Time-based redeployment of multi-class nodes for reliable wireless sensor network coverage

Abstract

We consider the problem of redeploying nodes into a wireless sensor network (WSN) to maintain reliable area coverage over time as nodes fail. Specifically, we consider the class of time-based node redeployment policies in which the WSN is inspected after a fixed amount of time, after which new sensor nodes are redeployed to bring the number of functioning nodes to a desired level. Whereas previous research on time-based node redeployment assumes nodes are identical with respect to time to failure, we use multiple classes of sensor nodes to represent a scenario where nodes’ times to failure are dependent on positioning in the network. We propose a partial survival signature (PSS) approach for estimating area coverage reliability under a given time-based redeployment policy, where the PSS is estimated by Monte Carlo simulation. This PSS representation enables efficient re-evaluation of coverage reliability under different redeployment policies, thus allowing the use of metaheuristics to obtain a set of redeployment policies that are near-efficient with respect to cost and coverage reliability. We present a numerical example to demonstrate that the PSS approach yields accurate estimates of coverage reliability within a reasonable amount of computation time. Furthermore, we apply non-dominated sorting genetic algorithm II (NSGA-II) to optimize the numerical example with respect to cost and coverage reliability.