Collaborative mobile charging policy for perpetual operation in large-scale wireless rechargeable sensor networks

Abstract In this paper, we present a mobile charging policy for perpetual operation of large-scale wireless rechargeable sensor networks (WRSNs). In these networks, dedicated mobile chargers (MCs) move throughout the network and supply energy for power-limited sensors. The MCs not only charge the sensors but also charge each other. We develop a hop-based mobile charging policy (HMCP) minimizing the number of required MCs. The HMCP considers both the sensors’ unbalanced energy consumption rate and the MCs’ limited energy capacity. The minimum number of MCs is is formulated as an integer programming problem. We first verify the existence of an optimal solution, and later design an algorithm to obtain the optimal solution. Based on HMCP, we propose HMCP+ for the case that only one MC can recharge sensors in each region. HMCP+ plans MCs’ paths to decrease mobile energy consumption by MCs. Finally, performance of the proposed polices is validated through the simulation results.

[1]  Abbas Mehrabi,et al.  General Framework for Network Throughput Maximization in Sink-Based Energy Harvesting Wireless Sensor Networks , 2017, IEEE Transactions on Mobile Computing.

[2]  Sotiris E. Nikoletseas,et al.  Efficient energy management in wireless rechargeable sensor networks , 2012, MSWiM '12.

[3]  Long Chen,et al.  Energy-balanced cooperative transmission based on relay selection and power control in energy harvesting wireless sensor network , 2016, Comput. Networks.

[4]  Hanif D. Sherali,et al.  On renewable sensor networks with wireless energy transfer , 2011, 2011 Proceedings IEEE INFOCOM.

[5]  S. Zhuiykov.  Solid-state sensors monitoring parameters of water quality for the next generation of wireless sensor networks , 2012 .

[6]  Zhigang Chen,et al.  Energy-Harvesting-Aided Spectrum Sensing and Data Transmission in Heterogeneous Cognitive Radio Sensor Network , 2016, IEEE Transactions on Vehicular Technology.

[7]  Cong Wang,et al.  Joint Mobile Data Gathering and Energy Provisioning in Wireless Rechargeable Sensor Networks , 2014, IEEE Transactions on Mobile Computing.

[8]  Jianping Pan,et al.  Evaluating the On-Demand Mobile Charging in Wireless Sensor Networks , 2015, IEEE Transactions on Mobile Computing.

[9]  Guihai Chen,et al.  Minimizing the number of mobile chargers for large-scale wireless rechargeable sensor networks , 2014, Comput. Commun..

[10]  Yunhao Liu,et al.  Underground Structure Monitoring with Wireless Sensor Networks , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[11]  Mohammad S. Obaidat,et al.  GTCharge: A game theoretical collaborative charging scheme for wireless rechargeable sensor networks , 2016, J. Syst. Softw..

[12]  Jenq-Shiou Leu,et al.  Energy Efficient Clustering Scheme for Prolonging the Lifetime of Wireless Sensor Network With Isolated Nodes , 2015, IEEE Communications Letters.

[13]  Zhigang Chen,et al.  Utility-Optimal Resource Management and Allocation Algorithm for Energy Harvesting Cognitive Radio Sensor Networks , 2016, IEEE Journal on Selected Areas in Communications.

[14]  Yuanyuan Yang,et al.  A Framework of Joint Mobile Energy Replenishment and Data Gathering in Wireless Rechargeable Sensor Networks , 2014, IEEE Transactions on Mobile Computing.

[15]  Cong Wang,et al.  Wireless Rechargeable Sensor Networks , 2015, SpringerBriefs in Electrical and Computer Engineering.

[16]  Jie Wu,et al.  Collaborative Mobile Charging , 2015, IEEE Transactions on Computers.

[17]  Sotiris E. Nikoletseas,et al.  Distributed wireless power transfer in sensor networks with multiple Mobile Chargers , 2015, Comput. Networks.

[18]  Hossam S. Hassanein,et al.  Towards prolonged lifetime for deployed WSNs in outdoor environment monitoring , 2015, Ad Hoc Networks.