Research of Network Capacity and Transmission Energy&nbsp; Consumption in WSNs Based on Game Theory

HAO Xiaochen; LIU Jinshuo; YAO Ning; XIE Lixia; WANG Liyuan

doi:10.11999/JEIT170927

Volume 40 Issue 7

Jul. 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(7): 1715-1722

HAO Xiaochen, LIU Jinshuo, YAO Ning, XIE Lixia, WANG Liyuan. Research of Network Capacity and Transmission Energy Consumption in WSNs Based on Game Theory[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1715-1722. doi: 10.11999/JEIT170927

Citation:

HAO Xiaochen, LIU Jinshuo, YAO Ning, XIE Lixia, WANG Liyuan. Research of Network Capacity and Transmission Energy Consumption in WSNs Based on Game Theory[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1715-1722. doi: 10.11999/JEIT170927

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Research of Network Capacity and Transmission Energy Consumption in WSNs Based on Game Theory

doi: 10.11999/JEIT170927

HAO Xiaochen LIU Jinshuo YAO Ning XIE Lixia WANG Liyuan

Funds:

The National Natural Science Foundation of China (61403336), The Natural Science Foundation of Hebei Province (F2015203342), The Independent Research Project Topics B Category for Young Teacher of Yanshan University (15LGB007)

Received Date: 2017-09-30
Rev Recd Date: 2018-03-08
Publish Date: 2018-07-19

Abstract

Abstract

To solve the problem that the network capacity decreases with the increasing interference in Wireless Sensor Networks (WSNs), a joint power control and channel allocation optimization game model is constructed, which considers the limitation of network energy. This game model contains the network capacity and the energy consumption of data transmission in the network. Theoretical analysis proves the existence of the optimal power and the optimal channel. Based on the model, a joint Power control and Channel allocation Optimization Algorithm for wireless sensor networks (PCOA) is proposed, which adopts the best response strategy. The theoretical analysis proves that this algorithm can converge to Nash Equilibrium. Besides, the information complexity of this algorithm is small. Simulation results show that PCOA algorithm can reduce the interference and the energy consumption, which increases the network capacity.
- Wireless Sensor Networks (WSNs)、Network capacity、Energy consumption、Power control、Channel allocation,

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References(22)

References

QIAN Zhihong and WANG Yijun. Internet of things-oriented wireless sensor networks review[J]. Journal of Electronics & Information Technology, 2013, 35(1): 215-227. doi: 10.3724/ SP.J.1146.2012.00876.

钱志鸿, 王义君. 面向物联网的无线传感器网络综述[J]. 电子与信息学报, 2013, 35(1): 215-227.

doi: 10.3724/SP.J.1146. 2012.00876.

[2] ELETREBY R and O. Secure and reliable connectivity in heterogeneous wireless sensor networks[C]. IEEE International Symposium on Information Theory, Aachen, Germany, 2017: 2880-2884. doi: 10.1109/ISIT. 2017.8007056.

[3] CHOUIKHI S, KORBI I E, GHAMRI-DOUDANE Y, et al. Routing-based multi-channel allocation with fault recovery for wireless sensor networks[C]. IEEE International Conference on Communications, London, UK, 2015: 6424-6430. doi: 10.1109/ICC.2015.7249348.

[4] SRBINOVSKA M, GAVROVSKI C, DIMCEV V, et al. Environmental parameters monitoring in precision agriculture using wireless sensor networks[J]. Journal of Cleaner Production, 2015, 88(1): 297-307. doi: 10.1016/ j.jclepro.2014.04.036.

LIU Haoran, SUN Yajing, LIU Bin, et al. Energy consumption balanced scale-free fault-tolerant topology model for wireless sensor networks[J]. Chinese Journal of Computers, 2017, 40(8): 1843-1855. doi: 10.11897/SP.J.1016. 2017.01843.

[6] WEI Kaibin. Energy saving based target coverage algorithm in wireless sensor network[C]. International Conference on Intelligent Transportation, Big Data & Smart City, Changsha, China, 2016: 324-327. doi: 10.1109/ICITBS.2016.84.

[7] JAN M, NANDA P, HE X, et al. Enhancing lifetime and quality of data in cluster-based hierarchical routing protocol for wireless sensor network[C]. IEEE International Conference, Zhangjiajie, China, 2013: 1400-1407. doi: 10.1109/HPCC.and.EUC.2013.198.

[8] MEERA G S, GUPTA V, SEKHAR S P, et al. An efficient mobile sink routing in wireless sensor network using dynamic steiner tree[C]. IEEE International Conference on Advanced Networks and Telecommunications Systems, Bangalore, India, 2016: 1-6. doi: 10.1109/ANTS.2016.7947869.

[9] ELBATT T and EPHREMIDES A. Joint scheduling and power control for wireless Ad hoc networks[J]. IEEE Transactions on Wireless Communications, 2004, 3(1): 74-85. doi: 10.1109/TWC.2003.819032.

[10] SBOUI L, REZKI Z, and ALOUINI M S. On energy efficient power allocation for power-constrained systems[C]. IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communication, Saudi Arabia, 2014: 1954-1958. doi: 10.1109/PIMRC.2014.7136491.

[11] ZHANG Deyu, CHEN Zhigang, ZHOU Haibo, et al. Energy- balanced cooperative transmission based on relay selection and power control in energy harvesting wireless sensor network[J]. Computer Networks, 2016, 104(20): 189-197. doi: 10.1016/j.comnet.2016.05.013.

[12] CHEN Jiming, YU Qing, CHENG Peng, et al. Game theoretical approach for channel allocation in wireless sensor and actuator networks[J]. Automatic Control, 2011, 56(10): 2332-2344. doi: 10.1109/TAC.2011.2164014.

[13] ZHENG Jianchao, ZHANG Honggang, Cai Yueming, et al. Game-theoretic multi-channel multi-access in energy harvesting wireless sensor networks[J]. IEEE Sensors Journal, 2016, 16(11): 4587-4594. doi: 10.1109/JSEN.2016.2539346.

[14] JIANG Dingde, WANG Yuanting, HAN Yang, et al. Maximum connectivity-based channel allocation algorithm in cognitive wireless networks for medical applications[J]. Neurocomputing, 2017, 220(12): 41-51. doi: 10.1016/j.neucom. 2016.05.102.

[15] SONG Yang, ZHANG Chi, and FANG Yuguang. Joint channel and power allocation in wireless mesh networks: A game theoretical perspective[J]. IEEE Journal on Selected Areas in Communications, 2008, 26(7): 1149-1159. doi: 10.1109/JSAC.2008.080912.

[16] BARCELÓ M, CORREA A, VICARIO J, et al. Joint routing, channel allocation and power control for real-life wireless sensor networks[J]. Emerging Telecommunications Technologies, 2015, 26(5): 945-956. doi: 10.1002/ett.2783.

[17] MALEKI E and MIRJALILY G. Fault-tolerant interference- aware topology control in multi-radio multi-channel wireless mesh networks[J]. Computer Networks, 2016, 110(9): 206-222. doi: 10.1016/j.comnet.2016.08.026.

ZHENG Gengzhong. Research on topology control and optimization in wireless sensor networks[D]. [Ph.D. dissertation], Xidian University, 2012: 23-37.

YIN Rongrong, LIU Bin, LI Yaqian, et al. Research on the fault-tolerant topology in energy heterogeneous wireless sensor networks[J]. Journal of Electronics & Information Technology, 2012, 34(9): 2180-2186. doi: 10.3724/SP.J.1146. 2011.01421.

[20] HAO Xiaochen, WANG Meiqi, HOU Shuang, et al. Distributed topology control and channel allocation algorithm for energy efficiency in wireless sensor network: From a game perspective[J]. Wireless Personal Communications, 2015, 80(4): 1557-1577. doi: 10.1007/ s11277-014-2100-9.

LI Xiaolong, FENG Donglei, and PENG Pengcheng. A potential game based topology control algorithm for wireless sensor networks[J]. Acta Physica Sinica, 2016, 65(2): 028401. doi: 10.7498/aps.65.028401.

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