Dependable k-coverage algorithms for sensor networks

TL;DR

This paper introduces centralized and distributed algorithms for sensor networks to achieve dependable k-coverage, enhancing robustness and extending network lifetime through sleep scheduling while maintaining continuous service.

Contribution

It presents novel centralized and distributed algorithms for k-coverage that improve network robustness and lifetime, including a guaranteed service controlled greedy sleep algorithm.

Findings

The controlled greedy sleep algorithm guarantees service despite errors.

Simulations show improved network lifetime with the proposed algorithms.

Compared to random solutions, the algorithms perform significantly better.

Abstract

Redundant sensing capabilities are often required in sensor network applications due to various reasons, e.g. robustness, fault tolerance, or increased accuracy. At the same time high sensor redundancy offers the possibility of increasing network lifetime by scheduling sleep intervals for some sensors and still providing continuous service with help of the remaining active sensors. In this paper centralized and distributed algorithms are proposed to solve the k-coverage sensing problem and maximize network lifetime. When physically possible, the proposed robust Controlled Greedy Sleep Algorithm provides guaranteed service independently of node and communication errors in the network. The performance of the algorithm is illustrated and compared to results of a random solution by simulation examples.