitous Computing 19, no. 7 (2015): 1011–19. http://dx.doi.org/10.1007/s00779-015-0884-6.

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14

Wang, Liang, Zhiwen Yu, Dingqi Yang, Tao Ku, Bin Guo, and Huadong Ma. "Collaborative Mobile Crowdsensing in Opportunistic D2D Networks." ACM Transactions on Sensor Networks 15, no. 3 (2019): 1–30. http://dx.doi.org/10.1145/3317689.

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15

Kaushik, Bhanu, Honggang Zhang, Xinyu Yang, Xinwen Fu, Benyuan Liu, and Jie Wang. "Providing service assurance in mobile opportunistic networks." Computer Networks 74 (December 2014): 114–40. http://dx.doi.org/10.1016/j.comnet.2014.07.018.

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16

Ciobanu, Radu-Ioan, Daniel Gutierrez Reina, Ciprian Dobre, and Sergio L. Toral. "Context-adaptive forwarding in mobile opportunistic networks." Annals of Telecommunications 73, no. 9-10 (2018): 559–75. http://dx.doi.org/10.1007/s12243-018-0654-3.

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17

Martín-Pascual, Miguel Ángel, and Celia Andreu-Sánchez. "Practical Application of Mesh Opportunistic Networks." Applied System Innovation 6, no. 3 (2023): 60. http://dx.doi.org/10.3390/asi6030060.

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Opportunistic networks allow for communication between nearby mobile devices through a radio connection, avoiding the need for cellular data coverage or a Wi-Fi connection. The limited spatial range of this type of communication can be overcome by using nodes in a mesh network. The purpose of this research was to examine a commercial application of electronic mesh communication without a mobile data plan, Wi-Fi, or satellite. A mixed study, with qualitative and quantitative strategies, was designed. An experimental session, in which participants tested opportunistic networks developing differe

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18

Visca, Jorge, and Javier Baliosian. "rl4dtn: Q-Learning for Opportunistic Networks." Future Internet 14, no. 12 (2022): 348. http://dx.doi.org/10.3390/fi14120348.

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Opportunistic networks are highly stochastic networks supported by sporadic encounters between mobile devices. To route data efficiently, opportunistic-routing algorithms must capitalize on devices’ movement and data transmission patterns. This work proposes a routing method based on reinforcement learning, specifically Q-learning. As usual in routing algorithms, the objective is to select the best candidate devices to put forward once an encounter occurs. However, there is also the possibility of not forwarding if we know that a better candidate might be encountered in the future. This decisi

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19

Zhang, Sheng, Houzhong Liu, Caisen Chen, Zhaojun Shi, and William Wei Song. "Activity-based routing algorithm in opportunistic mobile social networks." International Journal of Distributed Sensor Networks 17, no. 9 (2021): 155014772110412. http://dx.doi.org/10.1177/15501477211041272.

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In opportunistic mobile social networks, nodes are clustered according to their interests or hobbies and take part in different activities regularly. We delve into the temporal and spatial mobility characteristics of network nodes and put forward an activity-based message opportunistic forwarding algorithm. The main idea of the algorithm is that we choose different message forwarding methods according to the situation of nodes participating in activities. If the source node and the destination node are both attend in the same activities, we select the best relay node which has the biggest deli

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20

SMITH, ANTHONY, and RICHARD HILL. "MEASURING EFFICIENCY IN OPPORTUNISTIC AD HOC NETWORKS." Journal of Interconnection Networks 12, no. 03 (2011): 189–203. http://dx.doi.org/10.1142/s0219265911002940.

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Opportunistic Networks are examples of wireless, ad hoc networks where there is an absence of a continuous end-to-end path. The proliferation of mobile device usage creates opportunities for nodes to forward packets in a dynamic way, utilizing nodes as they present themselves. In more conventional, static network infrastructures, it is typical to measure efficiency of message passing between nodes. We review approaches to the measurement of efficiency in networks, and propose a qualitative and quantitative metrics framework and simulation model that would be suitable for the evaluation of perf

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21

Chen, Bangyuan, and Lingna Chen. "NPLP: An Improved Routing-Forwarding Strategy Utilizing Node Profile and Location Prediction for Opportunistic Networks." Information 10, no. 10 (2019): 306. http://dx.doi.org/10.3390/info10100306.

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Opportunistic networks are considered as the promising network structures to implement traditional and typical infrastructure-based communication by enabling smart mobile devices in the networks to contact with each other within a fixed communication area. Because of the intermittent and unstable connections between sources and destinations, message routing and forwarding in opportunistic networks have become challenging and troublesome problems recently. In this paper, to improve the data dissemination environment, we propose an improved routing-forwarding strategy utilizing node profile and

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22

Xiao, Mingjun, Jie Wu, and Liusheng Huang. "Community-Aware Opportunistic Routing in Mobile Social Networks." IEEE Transactions on Computers 63, no. 7 (2014): 1682–95. http://dx.doi.org/10.1109/tc.2013.55.

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23

Do, Tien Van, Nam H. Do, Ádám Horváth, and Jinting Wang. "Modelling opportunistic spectrum renting in mobile cellular networks." Journal of Network and Computer Applications 52 (June 2015): 129–38. http://dx.doi.org/10.1016/j.jnca.2015.02.007.

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24

Pal, Sujata, and Sudip Misra. "DISIDE: Distributed strategy identification in opportunistic mobile networks." Computer Communications 71 (November 2015): 119–28. http://dx.doi.org/10.1016/j.comcom.2015.08.020.

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25

Thomas, Bryce, Raja Jurdak, and Ian Atkinson. "Opportunistic content diffusion in mobile ad hoc networks." Ad Hoc Networks 45 (July 2016): 34–46. http://dx.doi.org/10.1016/j.adhoc.2016.02.022.

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26

Wang, Shengling, Min Liu, Xiuzhen Cheng, Zhongcheng Li, Jianhui Huang, and Biao Chen. "Opportunistic Routing in Intermittently Connected Mobile P2P Networks." IEEE Journal on Selected Areas in Communications 31, no. 9 (2013): 369–78. http://dx.doi.org/10.1109/jsac.2013.sup.0513033.

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27

Fan, Xiaoguang, Victor O. K. Li, and Kuang Xu. "Fairness Analysis of Routing in Opportunistic Mobile Networks." IEEE Transactions on Vehicular Technology 63, no. 3 (2014): 1282–95. http://dx.doi.org/10.1109/tvt.2013.2282341.

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28

Lai, Yongxuan, Zhengkun Chen, Weicong Wu, and Tianli Ma. "Multiple-resolution content sharing in mobile opportunistic networks." Wireless Communications and Mobile Computing 15, no. 16 (2014): 1991–2003. http://dx.doi.org/10.1002/wcm.2472.

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29

Yang, Yibo, Honglin Zhao, Jinlong Ma, and Xiaowei Han. "Social-aware data dissemination in opportunistic mobile social networks." International Journal of Modern Physics C 28, no. 09 (2017): 1750115. http://dx.doi.org/10.1142/s0129183117501157.

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Opportunistic Mobile Social Networks (OMSNs), formed by mobile users with social relationships and characteristics, enhance spontaneous communication among users that opportunistically encounter each other. Such networks can be exploited to improve the performance of data forwarding. Discovering optimal relay nodes is one of the important issues for efficient data propagation in OMSNs. Although traditional centrality definitions to identify the nodes features in network, they cannot identify effectively the influential nodes for data dissemination in OMSNs. Existing protocols take advantage of

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30

Kurdi, Shivan Fazil. "Mobility-Based Routing in Opportunistic Networks." International Journal of Technology Diffusion 3, no. 2 (2012): 28–35. http://dx.doi.org/10.4018/jtd.2012040103.

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In Opportunistic Networks (OppNets) nodes are only intermittently connected. A complete path from the sender node to the receiver does not exist. Mobile objects exploit direct contact for message transmission without relying on an existing end to end infrastructure. In such networks, routing is a challenging issue. Nevertheless, routing protocols in the mobility-based class of OppNets exploit some context information such as node mobility information and patterns to make forwarding decision, since the effectiveness of routing depends on node mobility. The aim of this research is to identify, e

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31

Liu, Kanghuai, Zhigang Chen, Jia Wu, and Leilei Wang. "FCNS: A Fuzzy Routing-Forwarding Algorithm Exploiting Comprehensive Node Similarity in Opportunistic Social Networks." Symmetry 10, no. 8 (2018): 338. http://dx.doi.org/10.3390/sym10080338.

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At the dawn of big data and 5G networks, end-to-end communication with large amounts of data between mobile devices is difficult to be implemented through the traditional face-to-face transmission mechanism in social networks. Consequently, opportunistic social networks proposed that message applications should choose proper relay nodes to perform effective data transmission processes. At present, several routing algorithms, based on node similarity, attempt to use the contextual information related to nodes and the special relationships between them to select a suitable relay node among neigh

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32

Ge, Lige, and Shengming Jiang. "An Efficient Opportunistic Routing Based on Prediction for Nautical Wireless Ad Hoc Networks." Journal of Marine Science and Engineering 10, no. 6 (2022): 789. http://dx.doi.org/10.3390/jmse10060789.

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Nautical wireless ad hoc networks are becoming increasingly popular in oceans due to their easy deployment and self-curing capability. They may alternate frequently between connected mobile ad hoc networks and partitioned opportunistic networks due to mobility in large spaces. Traditional mobile ad hoc network routing is used to find the shortest route for connected networks. However, for opportunistic networks, routing schemes with a broadcast nature mainly exploit the reduction in message duplication and the local relaying technologies described in the literature, which may lead to unnecessa

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33

Munjal, Aarti, Tracy Camp, and Nils Aschenbruck. "Changing Trends in Modeling Mobility." Journal of Electrical and Computer Engineering 2012 (2012): 1–16. http://dx.doi.org/10.1155/2012/372572.

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A phenomenal increase in the number of wireless devices has led to the evolution of several interesting and challenging research problems in opportunistic networks. For example, the random waypoint mobility model, an early, popular effort to model mobility, involves generatingrandommovement patterns. Previous research efforts, however, validate that movement patterns are not random; instead, human mobility is predictable to some extent. Since the performance of a routing protocol in an opportunistic network is greatly improved if the movement patterns of mobile users can be somewhat predicted

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34

Zhang, Zhen Yu, Shao Jie Wen, and Wen Zhong Yang. "Based on Energy-Efficient Opportunistic Multicast Routing for Mobile Wireless Sensor Networks." Applied Mechanics and Materials 599-601 (August 2014): 851–55. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.851.

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Energy-efficient is one of the main problems among all the problems in mobile wireless sensor networks, for improving the energy efficiency of the nodes in the multicast environment and complete the communication works with the minimum cost, we present a based on energy-efficient opportunistic multicast routing for mobile wireless sensor networks. In order to increase the reliability of links, we use opportunistic routing and collaboration mechanism to realize the routing method, and then use the path aggregation to reduce the energy consumption of the whole network. The results of simulation

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35

Yang, Guisong, Zhiwei Peng, and Xingyu He. "Data Collection Based on Opportunistic Node Connections in Wireless Sensor Networks." Sensors 18, no. 11 (2018): 3697. http://dx.doi.org/10.3390/s18113697.

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The working–sleeping cycle strategy used for sensor nodes with limited power supply in wireless sensor networks can effectively save their energy, but also causes opportunistic node connections due to the intermittent communication mode, which can affect the reliability of data transmission. To address this problem, a data collection scheme based on opportunistic node connections is proposed to achieve efficient data collection in a network with a mobile sink. In this scheme, the mobile sink first broadcasts a tag message to start a data collection period, and all nodes that receive this messa

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36

Socievole, Annalisa, Antonio Caputo, Floriano De Rango, and Peppino Fazio. "Routing in Mobile Opportunistic Social Networks with Selfish Nodes." Wireless Communications and Mobile Computing 2019 (February 3, 2019): 1–15. http://dx.doi.org/10.1155/2019/6359806.

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When the connection to Internet is not available during networking activities, an opportunistic approach exploits the encounters between mobile human-carried devices for exchanging information. When users encounter each other, their handheld devices can communicate in a cooperative way, using the encounter opportunities for forwarding their messages, in a wireless manner. But, analyzing real behaviors, most of the nodes exhibit selfish behaviors, mostly to preserve the limited resources (data buffers and residual energy). That is the reason why node selfishness should be taken into account whe

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37

Guo, Mei, and Min Xiao. "MSSN: An Attribute-Aware Transmission Algorithm Exploiting Node Similarity for Opportunistic Social Networks." Information 10, no. 10 (2019): 299. http://dx.doi.org/10.3390/info10100299.

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Recently, with the development of big data and 5G networks, the number of intelligent mobile devices has increased dramatically, therefore the data that needs to be transmitted and processed in the networks has grown exponentially. It is difficult for the end-to-end communication mechanism proposed by traditional routing algorithms to implement the massive data transmission between mobile devices. Consequently, opportunistic social networks propose that the effective data transmission process could be implemented by selecting appropriate relay nodes. At present, most existing routing algorithm

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38

Wang, Zhifei, Gang Xu, Na Zhang, Zhihan Qi, Fengqi Wei, and Liqiang He. "Ferry Node Identification Model for the Security of Mobile Ad Hoc Network." Security and Communication Networks 2021 (January 5, 2021): 1–13. http://dx.doi.org/10.1155/2021/6682311.

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An opportunistic network is a special type of wireless mobile ad hoc network that does not require any infrastructure, does not have stable links between nodes, and relies on node encounters to complete data forwarding. The unbalanced energy consumption of ferry nodes in an opportunistic network leads to a sharp decline in network performance. Therefore, identifying the ferry node group plays an important role in improving the performance of the opportunistic network and extending its life. Existing research studies have been unable to accurately identify ferry node clusters in opportunistic n

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39

Yang, Ming Xia, Shuang Xia Han, Cai Yun Yang, Lu Zhang, and Dong Fen Ye. "Survey on Node Mobility Model for Opportunistic Network." Applied Mechanics and Materials 52-54 (March 2011): 1253–57. http://dx.doi.org/10.4028/www.scientific.net/amm.52-54.1253.

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Opportunistic networks is one of the newest hot research spots in wireless networks after mobile ad hoc net-works(MANET) and wireless sensor networks(WSN). Mobility model describes mobility manners of nodes. It has been widely used in research on wireless network. This paper firstly introduced, classifies, and compares the current familiar mobility models. Secondly, it classifies, and compares the current familiar mobility models. Next, it was discussed that current research focus on new mobility models, analysis of nodes mobility features, trace strategy, and evaluation of mobility model. Fin

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40

Wu, Yahui, Su Deng, and Hongbin Huang. "Information Spreading in Mobile Opportunistic Networks with Limited Infectability." Journal of the Physical Society of Japan 82, no. 11 (2013): 114001. http://dx.doi.org/10.7566/jpsj.82.114001.

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41

Guidec, Frédéric, Nicolas Le Sommer, and Yves Mahéo. "Opportunistic Software Deployment in Disconnected Mobile Ad Hoc Networks." International Journal of Handheld Computing Research 1, no. 1 (2010): 24–42. http://dx.doi.org/10.4018/jhcr.2010090902.

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This paper presents a middleware platform allowing the dissemination of software components on handheld devices forming a disconnected MANET. It is based on a model that exploits peer-to-peer and opportunistic interactions between neighboring devices to deploy component-based applications, without relying on any kind of infrastructure network. Each device runs a deployment manager, which strive to fill a local component repository with software components so as to be able to satisfy the deployment requests expressed by the user. To do so the deployment manager interacts with peer managers loca

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42

Goudar, Gourish, and Suvadip Batabyal. "Point of Congestion in Large Buffer Mobile Opportunistic Networks." IEEE Communications Letters 24, no. 7 (2020): 1586–90. http://dx.doi.org/10.1109/lcomm.2020.2986230.

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43

You, Lei, Jianbo Li, Changjiang Wei, Jixing Xu, and Chenqu Dai. "A Data Item Selection Mechanism for Mobile Opportunistic Networks." International Journal of Distributed Sensor Networks 10, no. 5 (2014): 541065. http://dx.doi.org/10.1155/2014/541065.

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Wang, Eric Ke, Yueping Li, Yunming Ye, S. M. Yiu, and Lucas C. K. Hui. "A Dynamic Trust Framework for Opportunistic Mobile Social Networks." IEEE Transactions on Network and Service Management 15, no. 1 (2018): 319–29. http://dx.doi.org/10.1109/tnsm.2017.2776350.

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Wang, Fang, Zhaocheng Wang, Zhixing Yang, and Sheng Chen. "Contact duration aware cache refreshing for mobile opportunistic networks." IET Networks 5, no. 4 (2016): 93–103. http://dx.doi.org/10.1049/iet-net.2015.0086.

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46

Misra, Sudip, Sujata Pal, and Barun Kumar Saha. "Distributed Information-Based Cooperative Strategy Adaptationin Opportunistic Mobile Networks." IEEE Transactions on Parallel and Distributed Systems 26, no. 3 (2015): 724–37. http://dx.doi.org/10.1109/tpds.2014.2314687.

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47

Zakhary, Sameh, and Abderrahim Benslimane. "On location-privacy in opportunistic mobile networks, a survey." Journal of Network and Computer Applications 103 (February 2018): 157–70. http://dx.doi.org/10.1016/j.jnca.2017.10.022.

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48

Saha, Barun Kumar, Sudip Misra, and Sujata Pal. "SeeR: Simulated Annealing-Based Routing in Opportunistic Mobile Networks." IEEE Transactions on Mobile Computing 16, no. 10 (2017): 2876–88. http://dx.doi.org/10.1109/tmc.2017.2673842.

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49

Zakhary, Sameh, Milena Radenkovic, and Abderrahim Benslimane. "Efficient Location Privacy-Aware Forwarding in Opportunistic Mobile Networks." IEEE Transactions on Vehicular Technology 63, no. 2 (2014): 893–906. http://dx.doi.org/10.1109/tvt.2013.2279671.

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Zhou, Huan, Hongyang Zhao, Jiming Chen, Chi Harold Liu, and Jialu Fan. "Adaptive Working Schedule for Duty-Cycle Opportunistic Mobile Networks." IEEE Transactions on Vehicular Technology 63, no. 9 (2014): 4694–703. http://dx.doi.org/10.1109/tvt.2014.2312934.

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