Hindawi Publishing Corporation International Journal of Distributed Sensor Networks Volume 2013, Article ID 256569, 16 pages http://dx.doi.org/10.1155/2013/256569 Research Article eLighthouse: Enhance Solar Power Coverage in Renewable Sensor Networks Peng Liu, 1 Yifan Wu, 1 Jian Qiu, 1 Guojun Dai, 1 and Tingting Fu 2 1 Institute of Computer Application Technology, Hangzhou Dianzi University, Hangzhou 310018, China 2 Institute of Graphics and Image, Hangzhou Dianzi University, Hangzhou 310018, China Correspondence should be addressed to Tingting Fu; ft@hdu.edu.cn Received 16 May 2013; Revised 15 August 2013; Accepted 7 September 2013 Academic Editor: Aravind Kailas Copyright © 2013 Peng Liu et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Energy harvesting from ambient resource such as solar power improves the sustainability and continuous monitoring capability of sensor nodes. However, energy conservation and harvesting can hardly provide a complete solution due to two main reasons: the energy harvesting capabilities/opportunities are seriously afected by spatial and temporal facts regarding the location of sensor deployment, and distributed processing of sensing and communication are also uneven throughout the network which leads to unbalanced energy consumption. In this paper, we propose an energy transfer system called eLighthouse to level the energy harvesting and consumption of solar-powered WSN. An energy-hub equipment has been brought forward utilizing a controlled retrorefector to forward sunlight to the appropriate nodes which urgently require recharging. Te scheduling algorithm among multiple nodes is also included in this paper which helps to maintain the maximum number of nodes in active state; the localization algorithm which enables the controlled retrorefector for pointing correctly is also a key contribution of this paper. Te experimental and simulation results both demonstrated that the proposed system can maximize the utilization of the solar power charging technique efectively to prolong the network lifetime and build up a sustainable WSN. 1. Introduction Limited energy supply has been the main constraint of battery-powered system such as wireless sensor networks which provide continuous monitoring in ambient environ- ment. It greatly afects the sustainability of WSNs and has disproportionateimpactonthefdelity.Inthisarea,therecent research topics are mainly focused on two categories: energy saving and energy harvesting. A natural mechanism of energy saving is enhancing network protocols, such as energy-efcient MAC protocols, routing protocols, and data aggregation as shown in [1–3]. Te goals of these researches are not only to reduce the energy consumption rate but also to balance it. However, these schemes can only prolong the network lifetime to a limited extend but fail to make it sustainable. A promising solution to this problem is to explore energy harvesting and acquiring techniques. Solar power, wind power, and vibration power have all been introduced as perspective energy resource of tiny sensor nodes. Corresponding hardware design and experiments have also been introduced in many papers although it still sufers some limitations such as costliness, infexibility, and low efciency. Furthermore, without suf- fcient energy acquiring approaches, these methods cannot work well. On one hand, as a network performing distributed mon- itoring tasks, data communication and collection process are seriously dependent on task requirement and network topology. Sink nodes and other nodes near hot spots or in a busy route tend to consume their energy more rapidly which means energy consumption among the network that is unevenly distributed. On the other hand, the energy harvesting capability at each node may vary signifcantly due to environmental geometric. For example, the amount of harvested solar power in a sensor node varies due to factors of weather, location, and time, in spite of Maximum Power Point Tracking function being used. In one word, the energy harvesting is unbalanced as well as energy consumption. Researches have been carried out to balance the energy distribution, such as [4, 5]. However, these approaches only