Energy Harvesting for Wireless: a new replenishment strategy

QSHINEBP

QSHINE 2015, the Eleventh EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness took place last August in Taiwan. Many innovative researches on heterogeneous wired, wireless and hybrid networks were presented this year at the conference, but only two of them have been awarded as Best Papers. The first study was presented by Rong Yu from Guangdong University of Technology, and is titled ‘An Optimal Replenishment Strategy in Energy Harvesting Wireless Networks with Mobile Charger’.

State-of-the-art An energy harvesting wireless network consists of wireless nodes that are able to draw parts of their energy from the external environment by energy harvesting technologies. Recently, this kind of technology has been applied to wireless sensor networks in order to extend the network lifetime and decrease maintenance costs. On the other hand, harvested energy is often only available randomly, sporadically and small amounts. Energy replenishment schemes may utilize mobile charger to prolong the lifetime and improve the efficiency of wireless networks, and a mobile charger can wirelessly transfer energy to wireless nodes with rechargeable batteries. Current studies about this topic have some limitations, due to strict specific assumptions, such as fixed generated data rates, the same amount of replenished energy and the same size of energy storage for all nodes.

An optimal replenishment strategy The research presented at QSHINE considers a more practical scenario, and proposes an optimal energy replenishment strategy using stochastic inventory theory to derive the optimal amount of energy supplied by the mobile charger.

The main contributions of the new approach can be summarized as follows:

  • A more practical model considering three conditions: the time-varying rate of generated data; the different amount of replenished energy for nodes and the cost of energy stored in batteries;
  • Using a framework of stochastic inventory theory means a new perspective for solving the problem of energy replenishment;
  • As main results, the proposed strategy not only optimizes energy utilization, but also improves economic benefits.

The full research is available at the European Union Digital Library (EUDL)

Editorial Staff

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