The optimal game model of energy consumption for nodes cooperation in WSN

Zhang, Jun; Yin, Jun; Xu, Tianyi; Gao, Ziyang; Qi, Honggang; Yin, Hongsheng

doi:10.1007/s12652-018-1128-1

Cited by 14 publications

(10 citation statements)

References 25 publications

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“…The advantages of swarm intelligence is that it ensures adaptability and stability of the environment which is useful when needed to conserve energy in wireless sensor networks [42,43]. Furthermore, the bioinspired PSO has become one of the most significant optimization algorithms and has been extensively utilised to solve complex optimization problems.…”

Section: Literature Reviewmentioning

confidence: 99%

An Innovative Hyperheuristic, Gaussian Clustering Scheme for Energy-Efficient Optimization in Wireless Sensor Networks

2021

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Energy stability on sensor nodes in wireless sensor networks (WSNs) is always an important challenge, especially during data capturing and transmission of packets. The recent advancement in distributed clustering algorithms in the extant literature proposed for energy efficiency showed refinements in deployment of sensor nodes, network duration stability, and throughput of information data that are channelled to the base station. However, much scope still exists for energy improvements in a heterogeneous WSN environment. This research study uses the Gaussian elimination method merged with distributed energy efficient clustering (referred to as DEEC-Gauss) to ensure energy efficient optimization in the wireless environment. The rationale behind the use of the novel DEEC-Gauss clustering algorithm is that it fills the gap in the literature as researchers have not been able to use this scheme before to carry out energy-efficient optimization in WSNs with 100 nodes, between 1,000 and 5000 rounds and still achieve a fast time output. In this study, using simulation, the performance of highly developed clustering algorithms, namely, DEEC, EDEEC_E, and DDEEC, was compared to the proposed Gaussian Elimination Clustering Algorithm (DEEC-Gauss). The results show that the proposed DEEC-Gauss Algorithm gives an average percentage of 4.2% improvement for the first node dead (FND), a further 2.8% improvement for the tenth node dead (TND), and the overall time of delivery was increased and optimized when compared with other contemporary algorithms.

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Section: Literature Reviewmentioning

confidence: 99%

An Innovative Hyperheuristic, Gaussian Clustering Scheme for Energy-Efficient Optimization in Wireless Sensor Networks

2021

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“…One notable merit of this approach is that it can operate independently of the topology of the sensory field. The work in [157] proposes a dynamic node scheduling scheme using non cooperative game theoretic strategy to significantly cut down idle listening and improve the energy efficiency of WSNs. The minimum dominating cover set selection strategy based on game theory is discussed in [158] and a game theory-based approach for target coverage in a directional sensor network is described in [159].…”

Section: Figure 18 State Diagram Of Obsp Protocolmentioning

confidence: 99%

QoS-Aware Energy Management and Node Scheduling Schemes for Sensor Network-Based Surveillance Applications

et al. 2021

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“…is a Nash equilibrium of the game G = fM, S, ug. 32 Property 1. There is at least one Nash equilibrium in a finite perfect information game.…”

Section: Model Analysismentioning

confidence: 99%

“…If any participant i ∈ M and any strategy s i ∈ S satisfy u i ( s i * , s − i * ) ≥ u i ( s i , s − i * ) , then the strategy combination s * = ( s i * , s − i * ) is a Nash equilibrium of the game Γ = { M , S , u } . 32…”

Section: Design and Analysis Of Routing Game Modelmentioning

confidence: 99%

Game algorithm based on link quality: Wireless sensor network routing game algorithm based on link quality

Hao

Hou

Dang

et al. 2021

International Journal of Distributed Sensor Networks

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Aiming at the problems of low data transmission efficiency and uneven energy consumption caused by unreliable link communication in the routing process of wireless sensor networks, this article designs a routing game algorithm based on link quality. In this article, the index for evaluating link quality is defined first. Then, the link quality, node residual energy, and minimum jump transmission strategy are integrated into the utility function to establish a game model to determine the best next hop transmission node. Finally, the routing optimal transmission path is obtained according to the analysis of the existence of Nash equilibrium in the game. In the simulation experiment, the influence of the change of link quality parameters on the performance of the algorithm is analyzed, and the proposed algorithm is compared with non-linear weight particle swarm optimization (NWPSO) algorithm and Low Energy Adaptive Clustering Hierarchy-Improvement (LEACH-IMPT) algorithm in three aspects: the number of surviving nodes, network lifetime, and network energy consumption. The results show that the network lifetime of this method is 16.8% longer than that of LEACH-IMPT algorithm and 7.5% longer than that of NWPSO algorithm. This shows that the algorithm can effectively balance the network energy consumption and prolong the network life cycle. In addition, according to the routing path obtained in the simulation experiment, the optimality of its link quality is verified in the real experimental environment, and the experimental results prove the feasibility of the method in this article in practice.

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The optimal game model of energy consumption for nodes cooperation in WSN

Cited by 14 publications

References 25 publications

An Innovative Hyperheuristic, Gaussian Clustering Scheme for Energy-Efficient Optimization in Wireless Sensor Networks

An Innovative Hyperheuristic, Gaussian Clustering Scheme for Energy-Efficient Optimization in Wireless Sensor Networks

QoS-Aware Energy Management and Node Scheduling Schemes for Sensor Network-Based Surveillance Applications

Game algorithm based on link quality: Wireless sensor network routing game algorithm based on link quality

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