Topology Control Game Algorithm of Multi-performance Cooperative Optimization with Self-Maintaining for WSN
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 fa...
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| Published in | Wireless personal communications Vol. 94; no. 3; pp. 1237 - 1262 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.06.2017
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
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| 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. |
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| AbstractList | 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. |
| Author | Liu, Hao-Ran Chen, Bai Ru, Xiao-Yue Hao, Xiao-Chen Li, Xi-Da Liu, Wei-Jing Xin, Min-Jie |
| Author_xml | – sequence: 1 givenname: Hao-Ran surname: Liu fullname: Liu, Hao-Ran organization: The Key Laboratory for Special Fiber and Fiber Sensor of Hebei Province, Yanshan University – sequence: 2 givenname: Min-Jie surname: Xin fullname: Xin, Min-Jie organization: Institute of Electrical Engineering, Yanshan University – sequence: 3 givenname: Wei-Jing surname: Liu fullname: Liu, Wei-Jing organization: Institute of Electrical Engineering, Yanshan University – sequence: 4 givenname: Bai surname: Chen fullname: Chen, Bai organization: Institute of Electrical Engineering, Yanshan University – sequence: 5 givenname: Xiao-Chen surname: Hao fullname: Hao, Xiao-Chen email: haoxiaochen@ysu.edu.cn organization: Institute of Electrical Engineering, Yanshan University – sequence: 6 givenname: Xi-Da surname: Li fullname: Li, Xi-Da organization: The Key Laboratory for Special Fiber and Fiber Sensor of Hebei Province, Yanshan University – sequence: 7 givenname: Xiao-Yue surname: Ru fullname: Ru, Xiao-Yue organization: Institute of Electrical Engineering, Yanshan University |
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| Keywords | Wireless sensor network Link quality Cooperative optimization Topology control Multiple performance Game theory |
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In Advanced technologies, embedded and multimedia for human-centric computing (pp. 1215–1225). Springer, Netherlands, 2014. HaoXCZhangYXLiuBJiaNEnergy-balanced and reliable topology control game algorithm for sensor networksJournal of Software201122Suppl. 1112 Liao, C. C., & Ting, C. K. (2012). Extending the lifetime of dynamic wireless sensor networks by genetic algorithm. In Congress on evolutionary computation (CEC) (pp. 1–8). Brisbane: IEEE, 2012. 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Cooperative TC with adaptation for improved lifetime in Wireless Ad Hoc Networks. In INFOCOM, 2012 Proceedings IEEE (pp. 262–270). IEEE, 2012. – reference: LiuHRYinRRHaoXCDouJJBiWHA robust adjustable topology algorithm with steady links in wireless sensor networkJournal of Electronics & Information Technology2009311127512756 – reference: Ben-OthmanJBessaoudKBuiASelf-stabilizing algorithm for efficient topology control in wireless sensor networksJournal of Computational Science20134419920810.1016/j.jocs.2012.01.003 – reference: TripathiBSTripathiSSMinimum transmitting power and other performance metrics in regular WSN in fading environmentInternational Journal of New Trends in Electronics and Communication201422712 – reference: MiaoXNXuGCooperative differential game model based on trade-off between energy and delay for wireless sensor networksAnnals of Operations Research20132061297310307384910.1007/s10479-013-1354-z1271.90018 – reference: HaoXCZhangYXLiuBJiaNEnergy-balanced and reliable topology control game algorithm for sensor networksJournal of Software201122Suppl. 1112 – reference: ZhangYXStudy on topology optimization algorithm based on power control and channer allocation for wireless sensor network2012Qin HuangdaoYanshan University4344 – reference: Schweizer, I., Wagner, M., Bradler, D., et al. (2012). k TC-robust and adaptive wireless ad-hoc topology control. In 2012 21st International conference on computer communications and networks (ICCCN) (pp. 1–9). IEEE, Munich, 2012. – reference: Yang, G. Y., & Zhang, G. Y. (2011). A power control algorithm based on non-cooperative game for wireless sensor networks. In 2011 International conference on electronic and mechanical engineering and information technology (EMEIT) (pp. 687–690). IEEE, 2011. – reference: ZhaoXZhuangYWangJLocal adaptive transmit power assignment strategy for wireless sensor networksJournal of Central South University2012191909192010.1007/s11771-012-1225-9 – reference: Cho, H. H., Tseng, F. H., Shih, T. K., et al. (2014) A k-cooperative analysis in game-based WSN environment. In Advanced technologies, embedded and multimedia for human-centric computing (pp. 1215–1225). Springer, Netherlands, 2014. – reference: HeinzelmanWRChandrakasanAPBalakrishnanHNunamakerJSpragueREnergy-efficient communication protocol for wireless microsensor networksProceedings of the Hawaaian international conference on system science2000WashingtonIEEE Press30053014 – reference: Wang, C. H. (2012). An energy-balance based distributed Topology Control algorithm for wireless sensor networks. In Proceedings of 2nd international conference on mechatronics and intelligent materials (pp. 1392–1396). Guilin, China, 2012. – reference: Luo, J., Pan, C., Li, R. F., & Ge, F. (2012). Power control in distributed wireless sensor networks based on non-cooperative game theory. International Journal of Distributed Sensor Networks (pp. 1–10). – reference: KubischMKarlHWoliszAZhongLCRabaeyJYanikomerogluHDistributed algorithms for transmission power control in wireless sensor networksProceedings of the IEEE wireless communications and networking conference (WCNC)2003New YorkIEEE Press1620 – reference: YounisOFahmySHEED: A hybrid, energy-efficient, distributed clustering approach for ad-hoc sensor networksIEEE Transactions on Mobile Computing20043466066910.1109/TMC.2004.41 – reference: XingGLuCJiaXLocalized and configurable Topology Control in lossy wireless sensor networksAd Hoc Networks20131141345135810.1016/j.adhoc.2011.04.007 – reference: Wattenhofer, R., & Zollinger, A. (2004). XTC: A practical Topology Control algorithm for ad-hoc networks. In Proceedings of the 18th international parallel and distributed processing symposium (pp. 216–223). New Mexico: IEEE, 2004. – reference: FengDJiangCLimGA survey of energy-efficient wireless communicationsIEEE Communications Surveys & Tutorials201315116717810.1109/SURV.2012.020212.00049 – reference: LiYJWangZSunYXAnalyzing and modeling of the wireless link for sensor networksChinese Journal of Sensor and Actuators200720818461851 – reference: Huang, Y., Martínez, J. F., Hernández Díaz, V., et al. (2014). Localized and energy-efficient topology control in wireless sensor networks using fuzzy-logic control approaches. Mathematical Problems in Engineering (pp. 1–11). – reference: Liao, C. C., & Ting, C. K. (2012). Extending the lifetime of dynamic wireless sensor networks by genetic algorithm. In Congress on evolutionary computation (CEC) (pp. 1–8). Brisbane: IEEE, 2012. – reference: SenguptaDRoyAA literature survey of topology control and its related issues in wireless sensor networksInternational Journal of Information Technology and Computer Science201410192710.5815/ijitcs.2014.10.03 – reference: ZhangYHuangDJiMThe evolution game analysis of clustering for asymmetrical multi-factors in WSNsComputers & Electrical Engineering20133961746175710.1016/j.compeleceng.2012.11.025 – reference: ShiHYWangWLKwokNMGame theory for wireless sensor networks: A surveySensors20121279055909710.3390/s120709055 – reference: Akerberg, J., Gidlund, M., & Bjorkman, M. (2011). Future research challenges in wireless sensor and actuator networks targeting industrial automation. In 2011 9th IEEE international conference on industrial informatics (INDIN) (pp. 410–415). 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| SubjectTerms | Algorithms Communications Engineering Computer Communication Networks Computer simulation Engineering Game theory Networks Quality assessment Signal,Image and Speech Processing Topology optimization Wireless sensor networks |
| Title | Topology Control Game Algorithm of Multi-performance Cooperative Optimization with Self-Maintaining for WSN |
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