Steady and fair rate allocation for rechargeable sensors in perpetual sensor networks

  • Authors:

  • Kai-Wei Fan;Zizhan Zheng;Prasun Sinha

  • Affiliations:

  • The Ohio State University, Columbus, OH, USA;The Ohio State University, Columbus, OH, USA;The Ohio State University, Columbus, OH, USA

  • Venue:
  • Proceedings of the 6th ACM conference on Embedded network sensor systems
  • Year:
  • 2008

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Abstract

Renewable energy enables sensor networks with the capability to recharge and provide perpetual data services. Due to low recharging rates and the dynamics of renewable energy such as solar and wind power, providing services without interruptions caused by battery runouts is non-trivial. Most environment monitoring applications require data collection from all nodes at a steady rate. The objective of this paper is to design a solution for fair and high throughput data extraction from all nodes in presence of renewable energy sources. Specifically, we seek to compute the lexicographically maximum data collection rate for each node, such that no node will ever run out of energy. We propose a centralized algorithm and an asynchronous distributed algorithm that can compute the optimal lexicographic rate assignment for all nodes. The centralized algorithm jointly computes the optimal data collection rate for all nodes along with the flows on each link, while the distributed algorithm computes the optimal rate when the routes are pre-determined. We prove the optimality for both the centralized and the distributed algorithms, and use a testbed with 155 sensor nodes to validate the distributed algorithm.