Maximizing Quality of Coverage under Connectivity Constraints in Solar-Powered Active Wireless Sensor Networks

Abstract

Energy harvesting is a promising solution for reducing network maintenance and the overhead of replacing chemical batteries in sensor networks. In this article, problems related to controlling an active wireless sensor network comprised of nodes powered by both rechargeable batteries and solar energy are investigated. The objective of this control is to maximize the network's Quality of Coverage (QoC), defined as the minimum number of targets that can be covered by the network over a 24-hour period. Assuming a time-varying solar profile, the underlying problem is to optimally control the sensing range of each sensor so as to maximize the QoC. The problem is further constrained by requiring all active sensors to report any sensed data to a centralized base station, making connectivity a key factor in sensor management. Implicit in the solution is the allocation of solar energy during the day to sensing tasks and recharging of the battery so that a minimum coverage is guaranteed at all times. The problem turns out to be a nonlinear optimal control problem of high complexity. By exploiting the particular structure of the problem, we present a novel method for determining near-optimal sensing radii and routing paths as a series of quasiconvex (unimodal) optimization problems. The runtime of the proposed solution is 60X less than the standard optimal control method based on dynamic programming, while the worst-case error is less than 8%. The proposed method is scalable to large networks consisting of hundreds of sensors and targets. Several insights in the design of energy-harvesting networks are provided.