Joint Energy Management and Resource Allocation in Rechargeable Sensor Networks

—Energy harvesting sensor platforms have opened up a new dimension to the design of network protocols. In order to sustain the network operation, the energy consumption rate cannot be higher than the energy harvesting rate, otherwise, sensor nodes will eventually deplete their batteries. In contrast to traditional network resource allocation problems where the resources are static, time variations in recharging rate presents a new challenge. In this paper, we first explore the performance of an efficient dual decomposition and subgradient method based algorithm, called QuickFix, for computing the data sampling rate and routes. However, fluctuations in recharging can happen at a faster time-scale than the convergence time of the traditional approach. This leads to battery outage and overflow scenarios, that are both undesirable due to missed samples and lost energy harvesting opportunities respectively. To address such dynamics, a local algorithm, called SnapIt, is designed to ada...

• Type: Journal
• Year: 2010
• Where: INFOCOM
• Authors: Ren-Shiou Liu, Prasun Sinha, Can Emre Koksal
• Keywords: Communications, Energy Harvesting, Energy Harvesting Rate, INFOCOM 2010, Sampling Rate