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Journal articles on the topic 'IoT and mobile networks'
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Hu, Xiping, Zhaolong Ning, Kuan Zhang, Edith Ngai, Kun Bai, and Fei Wang. "Crowdsourcing for Mobile Networks and IoT." Wireless Communications and Mobile Computing 2018 (June 5, 2018): 1–2. http://dx.doi.org/10.1155/2018/6231236.
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Salva-Garcia, Pablo, Jose M. Alcaraz-Calero, Qi Wang, Jorge Bernal Bernabe, and Antonio Skarmeta. "5G NB-IoT: Efficient Network Traffic Filtering for Multitenant IoT Cellular Networks." Security and Communication Networks 2018 (December 10, 2018): 1–21. http://dx.doi.org/10.1155/2018/9291506.
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Internet of Things (IoT) is a key business driver for the upcoming fifth-generation (5G) mobile networks, which in turn will enable numerous innovative IoT applications such as smart city, mobile health, and other massive IoT use cases being defined in 5G standards. To truly unlock the hidden value of such mission-critical IoT applications in a large scale in the 5G era, advanced self-protection capabilities are entailed in 5G-based Narrowband IoT (NB-IoT) networks to efficiently fight off cyber-attacks such as widespread Distributed Denial of Service (DDoS) attacks. However, insufficient research has been conducted in this crucial area, in particular, few if any solutions are capable of dealing with the multiple encapsulated 5G traffic for IoT security management. This paper proposes and prototypes a new security framework to achieve the highly desirable self-organizing networking capabilities to secure virtualized, multitenant 5G-based IoT traffic through an autonomic control loop featured with efficient 5G-aware traffic filtering. Empirical results have validated the design and implementation and demonstrated the efficiency of the proposed system, which is capable of processing thousands of 5G-aware traffic filtering rules and thus enables timely protection against large-scale attacks.
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Al-Khalidi, Mohammed, Rabab Al-Zaidi, Ahmed M. Abubahia, Hari Mohan Pandey, Md Israfil Biswas, and Mohammad Hammoudeh. "Global IoT Mobility: A Path Based Forwarding Approach." Journal of Sensor and Actuator Networks 11, no. 3 (2022): 41. http://dx.doi.org/10.3390/jsan11030041.
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With the huge proliferation of mobile Internet of Things (IoT) devices such as connected vehicles, drones, and healthcare wearables, IoT networks are promising mobile connectivity capacity far beyond the conventional computing platforms. The success of this service provisioning is highly dependent on the flexibility offered by such enabling technologies to support IoT mobility using different devices and protocol stacks. Many of the connected mobile IoT devices are autonomous, and resource constrained, which poses additional challenges for mobile IoT communication. Therefore, given the unique mobility requirements of IoT devices and applications, many challenges are still to be addressed. This paper presents a global mobility management solution for IoT networks that can handle both micro and macro mobility scenarios. The solution exploits a path-based forwarding fabric together with mechanisms from Information-Centric Networking. The solution is equally suitable for legacy session-based mobile devices and emerging information-based IoT devices such as mobile sensors. Simulation evaluations have shown minimum overhead in terms of packet delivery and signalling costs to support macro mobility handover across different IoT domains.
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S. Jeba, Shiny. "A review on application of MANET-IoT." i-manager's Journal on Mobile Applications and Technologies 9, no. 1 (2022): 28. http://dx.doi.org/10.26634/jmt.9.1.18922.
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Mobile Ad-hoc Networks (MANETs) will be very important for the Internet of Things (IoT). MANET is a decentralized selforganizing wireless network. Every device in MANET is completely free and can move in any direction. The interaction of the Internet of Things with wireless sensors and Mobile Ad-hoc Networks allows for the development of a new MANET-IoT framework. Innovative MANET-IoT systems are created through the interaction between Wireless Sensor Networks (WSN) and the IoT, which creates numerous design difficulties. Several application domains use MANET-based IoT systems. These systems increase user mobility while reducing costs. At the same time, new complex problems are emerging in the area of networking. This paper analyzes the literature on various MANET-IoT applications using wireless sensor networks (WSNs).
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Manuel, Fernando Quiñones, Patricio Pachar Bravo Hever, Martínez-Curipoma Javier, Quiñones Luis, and Torres Rommel. "Developing and evaluation of an IoT mobile gateway for 4G LTE networks." Enfoque UTE 11, no. 4 (2020): 16–26. https://doi.org/10.29019/enfoqueute.v11n4.634.
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The current trend is to connect everything to network to be monitored and controlled remotely through own concept IoT technologies. One of the problems is to connect the devices to a network, using technologies with sufficient coverage and capacity, so this article shows the development of a mobile gateway for IoT applications under the Android platform evaluated in 4G mobile networks. The IoT mobile gateway sends the data collected from sensors by selecting the MQTT and HTTP protocols, to IoT platforms on the Internet. The architecture is composed of temperature, luminosity and pressure sensors that are integrated into a sensor node which function is for data collection, processing and then via Bluetooth is sent to an Android smartphone where an application that performs the mobile gateway function is running, here data network are sent through the 4G LTE network to the IoT platforms of Ubidots and Watson IoT. Subsequently, tests were carried out with various metrics such as latency, energy consumption and connection costs. It concludes that IoT mobile gateway has better performance under MQTT protocol compared to HTTP.
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D, Giji Kiruba. "A Survey of Secured Cluster Head: SCH Based Routing Scheme for Iot Based Mobile Wireless Sensor Network." ECS Transactions 107, no. 1 (2022): 16725–45. http://dx.doi.org/10.1149/10701.16725ecst.
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This paper describe various energy resourceful routing schemes for secured IoT-mobile sensor network and skeleton for clustered IoT-mobile sensor networks. The primitive design of a battery arrayed mobile wireless IoT-sensor nodes is to increase the transmission energy. The proposed work has the advantage that the communication and computation overheads are low and give better performance in terms of network lifetime, energy consumption, and intrusion detection. This paper proposes a secured energy resourceful routing protocol for security awareness in IoT-mobile wireless sensor networks. The intrusion and normal interruption are much related and it is hard to determine. A routing protocol is designed for selecting the appropriate path for data forwarding between cluster head and base station.
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Balan, Titus, Dan Robu, and Florin Sandu. "Multihoming for Mobile Internet of Multimedia Things." Mobile Information Systems 2017 (2017): 1–16. http://dx.doi.org/10.1155/2017/6965028.
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Mobility, redundancy, and bandwidth requirements are transforming the communication models used for IoT, mainly in case of Critical Communications and multimedia streaming (“IoMT, Internet of Multimedia Things”), as wireless video traffic is expected to be 60–75% of the global mobile traffic by 2020. One of the characteristics of 5G networks will be the proliferation of different/heterogeneous radio networks (virtualized radio access networks, RAN, new energy-efficient radios, femtocells, and offloading capabilities) and the possibility for IoT objects to connect and load-balance between dual and multiple RANs. This paper focuses on the possibility of using LISP (Locator Identifier Separation Protocol) for multihoming and load-balancing purposes and presents an illustrative scenario for the case of mobile IoT (e.g., the “things” part of vehicular or public transportation systems, PTS) that are also intensive bandwidth consumers, like the case of connected multimedia “things.” We have implemented and tested a demonstrator of a mobile LISP IoT gateway that is also integrated with Cloud-based video analytics.
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S.SivaNageswara Rao, Dr, Orchu Aruna, and Dr K.Lakshminadh. "Mobile ad hoc network integrated wireless networks: a survey." International Journal of Engineering & Technology 7, no. 1.9 (2018): 217. http://dx.doi.org/10.14419/ijet.v7i1.9.9827.
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Now a day, every one using mobile devices for communicating with others. The development of new technologies, like Internet of Things (IoT) needs coverage, connectivity, scalability and QoS. In ubiquity networks, the major issues are coverage, connectivity, scalability and QoS. To solve these limitations, integrating wireless networks with ad hoc networks. This paper provides detail survey on how ad hoc networks are integrated with Cellular Network, Wireless Mesh Networks and Wireless Sensor Networks. This integration may resolve the problems of coverage, connectivity, scalability and QoS.
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Zhu, Fusheng, Liming Chen, Wen Zhou, et al. "Chebyshev-Gauss Approximation Analysis for Mobile Edge Computing-Aided IoT Networks." Wireless Communications and Mobile Computing 2022 (July 18, 2022): 1–6. http://dx.doi.org/10.1155/2022/3099914.
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Recently, mobile edge computing (MEC) has been widely applied into Internet of Things (IoT) networks, which has attracted a lot of attention from researchers. A critical challenge in the MEC-aided IoT networks is that the performance analysis is often complicated, where it is quite difficult for us to obtain some analytical or closed-form solution to the performance analysis, such as outage probability and bit error rate. This has been the bottleneck of the development of MEC-aided IoT networks. To address this challenge, we deeply investigate the Chebyshev-Gauss approximation method and derive the analytical solution to implement this powerful and useful approximation. We then give several examples to show the effectiveness of the Chebyshev-Gauss approximation in the performance analysis for the MEC-aided IoT systems. The results in this work can serve as an important reference and reveal some important inherent mechanisms for the MEC-aided IoT networks.
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Lin, Bao-Shuh Paul. "Toward an AI-Enabled SDN-based 5G & IoT Network." Network and Communication Technologies 5, no. 2 (2020): 7. http://dx.doi.org/10.5539/nct.v5n2p7.
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Artificial Intelligent technology has been applied to a wide variety of applications including products, systems, and services of the Information & Communications Technology (ICT) and non-ICT or traditional industries. The benefits of these applications includes performance improvement, optimization, intelligent.The 5G mobile/wireless networks have intelligent features of network slicing and edge computing because of network equipment system vendors apply AI technology to the mobile systems. On the other hand, many traditional industries have benefits from AI technology in particular Machine Learning (ML) and Deep Learning (DL). Recently in the agriculture, healthcare, finance, and many other applications and services have adopted AI/ML/DL technology even with the integration of 5G and Internet of Things (IoT). This article focuses on the system architecture and design of open networking (ON) solution of 5G, the approach of SDN/NFV-based 5G and IoT and how AI/ML interact with 5G/IoT and learns from these. We call this interaction as SDN-based 5G/IoT Network AI or AI-enabled SDN-based 5G/IoT Network.
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Lammatha, Kranthi K. "Data Mining on 5G Technology IOT." International Journal of Engineering and Computer Science 8, no. 05 (2019): 24655–60. http://dx.doi.org/10.18535/ijecs/v8i05.4291.
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Data Mining on 5G Technology IOT Currently, data mining is regarded as one of the essential factors for the next generation of mobile networks. Through research and data analysis, there are expectations that complexity of these networks will be overcome and it will be possible to carry out dynamic management and operation activities. In order to full comprehend the particulars of 5G network, there are certain kind of information that should be gathered by network components in order to be analyzed by a data mining scheme. The recent years have seen a tremendous effort put in the course of designing the 5th Generation of mobile networks (5G). The innovation of 5G mobile networks have been aimed at providing tailor cut solution for different kinds of industries particularly the telecommunication sector, intelligent transportation industries, health sector and even in smart factories. On the other hand, the scientific community has realized that big data solutions can significantly enhance the operation and management of both current and future mobile networks. Usually, data mining is employed in the course of discovering patterns and relationships between different variables particularly in large data sets. Through the use of statistical analysis, machine learning and artificial intelligence are used in the data set in the course of extracting necessary knowledge from the examined data. Data mining is integral in 5G technology because it is through data mining that 5G is considered different particularly through the ease in decision making process that has been offered by the system in order to mitigate some common challenges through a dynamic and proactive mechanism.
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Tang, Zhen, Xiaobin Fu, and Pingping Xiao. "Mobile Performance Intelligent Evaluation of IoT Networks Based on DNN." International Journal of Antennas and Propagation 2022 (March 16, 2022): 1–7. http://dx.doi.org/10.1155/2022/4038830.
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The rapid development of the sensor equipment has promoted the rapid growth of the Internet of Things (IoT). The IoT has been widely employed in the multidimensional signal processing and gradually formed the IoT networks. Mobile communication promotes the wide application of the IoT networks. In this study, the transmit antenna selection (TAS) scheme is employed to investigate the average symbol error probability (ASEP) performance of mobile IoT networks over the 2-Rayleigh channels. We first employ moment-generating function (MGF) approach to derive the exact ASEP expressions. We also investigate the outage probability (OP) performance and derive OP expressions. Employing the deep neural network (DNN), an OP intelligent prediction algorithm is proposed. Then, the numerical simulations are conducted to confirm the ASEP and OP performance analysis. The effect of different channel parameters is also analyzed. Compared with Nakagami and Rayleigh channel models, the 2-Rayleigh model has 83.6% and 59.1% increase in ASEP values, respectively. Compared with ELM and RBF models, the DNN model has 31.7% and 22.5% increase in OP prediction accuracy, respectively.
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Candal-Ventureira, David, Pablo Fondo-Ferreiro, Felipe Gil-Castiñeira, and Francisco Javier González-Castaño. "Quarantining Malicious IoT Devices in Intelligent Sliced Mobile Networks." Sensors 20, no. 18 (2020): 5054. http://dx.doi.org/10.3390/s20185054.
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The unstoppable adoption of the Internet of Things (IoT) is driven by the deployment of new services that require continuous capture of information from huge populations of sensors, or actuating over a myriad of “smart” objects. Accordingly, next generation networks are being designed to support such massive numbers of devices and connections. For example, the 3rd Generation Partnership Project (3GPP) is designing the different 5G releases specifically with IoT in mind. Nevertheless, from a security perspective this scenario is a potential nightmare: the attack surface becomes wider and many IoT nodes do not have enough resources to support advanced security protocols. In fact, security is rarely a priority in their design. Thus, including network-level mechanisms for preventing attacks from malware-infected IoT devices is mandatory to avert further damage. In this paper, we propose a novel Software-Defined Networking (SDN)-based architecture to identify suspicious nodes in 4G or 5G networks and redirect their traffic to a secondary network slice where traffic is analyzed in depth before allowing it reaching its destination. The architecture can be easily integrated in any existing deployment due to its interoperability. By following this approach, we can detect potential threats at an early stage and limit the damage by Distributed Denial of Service (DDoS) attacks originated in IoT devices.
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Zhao, Hong-Yan, Jia-Chen Wang, Xin Guan, Zhi-Hong Wang, Yong-Hui He, and Hong-Lin Xie. "Ant Colony System for Energy Consumption Optimization in Mobile IoT Networks." Journal of Circuits, Systems and Computers 29, no. 09 (2019): 2050150. http://dx.doi.org/10.1142/s0218126620501509.
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In this paper, a new algorithm is proposed for computing the node-disjoint optimal transmission energy consumption route for coded cooperative mobile IoT networks. Inspired by the potential benefits user cooperation can provide, we incorporate user cooperation to the mobile ad-hoc multi-hop IoT networks. Our results include a novel ant colony system-based node-disjoint energy-efficient routing algorithm. Ant colony system can approximate the optimal route by local information and is thus very suitable for mobile IoT network environment. In particular, ant algorithm makes history-sensitive choice and thus can significantly outperform the greedy algorithm. In addition, it can efficiently handle the case of multiple sources and multiple destinations. For a large IoT network, we investigate the multi-scale ant colony system and when compared to Dijkstra algorithm, such an algorithm usually shortens the runtime by a factor of several hundred.
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Sharma, Vishal, Daniel G. Reina, Zengpeng Li, Kathiravan Srinivasan, Navuday Sharma, and Vinod Karar. "Distributed Secure Computing for Smart Mobile IoT Networks." Mobile Information Systems 2022 (April 15, 2022): 1–2. http://dx.doi.org/10.1155/2022/9864846.
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Tan, Yu-an, Xiaosong Zhang, Kashif Sharif, Chen Liang, Quanxin Zhang, and Yuanzhang Li. "Covert Timing Channels for IoT over Mobile Networks." IEEE Wireless Communications 25, no. 6 (2018): 38–44. http://dx.doi.org/10.1109/mwc.2017.1800062.
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Do, Trung-Anh, Sang-Woon Jeon, and Won-Yong Shin. "How to Cache in Mobile Hybrid IoT Networks?" IEEE Access 7 (2019): 27814–28. http://dx.doi.org/10.1109/access.2018.2882074.
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Guo, Hongzhi, Jiajia Liu, Jie Zhang, Wen Sun, and Nei Kato. "Mobile-Edge Computation Offloading for Ultradense IoT Networks." IEEE Internet of Things Journal 5, no. 6 (2018): 4977–88. http://dx.doi.org/10.1109/jiot.2018.2838584.
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Park, Byungjoo, Ankyu Hwang, and Haniph Latchman. "Design of Optimized Multimedia Data Streaming Management Using OMDSM over Mobile Networks." Mobile Information Systems 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/2867127.
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Mobility management is an essential challenge for supporting reliable multimedia data streaming over wireless and mobile networks in the Internet of Things (IoT) for location-based mobile marketing applications. The communications among mobile nodes for IoT need to have a seamless handover for delivering high quality multimedia services. The Internet Engineering Task Force (IETF) mobility management schemes are the proposals for handling the routing of IPv6 packets to mobile nodes that have moved away from their home network. However, the standard mobility management scheme cannot prevent packet losses due to longer handover latency. In this article, a new enhanced data streaming route optimization scheme is introduced that uses an optimized Transmission Control Protocol (TCP) realignment algorithm in order to prevent the packet disordering problem whenever the nodes in the IoT environment are communicating with each other. With the proposed scheme, data packets sequence realignment can be prevented, the packet traffic speed can be controlled, and the TCP performance can be improved. The experimental results show that managing the packet order in proposed new scheme remarkably increases the overall TCP performance over mobile networks within the IoT environment thus ensuring the high quality of service (QoS) for multimedia data streaming in location-based mobile marketing applications.
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Varga, Pal, Jozsef Peto, Attila Franko, et al. "5G support for Industrial IoT Applications— Challenges, Solutions, and Research gaps." Sensors 20, no. 3 (2020): 828. http://dx.doi.org/10.3390/s20030828.
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Industrial IoT has special communication requirements, including high reliability, low latency, flexibility, and security. These are instinctively provided by the 5G mobile technology, making it a successful candidate for supporting Industrial IoT (IIoT) scenarios. The aim of this paper is to identify current research challenges and solutions in relation to 5G-enabled Industrial IoT, based on the initial requirements and promises of both domains. The methodology of the paper follows the steps of surveying state-of-the art, comparing results to identify further challenges, and drawing conclusions as lessons learned for each research domain. These areas include IIoT applications and their requirements; mobile edge cloud; back-end performance tuning; network function virtualization; and security, blockchains for IIoT, Artificial Intelligence support for 5G, and private campus networks. Beside surveying the current challenges and solutions, the paper aims to provide meaningful comparisons for each of these areas (in relation to 5G-enabled IIoT) to draw conclusions on current research gaps.
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Thakre, Priyanka, and Prof Sonal Sharma. "A Survey on Security Mechanisms in D2D IoT Networks." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–11. http://dx.doi.org/10.55041/ijsrem29137.
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Due to the availability of handheld, mobile devices and the advent of cloud and bog data applications, the data traffic in the licensed bands has increased. This has led to the exploration of alternative avenues to de-load the conventional wireless networks. A new paradigm called device to device networks has evolved which is a category of mobile ad-hoc networks. Device-to- device (D2D) communication is expected to play a significant role in upcoming networks as it will reduce the burden from the cellular systems. This may make big data applications easier. However the D2D networks don’t use the security provided by cellular networks. Hence there is a chance of attacks. The major attack in D2D devices is the eavesdropping attack in which mobile hosts share the same wireless medium and broadcast signals over airwaves, which can be easily intercepted by receivers tuned to the proper frequency. Thus, the attacker can read exchanged messages and is able to inject fake messages to manipulate other users. This paper investigates the salient approaches of D2D networks in the context of security and access control and existing research methods. Keywords: Internet of Things (IoT), Network Security, D2D Security, Throughput, Error Rate.
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Alameri, I. A. "MANETS and Internet of Things: The Development of a Data Routing Algorithm." Engineering, Technology & Applied Science Research 8, no. 1 (2018): 2604–8. http://dx.doi.org/10.48084/etasr.1810.
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Internet of things (IoT), is an innovative technology which allows the connection of physical things with the digital world through the use of heterogeneous networks and communication technologies. IoT in smart environments interacts with wireless sensor network (WSN) and mobile ad‐hoc network (MANET), becoming even more attractive and economically successful. Interaction between wireless sensor and mobile ad‐hoc networks with the internet of things allows the creation of a new MANET‐IoT systems and IT‐based networks. Such systems give the user greater mobility and reduce costs. At the same time new challenging issues are opened in networking aspects. In this work, author proposed a routing solution for the IoT system using a combination of MANET protocols and WSN routing principles. The presented results of solution's investigation provide an effective approach to efficient energy consumption in the global MANET‐IoT system. That is a step forward to a reliable provision of services over global future internet infrastructure.
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Alameri, I. A. "MANETS and Internet of Things: The Development of a Data Routing Algorithm." Engineering, Technology & Applied Science Research 8, no. 1 (2018): 2604–8. https://doi.org/10.5281/zenodo.1207439.
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Internet of things (IoT), is an innovative technology which allows the connection of physical things with the digital world through the use of heterogeneous networks and communication technologies. IoT in smart environments interacts with wireless sensor network (WSN) and mobile ad‐hoc network (MANET), becoming even more attractive and economically successful. Interaction between wireless sensor and mobile ad‐hoc networks with the internet of things allows the creation of a new MANET‐IoT systems and IT‐based networks. Such systems give the user greater mobility and reduce costs. At the same time new challenging issues are opened in networking aspects. In this work, author proposed a routing solution for the IoT system using a combination of MANET protocols and WSN routing principles. The presented results of solution's investigation provide an effective approach to efficient energy consumption in the global MANET‐IoT system. That is a step forward to a reliable provision of services over global future internet infrastructure.
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Divya, K., and B. Srinivasan. "A Trust-Based Predictive Model for Mobile Ad Hoc Networks." International Journal on AdHoc Networking Systems 11, no. 03 (2021): 13–23. http://dx.doi.org/10.5121/ijans.2021.11302.
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The Internet of things (IoT) is a heterogeneous network of different types of wireless networks such as wireless sensor networks (WSNs), ZigBee, Wi-Fi, mobile ad hoc networks (MANETs), and RFID. To make IoT a reality for smart environment, more attractive to end users, and economically successful, it must be compatible with WSNs and MANETs. In light of this, the present paper discusses a novel quantitative trust model for an IoT-MANET. The proposed trust model combines both direct and indirect trust opinion in order to calculate the final trust value for a node. Further, a routing protocol has been designed to ensure the secure and reliable end-to-end delivery of packets by only considering trustworthy nodes in the path. Simulation results show that our proposed trust model outperforms similar existing trust models.
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Al mojamed, Mohammad. "On the Use of LoRaWAN for Mobile Internet of Things: The Impact of Mobility." Applied System Innovation 5, no. 1 (2021): 5. http://dx.doi.org/10.3390/asi5010005.
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A long-range wide-area network (LoRaWAN) targets both mobile and static Internet of Things (IoT) applications; it is suited to IoT applications, which require a large coverage area while consuming less power at a low data rate; it provides a solution for transferring data between IoT devices with a minimum cost in terms of power, at the expense of higher latency. LoRaWAN was designed for static low-power long-range networks. However, several IoT solution applications involve the use of mobility. Therefore, this study investigates the usage of LoRaWAN in the field of mobile Internet of Things applications such as bike rentals, fleet monitoring, and wildlife and animal tracking applications. Using the OMNeT++ simulator, two different well-known mobility models are used to investigate the influence of mobility on the performance of mobile LoRaWAN. The results show that intense LoRaWAN networks can operate under a high velocity and varying traffic load. It can be observed that the random waypoint model combination yields a better performance, but at the cost of higher collisions and energy consumption. As a consequence, the results suggest the reconsideration of mobile IoT solutions over LoRaWAN.
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Fan, Kai, Chen Zhang, Kan Yang, Hui Li, and Yintang Yang. "Lightweight NFC Protocol for Privacy Protection in Mobile IoT." Applied Sciences 8, no. 12 (2018): 2506. http://dx.doi.org/10.3390/app8122506.
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The Internet of Things (IoT) aims to achieve the interconnection of all devices in our lives. Due to the complex network environment, the IoT with mobile devices often faces many security problems, such as privacy leakages and identity forgery attacks. As a developing technology in mobile IoT, near field communication (NFC) is widely used in electronic payments and identity authentications. The current NFC studies mainly focus on payment technology, but there are a few studies on privacy protection and the lightweight requirements in the mobile IoT authentication protocol. We focus on the lightweight privacy protection authentication technology in mobile IoT. In the paper, we summarize the clustering model in mobile IoT networks and propose a lightweight authentication protocol. A security analysis shows that the protocol can resist many security threats, such as privacy leakages, identity forgeries, and replay attacks. The simulation also shows that the protocol is lightweight, with the utilization of look-up-tables (LUTs) and registers in our protocol being less than 0.5%. Our work can provide a secure and lightweight mobile authentication serve in the NFC-based mobile IoT network such as smart home and office attendance.
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Rendy, Munadi, Rakhman Arief, and Perdana Doan. "Smart Garage Implementation and Design Using Whatsapp Communication Media." TELKOMNIKA Telecommunication, Computing, Electronics and Control 16, no. 3 (2018): 1107–13. https://doi.org/10.12928/TELKOMNIKA.v16i3.8063.
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WhatsApp is a social networking app that serves as a communication medium. According to the Online Audience Measurement Standards named comScore, in 2017, WhatsApp application users in Indonesia amounted to 35.8 million people. As the most popular mobile application with the most users in the country, in this research the authors chose Whatsapp as a communication medium that will be integrated into one application of Internet of Things (IoT), that is Smart Garage. Smart Garage is a combination of information technology and computing technology that is applied to a house by relying on efficiency and device automation. The results of this research shows that it is better to use mobile data networks than using the wireless networks. The maximum delay when using mobile data is 7.5 s and 7.7 s when using wireless networks. The research using WhatsApp application still rare especially in the field of IoT.
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Researcher. "CYBER SEC IOT MOBILE-DEEP SECURE: A UNIFIED CYBERSECURITY FRAMEWORK UTILIZING DEEP LEARNING FOR ENHANCED PROTECTION OF MOBILE AND IOT NETWORKS." International Journal of Advanced Research in Engineering and Technology (IJARET) 15, no. 5 (2024): 193–211. https://doi.org/10.5281/zenodo.13980306.
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The growing interconnectivity between mobile devices and Internet of Things (IoT) networks has exposed significant cybersecurity vulnerabilities, necessitating a more advanced and unified approach to threat management. CyberSecIoTMobile-DeepSecure is a comprehensive security framework designed to address these challenges by combining deep learning techniques, including convolutional neural networks (CNNs) and long short-term memory (LSTM) models, for enhanced threat detection and response across both mobile and IoT ecosystems. The framework preprocesses network traffic data to remove noise and standardize inputs, improving the accuracy of the deep learning models. By leveraging behavioral analytics and real-time anomaly detection, CyberSecIoTMobile-DeepSecure achieves a 96.8% accuracy in identifying sophisticated threats, such as zero-day exploits and network intrusions. The intelligent response mechanism dynamically adjusts security measures based on the threat's severity, helping to minimize system downtime and enhance overall resilience. Experimental results show that CyberSecIoTMobile-DeepSecure reduces detection latency by 28% and lowers packet loss during attacks by 51% compared to traditional machine learning approaches, ensuring rapid and precise defense. Additionally, the framework demonstrates a 36% decrease in energy consumption, making it suitable for resource-constrained IoT devices. By offering seamless integration, adaptive threat management, and robust protection, CyberSecIoTMobile-DeepSecure provides a scalable solution for securing interconnected mobile and IoT networks in diverse and challenging environments.
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Farooq, Umer, Muhammad Asim, Noshina Tariq, Thar Baker, and Ali Ismail Awad. "Multi-Mobile Agent Trust Framework for Mitigating Internal Attacks and Augmenting RPL Security." Sensors 22, no. 12 (2022): 4539. http://dx.doi.org/10.3390/s22124539.
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Recently, the Internet of Things (IoT) has emerged as an important way to connect diverse physical devices to the internet. The IoT paves the way for a slew of new cutting-edge applications. Despite the prospective benefits and many security solutions offered in the literature, the security of IoT networks remains a critical concern, considering the massive amount of data generated and transmitted. The resource-constrained, mobile, and heterogeneous nature of the IoT makes it increasingly challenging to preserve security in routing protocols, such as the routing protocol for low-power and lossy networks (RPL). RPL does not offer good protection against routing attacks, such as rank, Sybil, and sinkhole attacks. Therefore, to augment the security of RPL, this article proposes the energy-efficient multi-mobile agent-based trust framework for RPL (MMTM-RPL). The goal of MMTM-RPL is to mitigate internal attacks in IoT-based wireless sensor networks using fog layer capabilities. MMTM-RPL mitigates rank, Sybil, and sinkhole attacks while minimizing energy and message overheads by 25–30% due to the use of mobile agents and dynamic itineraries. MMTM-RPL enhances the security of RPL and improves network lifetime (by 25–30% or more) and the detection rate (by 10% or more) compared to state-of-the-art approaches, namely, DCTM-RPL, RBAM-IoT, RPL-MRC, and DSH-RPL.
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Kassimov, Abdurazak, Muhabbat Khizirova, Muratbek Yermekbaev, Daniyar Abdikhan, and Sunggat Marxuly. "Mobile application for remote monitoring and control of lorawan networks." International Journal of Innovative Research and Scientific Studies 8, no. 4 (2025): 785–98. https://doi.org/10.53894/ijirss.v8i4.7948.
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The proliferation of Internet of Things (IoT) technologies has led to increased adoption of Low Power Wide Area Networks (LPWAN), with LoRaWAN emerging as a prominent protocol for long-range, low-power communication. However, the effective management of LoRaWAN networks presents challenges in terms of monitoring, control, and optimization. This paper introduces a comprehensive mobile application developed specifically for remote monitoring and control of LoRaWAN systems. The application integrates secure authentication mechanisms, dashboard visualization, device management, geolocation mapping, analytics, alert management, and customizable settings. Our methodology combines cross-platform development techniques with optimization for resource-constrained environments typical of IoT scenarios. Results demonstrate that the mobile application significantly improves operational efficiency by enabling real-time monitoring, reducing response times to critical events, and providing actionable insights through data visualization and analytics. The implementation allows for secure device registration via both Over-The-Air Activation (OTAA) and Activation By Personalization (ABP) methods, with geolocation capabilities for spatial awareness of network nodes. The conclusions highlight how mobile-based management solutions can democratize IoT network administration while maintaining robust security protocols and enhancing user experience in industrial IoT deployments.
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Abhishek, Singh, Gupta Gargi, Khan Hera, and Kumar Maurya Arun. "Study of Future Prospects of the Internet of Things." Advancement and Research in Instrumentation Engineering 6, no. 3 (2023): 1–17. https://doi.org/10.5281/zenodo.8113021.
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<em>As the Internet of Things (rapidly develops as the next stage of the Internet's growth, it is essential to understand the different possible areas for IoT applications as well as the research difficulties that go along with them. IoT is anticipated to permeate almost every part of everyday life, from smart cities to health care, smart agriculture, logistics, and retail, to even smart living and smart ecosystems. A new paradigm known as the Internet of Things (IoT) has transformed the old way of life into a high-tech one. These changes brought about by IoT include the development of smart homes, communities, and industries as well as the reduction of pollution and energy consumption. To advance technology through IoT, several important research studies and investigations have been conducted. The development of mobile computers, smartphones, sensors, and sensor networks in conjunction with next-generation mobile networks has now created enormous opportunity for researchers and developers of different Internet of Things systems and applications (IOT).</em>
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Ateya, Abdelhamied A., Abeer D. Algarni, Monia Hamdi, Andrey Koucheryavy, and Naglaa F. Soliman. "Enabling Heterogeneous IoT Networks over 5G Networks with Ultra-Dense Deployment—Using MEC/SDN." Electronics 10, no. 8 (2021): 910. http://dx.doi.org/10.3390/electronics10080910.
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The Internet of things (IoT) is the third evolution of the traditional Internet that enables interaction and communication among machines. Many IoT platforms and networks have been developed, and recently, market sectors have started to develop specific IoT applications and services. Integrating heterogeneous IoT networks with the existing ones, mainly with the cellular networks, is a great demand. IoT represents one of the main use cases of the fifth-generation (5G) cellular system as announced by the 3rd Generation Partnership Project (3GPP) and the International Telecommunication Union (ITU). Integrating IoT networks with 5G networks face many challenges related to dense deployment and a massive number of expected connected devices. Thus, IoT network availability and scalability are the main requirements that should be achieved. To this end, this work provides a framework for integrating heterogeneous IoT networks with the 5G networks. The proposed system considers dense deployment and system scalability and availability requirements as announced by ITU and 3GPP. Our proposed structure deploys three main communication paradigms; mobile edge computing (MEC), device-to-device communications (D2D), and software-defined networking (SDN). Our proposed system is evaluated over a reliable environment for various deployment scenarios, and the results validate the proposed structure. The proposed IoT/5G reduces the percentage of blocked tasks by an average of 30% than other traditional IoT networks. This increases the overall system availability and scalability since IoT networks can have more devices and tasks than existing IoT networks. Furthermore, our proposed structure reduces the overall consumed energy by an average of 20% than existing IoT networks, which is an effective metric for IoT networks.
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Li, Jing, Weifa Liang, Zichuan Xu, Xiaohua Jia, and Wanlei Zhou. "Service Provisioning for Multi-source IoT Applications in Mobile Edge Computing." ACM Transactions on Sensor Networks 18, no. 2 (2022): 1–25. http://dx.doi.org/10.1145/3484200.
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We are embracing an era of Internet of Things (IoT). The latency brought by unstable wireless networks caused by limited resources of IoT devices seriously impacts the quality of services of users, particularly the service delay they experienced. Mobile Edge Computing (MEC) technology provides promising solutions to delay-sensitive IoT applications, where cloudlets (edge servers) are co-located with wireless access points in the proximity of IoT devices. The service response latency for IoT applications can be significantly shortened due to that their data processing can be performed in a local MEC network. Meanwhile, most IoT applications usually impose Service Function Chain (SFC) enforcement on their data transmission, where each data packet from its source gateway of an IoT device to the destination (a cloudlet) of the IoT application must pass through each Virtual Network Function (VNF) in the SFC in an MEC network. However, little attention has been paid on such a service provisioning of multi-source IoT applications in an MEC network with SFC enforcement. In this article, we study service provisioning in an MEC network for multi-source IoT applications with SFC requirements and aiming at minimizing the cost of such service provisioning, where each IoT application has multiple data streams from different sources to be uploaded to a location (cloudlet) in the MEC network for aggregation, processing, and storage purposes. To this end, we first formulate two novel optimization problems: the cost minimization problem of service provisioning for a single multi-source IoT application, and the service provisioning problem for a set of multi-source IoT applications, respectively, and show that both problems are NP-hard. Second, we propose a service provisioning framework in the MEC network for multi-source IoT applications that consists of uploading stream data from multiple sources of the IoT application to the MEC network, data stream aggregation and routing through the VNF instance placement and sharing, and workload balancing among cloudlets. Third, we devise an efficient algorithm for the cost minimization problem built upon the proposed service provisioning framework, and further extend the solution for the service provisioning problem of a set of multi-source IoT applications. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms are promising.
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Xu, Zhanyang, Renhao Gu, Tao Huang, et al. "An IoT-Oriented Offloading Method with Privacy Preservation for Cloudlet-Enabled Wireless Metropolitan Area Networks." Sensors 18, no. 9 (2018): 3030. http://dx.doi.org/10.3390/s18093030.
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With the development of the Internet of Things (IoT) technology, a vast amount of the IoT data is generated by mobile applications from mobile devices. Cloudlets provide a paradigm that allows the mobile applications and the generated IoT data to be offloaded from the mobile devices to the cloudlets for processing and storage through the access points (APs) in the Wireless Metropolitan Area Networks (WMANs). Since most of the IoT data is relevant to personal privacy, it is necessary to pay attention to data transmission security. However, it is still a challenge to realize the goal of optimizing the data transmission time, energy consumption and resource utilization with the privacy preservation considered for the cloudlet-enabled WMAN. In this paper, an IoT-oriented offloading method, named IOM, with privacy preservation is proposed to solve this problem. The task-offloading strategy with privacy preservation in WMANs is analyzed and modeled as a constrained multi-objective optimization problem. Then, the Dijkstra algorithm is employed to evaluate the shortest path between APs in WMANs, and the nondominated sorting differential evolution algorithm (NSDE) is adopted to optimize the proposed multi-objective problem. Finally, the experimental results demonstrate that the proposed method is both effective and efficient.
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Min, Wei, Abdukodir Khakimov, Abdelhamied A. Ateya, et al. "Dynamic Offloading in Flying Fog Computing: Optimizing IoT Network Performance with Mobile Drones." Drones 7, no. 10 (2023): 622. http://dx.doi.org/10.3390/drones7100622.
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The rapid growth of Internet of Things (IoT) devices and the increasing need for low-latency and high-throughput applications have led to the introduction of distributed edge computing. Flying fog computing is a promising solution that can be used to assist IoT networks. It leverages drones with computing capabilities (e.g., fog nodes), enabling data processing and storage closer to the network edge. This introduces various benefits to IoT networks compared to deploying traditional static edge computing paradigms, including coverage improvement, enabling dense deployment, and increasing availability and reliability. However, drones’ dynamic and mobile nature poses significant challenges in task offloading decisions to optimize resource utilization and overall network performance. This work presents a novel offloading model based on dynamic programming explicitly tailored for flying fog-based IoT networks. The proposed algorithm aims to intelligently determine the optimal task assignment strategy by considering the mobility patterns of drones, the computational capacity of fog nodes, the communication constraints of the IoT devices, and the latency requirements. Extensive simulations and experiments were conducted to test the proposed approach. Our results revealed significant improvements in latency, availability, and the cost of resources.
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Brooks, Tyson. "Authenticating Devices in Fog-mobile Edge Computing Environments through a Wireless Grid Resource Sharing Protocol." International Journal of UbiComp 13, no. 2 (2022): 1–17. http://dx.doi.org/10.5121/iju.2022.13201.
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The rapid growth of the Internet of Things (IoT), cloud computing, Fog computing, mobile edge computing and wireless grids has resulted in the widespread deployment of relatively immature technology. These technologies, which will primarily use 5G wireless communication networks, are becoming popular because they can be deployed quickly with little infrastructure and lends themselves to environments utilizing numerous internet connected devices (ICD). There are, however, many significant challenges faced by security designers, engineers and implementers of these networks in ensuring that the level of security afforded is appropriate. Because of the threat of exploitation, these networks have to be protected by a robust security architecture due to these technologies being plagued with security problems. The authentication of smart ICDs to IoT networks is a critical mechanism for achieving security on these new information system platforms. This article identifies an authentication process required for these ICDs, which will need to prove their identity to authenticate to an IoT fog-mobile edge computing (FMEC) cloud network through a wireless grid authentication process. The purpose of this article is to begin to hypothesize a generic authentication methodology for these FMEC clouds uses in an IoT architecture. The proposed methodology, called wg-IoT, must include the integration of Fog computing, wireless grids and mobile edge computing clouds to create this new IoT architecture. An authentication process developed from the resource sharing protocol (RSP) from a wireless grid is first developed and proposed for the authentication of ICDs. The wireless grid core components must be embedded in IoT devices or sensors depending on their capability to handle five primary functions: management of identification [ID] and presence, permissions management, data transferability, application-programming interface [API] and security.
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Tyson, Brooks. "AUTHENTICATING DEVICES IN FOG-MOBILE EDGE COMPUTING ENVIRONMENTS THROUGH A WIRELESS GRID RESOURCE SHARING PROTOCOL." International Journal of Ubiquitous Computing (IJU) 13, no. 1/2 (2022): 17. https://doi.org/10.5281/zenodo.6531667.
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The rapid growth of the Internet of Things (IoT), cloud computing, Fog computing, mobile edge computing and wireless grids has resulted in the widespread deployment of relatively immature technology. These technologies, which will primarily use 5G wireless communication networks, are becoming popular because they can be deployed quickly with little infrastructure and lends themselves to environments utilizing numerous internet connected devices (ICD). There are, however, many significant challenges faced by security designers, engineers and implementers of these networks in ensuring that the level of security afforded is appropriate. Because of the threat of exploitation, these networks have to be protected by a robust security architecture due to these technologies being plagued with security problems. The authentication of smart ICDs to IoT networks is a critical mechanism for achieving security on these new information system platforms. This article identifies an authentication process required for these ICDs, which will need to prove their identity to authenticate to an IoT fog-mobile edge computing (FMEC) cloud network through a wireless grid authentication process. The purpose of this article is to begin to hypothesize a generic authentication methodology for these FMEC clouds uses in an IoT architecture. The proposed methodology, called wg-IoT, must include the integration of Fog computing, wireless grids and mobile edge computing clouds to create this new IoT architecture. An authentication process developed from the resource sharing protocol (RSP) from a wireless grid is first developed and proposed for the authentication of ICDs. The wireless grid core components must be embedded in IoT devices or sensors depending on their capability to handle five primary functions: management of identification [ID] and presence, permissions management, data transferability, application-programming interface [API] and security.
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Slavkovski, Hristijan, and Toni Janevski. "COMPARISON OF LoRaWAN AND MOBILE IOT NETWORKS AND SERVICES." Journal of Electrical Engineering and Information Technologies 9, no. 2 (2024): 100–107. https://doi.org/10.51466/jeeit2492224100s.
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Sharmeen, Shaila, Shamsul Huda, Jemal H. Abawajy, Walaa Nagy Ismail, and Mohammad Mehedi Hassan. "Malware Threats and Detection for Industrial Mobile-IoT Networks." IEEE Access 6 (2018): 15941–57. http://dx.doi.org/10.1109/access.2018.2815660.
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Yamada, Yoshinobu, Ryoichi Shinkuma, Takanori Iwai, Takeo Onishi, Takahiro Nobukiyo, and Kozo Satoda. "Temporal traffic smoothing for IoT traffic in mobile networks." Computer Networks 146 (December 2018): 115–24. http://dx.doi.org/10.1016/j.comnet.2018.08.020.
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Li, Kaixin, Jiajie Xu, Hua Xing, Ying Chen, and Jiwei Huang. "Dynamic Task Offloading for NOMA-Enabled Mobile Edge Computing with Heterogeneous Networks." Security and Communication Networks 2022 (September 20, 2022): 1–13. http://dx.doi.org/10.1155/2022/7258236.
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With the rapid development of the Internet of Things (IoT), more and more computation-intensive tasks are generated by IoT devices. Due to their own limitations, IoT devices cannot process all tasks locally, and some tasks need to be offloaded to edge servers for processing. In addition, nonorthogonal multiple access (NOMA) technology allows multiple IoT devices to share the same frequency resource. IoT devices can use NOMA technology to transmit data to increase the data transmission rate. In this article, we study the problem of NOMA-enabled dynamic task offloading in heterogeneous networks. We formulate a stochastic optimization problem to minimize system energy consumption. Using stochastic optimization techniques, we transform this problem into a deterministic optimization problem and decompose it into five sub-problems to solve. At the same time, we propose a NOMA-enabled dynamic task offloading (NDTO) algorithm. Then, we mathematically analyze the performance of the NDTO algorithm. We conduct a series of parameter analysis experiments and comparative experiments, and the results verify the performance of the NDTO algorithm.
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Somantri, Supriatna, Hardi Herdiana, Ujang Mulyana, and Anggy Pradifta Junfithrana. "SMART AGRICULTURE BASED IOT AND MOBILE APPS." INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) 3, no. 2 (2020): 86–96. http://dx.doi.org/10.52005/ijeat.v3i2.62.
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Agriculture is the main occupation in our country for many centuries. But now because of the migration of people from rural to urban areas there are barriers to agriculture. So to solve this problem we are using smart farming techniques using IOT. Smart farming is a developing concept, because the IOT Sensor is able to provide information about the agricultural sector and then act on user input. To develop this Intelligent Agricultural System, it uses the advantages of the latest technology such as Arduino, IOT and Wireless Sensor Networks. The paper aims to make use of the emerging technology namely IOT and the use of intelligent agricultural automation. Monitoring of environmental conditions is the main factor for increasing efficient crop yields. This feature includes the development of a system that can monitor temperature, humidity and is programmed via an android application.
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Elazhary, Hanan. "Internet of Things (IoT), mobile cloud, cloudlet, mobile IoT, IoT cloud, fog, mobile edge, and edge emerging computing paradigms: Disambiguation and research directions." Journal of Network and Computer Applications 128 (February 2019): 105–40. http://dx.doi.org/10.1016/j.jnca.2018.10.021.
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Zikria, Yousaf, Sung Kim, Muhammad Afzal, Haoxiang Wang, and Mubashir Rehmani. "5G Mobile Services and Scenarios: Challenges and Solutions." Sustainability 10, no. 10 (2018): 3626. http://dx.doi.org/10.3390/su10103626.
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The Fifth generation (5G) network is projected to support large amount of data traffic and massive number of wireless connections. Different data traffic has different Quality of Service (QoS) requirements. 5G mobile network aims to address the limitations of previous cellular standards (i.e., 2G/3G/4G) and be a prospective key enabler for future Internet of Things (IoT). 5G networks support a wide range of applications such as smart home, autonomous driving, drone operations, health and mission critical applications, Industrial IoT (IIoT), and entertainment and multimedia. Based on end users’ experience, several 5G services are categorized into immersive 5G services, intelligent 5G services, omnipresent 5G services, autonomous 5G services, and public 5G services. In this paper, we present a brief overview of 5G technical scenarios. We then provide a brief overview of accepted papers in our Special Issue on 5G mobile services and scenarios. Finally, we conclude this paper.
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El Mahjoubi, Ahmed, Tomader Mazri, and Nabil Hmina. "NB-IoT and eMTC: Engineering results towards 5G/IoT Mobile Technologies." International Journal of Interactive Mobile Technologies (iJIM) 13, no. 01 (2019): 115. http://dx.doi.org/10.3991/ijim.v13i01.9728.
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5G RF technology is an essential part of the wireless mobile technology. Technically, 5G is predicted to empower people-thing and thing-thing interconnections by combining wireless technologies and networks. Our university has been actively support research on 4G/5G/IoT, in which the NB-IoT, eMTC and Massive Carrier Aggregation new features challenge are of big interest. New 5G trials put forward a lot of prerequisites for new RF interface in terms of radio bandwidth, power issues, as well as the huge number of connections for IoT capacity management and optimization. Based on Morocco’s current situation, this paper first discusses the 5G technologies; In addition, we will discuss IoT SoftRadio application support, and NB-IoT master plan recap. At last, based on the current plan of 5G RF KPIs management according to first Morocco 5G trail Results and Deployment plans.
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Khan, Dr Ahmad Khan. "Efficient Resource Management for IoT Devices in Mobile Networks Using Packet Collection and Forwarding in Transportation Systems." Asian Bulletin of Big Data Management 5, no. 1 (2025): 43–57. https://doi.org/10.62019/abbdm.v5i1.294.
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The Internet of Things (IoT) and Machine Type Communication (MTC), also known as Machine-to-Machine (M2M) communication, have led to significant advancements in various industries, resulting in a notable increase in IoT devices in recent years. A range of communication technologies, including Low Power Wide Area Networks (LPWAN), Narrow Band IoT (NB-IoT), Long-Term Evolution (LTE), LTE-Advanced (LTE-A), and emerging 5G & 6G cellular networks, have been deployed to connect IoT sensors and devices. LTE and LTE-A are particularly effective for IoT device interoperability due to their widespread availability. However, the current cellular mobile networks are primarily designed to cater to broadband services and human-based communication (H2H), which poses challenges for handling the narrowband traffic generated by IoT devices, especially when millions of devices communicate within a single cell, such as during transportation. In transportation systems, where containers carrying various goods require continuous data transmission, this massive volume of IoT traffic can overwhelm network resources, leading to inefficient spectrum usage. This paper proposes an innovative solution to address these challenges by introducing a resource management framework that utilizes packet collection and forwarding techniques. Specifically, the system employs an intermediary node, termed the Packet Collection and Forwarding (PCF) node, which temporarily stores small packets in a buffer. Once the buffer reaches capacity, these tiny packets are aggregated into a larger packet and forwarded to the recipient, reducing network congestion and enhancing resource allocation efficiency. Additionally, the system incorporates strategies to minimize delays in the micro-packet collection process, ensuring minimal impact on communication latency. By leveraging this approach, the proposed system optimizes network performance, reduces energy consumption, and supports scalable, sustainable IoT solutions in mobile networks, particularly in transportation systems. Simulation results demonstrate significant improvements in resource management, throughput, and overall network efficiency, contributing to the development of robust IoT infrastructures for dynamic environments.
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Choudhury, Hiten. "Computational Overhead of a Novel Scheme for Identity Confidentiality on IoT Devices in 5G Mobile Networks." Spectrum: Science and Technology 7, no. 1 (2020): 23–29. http://dx.doi.org/10.54290/spect/2020.v7.1.0003.
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Mobile networks are becoming a preferred choice for the Internet of Things (IoT), due to its flexibility, broad coverage, increasing bandwidth, low latency and low subscription cost. However, a long-standing security issue in any mobile network across the various generations is identity confidentiality. In a recent technical specification standardised by 3rd Generation Partnership Project (3GPP) for 5G mobile network, a novel scheme called the Elliptic Curve Integrated Encryption Scheme (ECIES) is adopted to tackle the issue of identity confidentiality. While this mechanism seems to provide a reasonable solution for modern resource affluent smart phones, it’s suitability for resource constrained IoT devices needs to be analysed. In this paper, we study the computational overhead of the ECIES on IoT devices.
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Lavanya K. "A Review on Machine Learning and Deep Learning Techniques for Medical Internet of Things (m-IoT)." Communications on Applied Nonlinear Analysis 32, no. 2s (2024): 271–83. https://doi.org/10.52783/cana.v32.2384.
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The mobile health care over Internet of Things (IoT) offers flexibility and fast clinical diagnosis irrespective of distance and viewing displays. The delivery, management, and oversight of medical services have undergone a radical transformation as a result of the integration of Machine Learning (ML) and Deep Learning (DL) techniques in the mobile healthcare domain. To achieve better Quality of Service (QoS), the present networks needs more lime light of research in terms of streaming the medical videos without sacrificing the medical quality of experience (mQoE).Researchers have addressed various issues and proposed numerous solutions in terms of machine learning for IoT in mobile healthcare. The article provides a thorough analysis of contemporary machine learning (ML)/Deep Learning (DL) concepts, with a focus on mobile healthcare domain. It mainly focus on recent developments in health care domain and also opens research issues that need to be addressed in the future A wide range of topics, including the diagnosis and classification of diseases, customised therapy suggestions, remote patient surveillance and their health behaviour analysis have been covered. A comprehensive review has been conducted on IoT in healthcare, Big medical data in IoT, ML and DL models and ML challenges in IoT healthcare. This survey of IoT based medical data transmission is focused on recognising an accurate prediction model. The simulation results and comparison analysis of various ML/DL algorithms have been presented. The medical image classification have been evaluated based on several metrics including prediction accuracy, specificity and sensitivity. These metrics have been compared and tabulated for various learning algorithms like Artificial Neural Networks (ANN),Naïve Bayes Classifier (NB), Reinforcement Learning (RF),Support Vector machine (SVM),Convolutional Neural Networks (CNN). Finally, a frame work for a secured multipath medical video transmission using the hybrid version of the above discussed algorithms has also been suggested.
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Saharov, D., and D. Kozlov. "Detecting Abnormal Behavior of an IoT Device in the Network Based on a Traffic Model." Telecom IT 7, no. 3 (2019): 50–55. http://dx.doi.org/10.31854/2307-1303-2019-7-3-50-55.
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The article deals with the СoAP Protocol that regulates the transmission and reception of information traf-fic by terminal devices in IoT networks. The article describes a model for detecting abnormal traffic in 5G/IoT networks using machine learning algorithms, as well as the main methods for solving this prob-lem. The relevance of the article is due to the wide spread of the Internet of things and the upcoming update of mobile networks to the 5g generation.
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Hkiri, Amal, Sami Alqurashi, Omar Ben Bahri, Mouna Karmani, Hamzah Faraj, and Mohsen Machhout. "Performance Evaluation of Mobile RPL-Based IoT Networks under Hello Flood Attack." Electronics 13, no. 11 (2024): 2226. http://dx.doi.org/10.3390/electronics13112226.
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The RPL protocol is essential for efficient communication within the Internet of Things (IoT) ecosystem, yet it remains vulnerable to various attacks, particularly in dense and mobile environments where it shows certain limitations and susceptibilities. This paper presents a comprehensive simulation-based analysis of the RPL protocol’s vulnerability to the Hello Flood attack in mobile environments. Using four different group mobility models—the Column Mobility Model (CMM), Reference Point Group Mobility Model (RPGM), Nomadic Community Mobility Model (NCM), and Pursue Mobility Model (PMM)—within the Cooja simulator, this study uniquely investigates the Hello Flood attack in mobile settings, an area previously overlooked. Our systematic evaluation focuses on critical performance metrics, including the Packet Delivery Ratio (PDR), End-to-End Delay (E2ED), throughput, Expected Transmission Count (ETX), and Average Power Consumption (APC). The findings reveal several key insights: PDR decreases significantly, indicating increased packet loss or delivery failures; ETX values rise, necessitating more packet retransmissions and routing hops; E2ED increases, introducing delays in routing decisions and data transmission times; throughput declines as the attack disrupts data flow; and APC escalates due to higher energy usage on packet transmissions, especially over extended paths. These results underscore the urgent need for robust security measures to protect RPL-based IoT networks in mobile environments. Furthermore, our work emphasizes the exacerbated impact of the attack in mobile scenarios, highlighting the evolving security requirements of IoT networks.