Min–max movement of barrier coverage with sink-based mobile sensors for crowdsensing

Abstract

Emerging crowdsensing applications imposed a new barrier coverage problem called min–max sink-based linear barrier coverage (min–max SLBC). In the problem, we are given a group of sinks distributed on a plane, each of which can disseminate an infinite number of nonuniform mobile sensors. The aim is to cover a given linear barrier using mobile sensors disseminated from the sinks, such that the maximum energy consumed by sensor movement is minimized. We devise a polynomial algorithm for min–max SLBC with nonuniform sensors, despite the sensor-based linear barrier coverage counterpart of the problem was proven strongly NP-hard. To this end, we first present a polynomial-time algorithm, namely Separated Target Coverage Algorithm (STCA), for optimally solving the discretized version of min–max SLBC. Then we devise the exact algorithm called Segment Collaborative-Coverage Algorithm (SCCA) for the continuous version of min–max SLBC, by improving an approximate solution computed by STCA to eventually obtain an arguably optimal solution. Lastly, numerical experiments are carried out to validate the efficiency and effectiveness of SCCA via comparing with other baselines including the state-of-art algorithms.