Wireless energy transfer in sensor networks with adaptive, limited knowledge protocols Constantinos Marios Angelopoulos c , Sotiris Nikoletseas a,b , Theofanis P. Raptis a,b,⇑ a Department of Computer Engineering and Informatics, University of Patras, Greece b Computer Technology Institute and Press ‘‘Diophantus’’ (CTI), Patras, Greece c Centre Universitaire d’ Informatique, Université de Genève, Switzerland article info Article history: Received 21 September 2013 Received in revised form 14 March 2014 Accepted 28 April 2014 Available online 16 May 2014 Keywords: Sensor networks Energy efficiency Mobility Distributed algorithms Wireless energy transfer Wireless recharging abstract 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 effi- cient 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 fol- low. One of our protocols (LRP) performs some distributed, limited sampling of the net- work 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 knowl- edge method (GKP) we also provide. Ó 2014 Elsevier B.V. All rights reserved. 1. Introduction The last decade energy harvesting technologies have been effectively integrated into wireless sensor networks. A variety of ambient energy, such as mechanical, thermal, photovoltaic and electromagnetic energy, can be converted into electrical energy to charge sensor batteries. However, as all these energy sources come from the external envi- ronment and their spatial–temporal profiles exhibit great variations, the strength of harvested energy is typically low, and especially sensitive to the environment dynamics. As there is generally a lack of a priori knowledge of energy profiles, such dynamics imposes much difficulty on the design of protocols that must keep sensors from running out of energy. The technology of highly-efficient wireless energy transfer was proposed for efficient, non-radiative energy transmission over mid-range. The work in [1] has shown that through strongly coupled magnetic resonances, the efficiency of transferring 60 W of power over a distance in excess of 2 m is as high as 40%. Industry research also demonstrated that it is possible to improve transferring 60 W of power over a distance of up to 1 m with efficiency of 75% [2]. At present, commercial products utilizing wire- less energy transfer have been available on the market such as those in [3–5]. These technologies offer new possibilities for managing the available energy in wireless sensor networks and lead http://dx.doi.org/10.1016/j.comnet.2014.04.022 1389-1286/Ó 2014 Elsevier B.V. All rights reserved. ⇑ Corresponding author at: Department of Computer Engineering and Informatics, University of Patras, Greece. Tel.: +30 2610996964. E-mail address: traptis@ceid.upatras.gr (T.P. Raptis). Computer Networks 70 (2014) 113–141 Contents lists available at ScienceDirect Computer Networks journal homepage: www.elsevier.com/locate/comnet