Hierarchical, collaborative wireless energy transfer in sensor networks with multiple Mobile Chargers

• Published in: Computer networks (Amsterdam, Netherlands : 1999) Vol. 97; pp. 98 - 112
• Main Authors: Madhja, Adelina, Nikoletseas, Sotiris, Raptis, Theofanis P.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 14.03.2016; Elsevier Sequoia S.A
• Subjects: Charge; Charging; Collaboration; Collaborative charging; Comparative studies; Computer networks; Decision analysis; Distributed algorithms; Energy efficiency; Energy management; Energy transfer; Knowledge management; Mobility; Network flow problem; Networks; Nodes; Protocol; Protocol (computers); Robustness; Sensor networks; Sensors; State of the art; Structural hierarchy; Wireless energy transfer; Wireless networks; Wireless power transmission; Collaborative charging; Sensor networks; Mobility; Wireless energy transfer; Energy efficiency; Distributed algorithms
• ISSN: 1389-1286; 1872-7069
• DOI: 10.1016/j.comnet.2016.01.007

Wireless energy transfer is used to fundamentally address energy management problems in Wireless Rechargeable Sensor Networks (WRSNs). In such networks mobile entities traverse the network and wirelessly replenish the energy of sensor nodes. In recent research on collaborative wireless charging, the mobile entities are also allowed to charge each other. In this work, we enhance the collaborative feature by forming a hierarchical charging structure. We distinguish the Chargers in two groups, the hierarchically lower Mobile Chargers which charge sensor nodes and the hierarchically higher Special Chargers which charge Mobile Chargers. We define the Coordination Decision Problem and prove that it is NP-complete. Also, we propose a new protocol for 1-D networks which we compare with a state of the art protocol. Motivated by the improvement in 1-D networks, we propose and implement four new collaborative charging protocols for 2-D networks, in order to achieve efficient charging and improve important network properties. Our protocols are either centralized or distributed, and assume different levels of network knowledge. Extensive simulation findings demonstrate significant performance gains, with respect to non-collaborative state of the art charging methods. In particular, our protocols improve several network properties and metrics, such as the network lifetime, routing robustness, coverage and connectivity. A useful feature of our methods is that they can be suitably added on top of non-collaborative protocols to further enhance their performance.