Abstract
As an important application of wireless sensor networks (WSNs), deployment of mobile sensors to periodically monitor (sweep cover) a set of points of interest (PoIs) arises in various applications, such as environmental monitoring and data collection. For a set of PoIs in an Eulerian graph, the point sweep coverage problem of deploying the fewest sensors to periodically cover a set of PoIs is known to be Non-deterministic Polynomial Hard (NP-hard), even if all sensors have the same velocity. In this paper, we consider the problem of finding the set of PoIs on a line periodically covered by a given set of mobile sensors that has the maximum sum of weight. The problem is first proven NP-hard when sensors are with different velocities in this paper. Optimal and approximate solutions are also presented for sensors with the same and different velocities, respectively. For M sensors and N PoIs, the optimal algorithm for the case when sensors are with the same velocity runs in time; our polynomial-time approximation algorithm for the case when sensors have a constant number of velocities achieves approximation ratio ; for the general case of arbitrary velocities, and approximation algorithms are presented, respectively, where integer is the tradeoff factor between time complexity and approximation ratio.
Highlights
Coverage is one of the most important applications of wireless sensor networks (WSN), where sensors are placed on an area of interest to monitor the environment and detect extraordinary activities
We study a variant of this problem, named Maxweighted Point Sweep Coverage, to find the set of points of interest (PoIs) that have the maximum sum of weight, periodically covered by a given set of sensors with different velocities
For the special cases of the Max-weighed Point Sweep Coverage on the line (MPSCL) problem when sensors have a constant number of velocities, we present a 12 -approximation algorithm by extending the solution for the same-velocity case
Summary
Coverage is one of the most important applications of wireless sensor networks (WSN), where sensors are placed on an area of interest to monitor the environment and detect extraordinary activities. We study a variant of this problem, named Maxweighted Point Sweep Coverage, to find the set of PoIs that have the maximum sum of weight, periodically covered by a given set of sensors with different velocities. We show that it is NP-hard even when the PoIs are distributed on a line. We define the MPSCL problem, prove that it is NP-hard by showing that a special case of its decision version is NP-complete (NPC), and present optimal and approximation algorithms for the cases of mobile sensors with the same and different velocities, respectively.
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