Towards Energy-Fairness in Asynchronous Duty-Cycling Sensor Networks

In this article, we investigate the problem of controlling node sleep intervals so as to achieve the min-max energy fairness in asynchronous duty-cycling sensor networks. We propose a mathematical model to describe the energy efficiency of such networks and observe that traditional sleep interval setting strategies, for example, operating sensor nodes with an identical sleep interval, or intuitive control heuristics, for example, greedily increasing sleep intervals of sensor nodes with high energy consumption rates, hardly perform well in practice. There is an urgent need to develop an efficient sleep interval control strategy for achieving fair and high energy efficiency. To this end, we theoretically formulate the Sleep Interval Control (SIC) problem and find out that it is a convex optimization problem. By utilizing the convex property, we decompose the original problem and propose a distributed algorithm, called GDSIC. In GDSIC, sensor nodes can tune sleep intervals through a local information exchange such that the maximum energy consumption rate of the network approaches to be minimized. The algorithm is self-adjustable to the traffic load variance and is able to serve as a unified framework for a variety of asynchronous duty-cycling MAC protocols. We implement our approach in a prototype system and test its feasibility and applicability on a 50-node testbed. We further conduct extensive trace-driven simulations to examine the efficiency and scalability of our algorithm with various settings.