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An Efficient Combined Charging Strategy for Large-Scale Wireless Rechargeable Sensor Networks

Ying Dong, Shiyuan Li, Guangjiu Bao, Chunyue Wang

2020IEEE Sensors Journal31 citationsDOI

Abstract

The adoption of mobile energy equipment to replenish the energy in wireless sensor networks is gaining increasing attention. However, pioneering work on charging neglects the location and time-varied energy feature of the node, leading to a high charging frequency and long charging path. In this work, we aim to reduce the charging frequency and improve its efficiency. The temporal-spatial combined charging strategy (TSCCS) is developed, which can guarantee that a network runs for a long time. First, an energy and location aware K-means (ELAK-means) clustering algorithm is proposed to group nodes into clusters and construct the spatial location and the energy consumption of nodes. Second, to balance the energy consumption of nodes, an intra-cluster communication mode-simple tree-like communication mode (STCM) is proposed. A multiple backtracking method (M-BTM) ensures the communication mode of each node. The communication hops of nodes can be limited to within two hops in a cluster. Simulations demonstrate that TSCCS can enhance performance by reducing journey length and average charging frequency, improving the charging efficiency and ensuring that the energy consumption is more balanced across the network.

Topics & Concepts

Energy consumptionWireless sensor networkComputer scienceEfficient energy useWirelessCluster analysisNode (physics)BacktrackingEnergy (signal processing)Computer networkKey distribution in wireless sensor networksEnergy conservationReal-time computingWireless networkEngineeringElectrical engineeringTelecommunicationsAlgorithmStatisticsMachine learningMathematicsStructural engineeringEnergy Harvesting in Wireless NetworksWireless Power Transfer SystemsAdvanced MIMO Systems Optimization
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