Efficient Line K-Coverage Algorithms in Mobile Sensor Network

Yang Wang, Shuang Wu, Xiaofeng Gao, Fan Wu, Guihai Chen

Abstract: In this paper, we address a new type of coverage problem in mobile sensor network, named Line K-Coverage. It guarantees that any line cutting across a region of interest will be detected by at least K sensors. We aim to schedule an efficient sensor movement to satisfy the line K-coverage while minimize the total sensor movements for energy efficiency, which is named as LK-MinMovs problem. We propose a pioneering layer-based algorithm LLK-MinMovs to solve it in polynomial time. Compared with a MinSum algorithm from previous literature to solve line 1-coverage problem, LLK-MinMovs fixes a critical flaw after finding a counter example for MinSum. We further construct two time-efficient heuristics named LK-KM and LK-KM+ based on the famous Hungarian algorithm. By sacrificing optimality a little bit, these two algorithms runs extremely faster than algorithm LLK-MinMovs. We validate the efficiency of our designs in numerical experiments and compare them under different experiment settings.