A Game-Theoretic Approach for Cost-Effective Multicast Routing in the Internet of Things

Kumar, Sumit; Goswami, Antriksh; Gupta, Ruchir; Singh, Satya P.; Lay-Ekuakille, A.

doi:10.1109/jiot.2022.3164028

Cited by 14 publications

(3 citation statements)

References 35 publications

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“…Also, clusters of trees have been built using different methodologies [11][12][13]. Several approaches use game theory to construct a spanning tree that requires minimal transmission power [14,15]. Finally, some authors have attempted to minimize the path lengths from the source to all other nodes to minimize energy consumption [16,17].…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient Decentralized Broadcasting in Wireless Multi-Hop Networks

Sterz,

Klose,

Sommer

et al. 2023

Sensors

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Several areas of wireless networking, such as wireless sensor networks or the Internet of Things, require application data to be distributed to multiple receivers in an area beyond the transmission range of a single node. This can be achieved by using the wireless medium’s broadcast property when retransmitting data. Due to the energy constraints of typical wireless devices, a broadcasting scheme that consumes as little energy as possible is highly desirable. In this article, we present a novel multi-hop data dissemination protocol called BTP. It uses a game-theoretical model to construct a spanning tree in a decentralized manner to minimize the total energy consumption of a network by minimizing the transmission power of each node. Although BTP is based on a game-theoretical model, it neither requires information exchange between distant nodes nor time synchronization during its operation, and it inhibits graph cycles effectively. The protocol is evaluated in Matlab and NS-3 simulations and through real-world implementation on a testbed of 75 Raspberry Pis. The evaluation conducted shows that our proposed protocol can achieve a total energy reduction of up to 90% compared to a simple broadcast protocol in real-world experiments.

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Section: Related Workmentioning

confidence: 99%

Energy-Efficient Decentralized Broadcasting in Wireless Multi-Hop Networks

Sterz,

Klose,

Sommer

et al. 2023

Sensors

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“…A multi-objective ant colony optimisation-based secure routing scheme is proposed to enable devices or servers to jump out easily from the local optima with the minimum possible energy consumption of nodes. Additionally, this algorithm has the built-in capacity to converge more rapidly than other approaches [12].…”

Section: Literature Reviewmentioning

confidence: 99%

Machine Learning-Enabled Communication Approach for the Internet of Medical Things

Khan,

Ghani,

Allaoua Chelloug

et al. 2023

Computers, Materials &Amp; Continua

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The Internet of Medical Things (IoMT) is mainly concerned with the efficient utilisation of wearable devices in the healthcare domain to manage various processes automatically, whereas machine learning approaches enable these smart systems to make informed decisions. Generally, broadcasting is used for the transmission of frames, whereas congestion, energy efficiency, and excessive load are among the common issues associated with existing approaches. In this paper, a machine learning-enabled shortest path identification scheme is presented to ensure reliable transmission of frames, especially with the minimum possible communication overheads in the IoMT network. For this purpose, the proposed scheme utilises a well-known technique, i.e., Kruskal's algorithm, to find an optimal path from source to destination wearable devices. Additionally, other evaluation metrics are used to find a reliable and shortest possible communication path between the two interested parties. Apart from that, every device is bound to hold a supplementary path, preferably a second optimised path, for situations where the current communication path is no longer available, either due to device failure or heavy traffic. Furthermore, the machine learning approach helps enable these devices to update their routing tables simultaneously, and an optimal path could be replaced if a better one is available. The proposed mechanism has been tested using a smart environment developed for the healthcare domain using IoMT networks. Simulation results show that the proposed machine learning-oriented approach performs better than existing approaches where the proposed scheme has achieved the minimum possible ratios, i.e., 17% and 23%, in terms of end to end delay and packet losses, respectively. Moreover, the proposed scheme has achieved an approximately 21% improvement in the average throughput compared to the existing schemes.

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“…Meanwhile, our T-S fuzzy trust model can obtain a more accurate trust evaluation value under the premise of ensuring the required stability of IoTs. Referring to [ 3 , 4 , 5 ], we design a repeated game model to perfect the energy-efficient privacy-preserving scheme, where the subgame Nash equilibrium of the repeated game model can balance the data security and network resource consumption [ 6 ]. The contributions of this research are given as follows: Firstly, we propose a novel privacy-preserving scheme based on T-S fuzzy trust theory to mitigate the pollution attacks, in which the security is proved according to the hardness of the discrete logarithm.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy-Based Privacy-Preserving Scheme of Low Consumption and High Effectiveness for IoTs: A Repeated Game Model

Cao

Zhu

2022

Sensors

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In the Internet of things (IoTs), data transmission via network coding is highly vulnerable to intra-generation and inter-generation pollution attacks. To mitigate such attacks, some resource-intensive privacy-preserving schemes have been adopted in the previous literature. In order to balance resource consumption and data-privacy-preserving issues, a novel fuzzy-based privacy-preserving scheme is proposed. Our scheme is constructed on a T-S fuzzy trust theory, and network coding data streams are routed in optimal clusters formulated by a designed repeated game model to defend against pollution attacks. In particular, the security of our scheme relies on the hardness of the discrete logarithm. Then, we prove that the designed repeated game model has a subgame-perfect Nash equilibrium, and the model can improve resource utilization efficiency under the condition of data security. Simulation results show that the running time of the proposed privacy-preserving scheme is less than 1 s and the remaining energy is higher than 4 J when the length of packets is greater than 400 and the number of iterations is 100. Therefore, our scheme has higher time and energy efficiency than those of previous studies. In addition, the effective trust cluster formulation scheme (ETCFS) can formulate an optimal cluster more quickly under a kind of camouflage attack.

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A Game-Theoretic Approach for Cost-Effective Multicast Routing in the Internet of Things

Cited by 14 publications

References 35 publications

Energy-Efficient Decentralized Broadcasting in Wireless Multi-Hop Networks

Energy-Efficient Decentralized Broadcasting in Wireless Multi-Hop Networks

Machine Learning-Enabled Communication Approach for the Internet of Medical Things

Fuzzy-Based Privacy-Preserving Scheme of Low Consumption and High Effectiveness for IoTs: A Repeated Game Model

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