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Topology Control Game Algorithm of Multi-performance Cooperative Optimization with Self-Maintaining for WSN.

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Title: Topology Control Game Algorithm of Multi-performance Cooperative Optimization with Self-Maintaining for WSN.
Authors: Liu, Hao-Ran1, Xin, Min-Jie2, Liu, Wei-Jing2, Chen, Bai2, Hao, Xiao-Chen2 haoxiaochen@ysu.edu.cn, Li, Xi-Da1, Ru, Xiao-Yue2
Source: Wireless Personal Communications. Jun2017, Vol. 94 Issue 3, p1237-1262. 26p.
Subjects: Wireless sensor networks, Cooperating objects (Computer systems), Wireless sensor nodes, Mathematical optimization, Topology, Telecommunication systems, Electronic systems
Abstract: Wireless sensor network is the key technology to extend the covering area of Internet in the future. It has a range of application values. A network with a lot of good performance could meet more demands of practical applications. Therefore, topology control whose main goal is to prolong lifetime faces a new challenge. Although good link quality can't improve some performance such as robustness and sparseness, it could decrease the probability of data retransmission. So if links have good quality, the energy is saved and the delay is reduced. But most existing topology control optimization algorithms ignore the importance of link quality. Hence, a bi-directional link communication quality evaluation indicator is designed firstly. Then, connectivity, link weight, interference among nodes, equilibrium of surplus energy, node degree, the transmitting power of nodes and node's current surplus energy are integrated into utility function to structure a game model named MPOGM. Finally, on the basis of MPOGM, a topology control game algorithm of multi-performance cooperative optimization with self-maintaining (MPCOSM) is proposed. The theoretical analysis demonstrates that MPCOSM could converge to Pareto Optimal Nash Equilibrium. The simulation results show that MPCOSM could achieve the cooperative optimization of multiple performance. [ABSTRACT FROM AUTHOR]
Copyright of Wireless Personal Communications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Wireless sensor network is the key technology to extend the covering area of Internet in the future. It has a range of application values. A network with a lot of good performance could meet more demands of practical applications. Therefore, topology control whose main goal is to prolong lifetime faces a new challenge. Although good link quality can't improve some performance such as robustness and sparseness, it could decrease the probability of data retransmission. So if links have good quality, the energy is saved and the delay is reduced. But most existing topology control optimization algorithms ignore the importance of link quality. Hence, a bi-directional link communication quality evaluation indicator is designed firstly. Then, connectivity, link weight, interference among nodes, equilibrium of surplus energy, node degree, the transmitting power of nodes and node's current surplus energy are integrated into utility function to structure a game model named MPOGM. Finally, on the basis of MPOGM, a topology control game algorithm of multi-performance cooperative optimization with self-maintaining (MPCOSM) is proposed. The theoretical analysis demonstrates that MPCOSM could converge to Pareto Optimal Nash Equilibrium. The simulation results show that MPCOSM could achieve the cooperative optimization of multiple performance. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Wireless Personal Communications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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