Wireless energy transfer in sensor networks with adaptive, limited knowledge protocols

Authors: Angelopoulos, C.M., Nikoletseas, S.E. and Raptis, T.P.

http://dx.doi.org/10.1016/j.comnet.2014.04.022

Journal: Computer Networks

Volume: 70

Pages: 113-141

DOI: 10.1016/j.comnet.2014.04.022

This data was imported from Scopus:

Authors: Angelopoulos, C.M., Nikoletseas, S. and Raptis, T.P.

Journal: Computer Networks

Volume: 70

Pages: 113-141

ISSN: 1389-1286

DOI: 10.1016/j.comnet.2014.04.022

We investigate the problem of efficient wireless energy transfer in Wireless Rechargeable Sensor Networks (WRSNs). In such networks a special mobile entity (called the Mobile Charger) traverses the network and wirelessly replenishes the energy of sensor nodes. In contrast to most current approaches, we envision methods that are distributed, adaptive and use limited network information. We propose three new, alternative protocols for efficient charging, addressing key issues which we identify, most notably (i) to what extent each sensor should be charged, (ii) what is the best split of the total energy between the charger and the sensors and (iii) what are good trajectories the Mobile Charger should follow. One of our protocols (LRP) performs some distributed, limited sampling of the network status, while another one (RTP) reactively adapts to energy shortage alerts judiciously spread in the network. We conduct detailed simulations in uniform and non-uniform network deployments, using three different underlying routing protocol families. In most cases, both our charging protocols significantly outperform known state of the art methods, while their performance gets quite close to the performance of the global knowledge method (GKP) we also provide. © 2014 Elsevier B.V. All rights reserved.

This data was imported from Web of Science (Lite):

Authors: Angelopoulos, C.M., Nikoletseas, S. and Raptis, T.P.

Journal: COMPUTER NETWORKS

Volume: 70

Pages: 113-141

eISSN: 1872-7069

ISSN: 1389-1286

DOI: 10.1016/j.comnet.2014.04.022

The data on this page was last updated at 05:09 on February 24, 2020.