Potential-Game Based Optimally Rigid Topology Control in Wireless Sensor Networks

Luo, Xiaoyuan; Li, Xiaolei; Wang, Jian‐Ge; Guan, Xinping

doi:10.1109/access.2018.2814079

Cited by 8 publications

(3 citation statements)

References 36 publications

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“…The algorithm introduces a link weight function which considers the link quality and residual energy synthetically to establish a topology with high-quality link communication and balanced energy consumption. Furthermore, Luo et al combined the rigid graph and potential-game into a two-stage constraint solving problem, which greatly enhanced the network life cycle [12].…”

Section: Related Workmentioning

confidence: 99%

“…In this paper, the principle of optimal rigid graph is introduced to eliminate redundant links in the network. As shown in Table 2, Each node i calculates its own number k of neighbors according to the set R of neighbor nodes, builds its sub-graph matrix i G of weight link set i W from Formula (12) and (13), and determines whether the link set it builds satisfies the construction of a rigid matrix based on Definition 4-6 and Lemma 2. If so, a rigid matrix M can be constructed from Formula (14) - (16), and an optimal subrigid matrix c M will be constructed according to Property 3.…”

Section: Redundant Link Deletion Stagementioning

confidence: 99%

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Topology Control Algorithm of Underwater Sensor Network Based on Potential-Game and Optimal Rigid Sub-Graph

Wei

Han

2020

IEEE Access

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Aiming at the problems of unbalanced energy consumption, redundant links, short life cycle in underwater sensor networks, a topology control algorithm for underwater wireless sensor networks based on potential-game and optimal rigid sub-graph is proposed. Firstly, based on the potential game theory, the topology control model of underwater sensor network is constructed, which considers network coverage, connectivity, transmission energy consumption, end-to-end delay, transmission success rate, node residual energy and so on. It is proved that the model is an ordinal potential game and has a Nash equilibrium solution. Then, the link weight function of node load and node residual energy is introduced, and the redundant links in the network are eliminated by using the principle of optimal rigid sub-graph.Simulation experiments and contrast analysis show that compared with other network models, the network topology model constructed in this paper has lowed node load and stronger energy balance, prolongs the life cycle of the network and more conforms to the underwater environment. INDEX TERMS redundant links, topology control, potential-game, optimal rigid sub-graph, life cycle.

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Section: Related Workmentioning

confidence: 99%

Section: Redundant Link Deletion Stagementioning

confidence: 99%

Topology Control Algorithm of Underwater Sensor Network Based on Potential-Game and Optimal Rigid Sub-Graph

Wei

Han

2020

IEEE Access

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“…In [20], a game theoretic model to extend the network life is investigated in software defined radio WSN. A potential game is formulated in [21] as a solution for the topology control optimisation problem in a WSN. Du et al [22] proposed a non‐cooperative potential game for topology control addressing the problem of power minimisation and energy balancing in a WSN.…”

Section: Related Workmentioning

confidence: 99%

Game theoretical model for information transmission in structure‐free wireless sensor networks

Chaiel¹,

Abass

2020

IET Communications

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IoT networks 3D deployment using hybrid many-objective optimization algorithms

et al. 2020

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When resolving many-objective problems, multi-objective optimization algorithms encounter several difficulties degrading their performances. These difficulties may concem the exponential execution time, the effectiveness of the mutation and recom bination operators or finding the tradeoff between diversity and convergence. In this paper, the issue of 3D redeploying in indoor the connected objects (or nodes) in the Internet of Things collection networks (formerly known as wireless sensor nodes) is investigated. The airn is to determine the ideal locations of the objects to be added to enhance an initial deployment while satisfying antagonist objectives and constraints. In this regard, a first proposed contribution airn to introduce an hybrid mode! that includes many-objective optirnization algorithms relying on decomposition (MOEA/D, MOEA/DD) and reference points (Two_Arch2, NSGA-III) while using two strategies for introducing the preferences (P I-EMO-P C) and the dimensionality reduction (MVU-PCA). This hybridization aims to combine the algorithms advantages for resolving the many-objective issues. The second contribution concems prototyping and deploying real connected objects which allows assessing the performance of the proposed hybrid scheme on a real world environment. The obtained experirnental and numerical results show the efficiency of the suggested hybridization scheme against the original algorithms.

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Potential-Game Based Optimally Rigid Topology Control in Wireless Sensor Networks

Cited by 8 publications

References 36 publications

Topology Control Algorithm of Underwater Sensor Network Based on Potential-Game and Optimal Rigid Sub-Graph

Topology Control Algorithm of Underwater Sensor Network Based on Potential-Game and Optimal Rigid Sub-Graph

Game theoretical model for information transmission in structure‐free wireless sensor networks

IoT networks 3D deployment using hybrid many-objective optimization algorithms

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