A k-Barrier Coverage Enhancing Scheme Based on Gaps Repairing in Visual Sensor Network

This article explains how to efficiently use the rotation ability of stationary sensors and relocation ability of mobile sensors to achieve
${k}$
-barrier coverage in a randomly deployed hybrid visual sensor network. Based on such a network, three problems are studied for
${k}$
-barrier coverage. The first problem is to minimize the number of required mobile sensors and the second is to minimize the total moving distance, with deployed stationary sensors and the requirement value of
${k}$
. The last problem focuses on solving the maximum number of strong barriers with deployed stationary and mobile sensors. To address these problems, we introduce a virtual barrier curve model and design a strong
${k}$
-barrier coverage enhancing scheme (KCES) to transfer the
${k}$
-barrier construction problems into barrier gaps repairing problem in
${k}$
turns. Both analytical and experimental studies demonstrate the effectiveness of the proposed approach.