Barrier coverage problem is one of the most crucial issues in wireless sensor networks (WSNs) which have been applied to a wild range of applications. A lot of algorithms have been proposed to cope with this problem. However, the majority researches apply the Boolean Sensing Model (BSM) and the sensing frequency of the sensor is not considered, which are difficult to reflect the physical features of the sensing component. This paper proposed a barrier coverage algorithm, called Guaranteeing Surveillance Quality with Minimal Number of Active Sensors, or GSMS in short, aiming to guarantee the surveillance quality for a given monitoring region while activating the minimal number of active sensors. By applying the Probability Sensing Model (PSM) and considering sensing frequency, the proposed GSMS algorithm calculates the sensing probability of every location in the monitoring region and identifies the bottleneck location of surveillance quality. Then the GSMS algorithm prior schedules the sensor with the maximal contribution to the bottleneck location in terms of surveillance quality. The experimental study reveals that the proposed GSMS algorithm outperforms the existing algorithm in terms of the number of active sensors, lifetime of the WSNs, efficiency as well as the cooperative sensing probability.INDEX TERMS Wireless sensor networks, barrier coverage, probability sensing model, surveillance quality, sensing frequency.
Barrier coverage is one of the most important issues in intruder detection applications. Visual sensors can give more accurate information of intruder but also raise the problem of large data volume for information exchange and processing. Constructing a disjoint full-view barrier using minimal number of visual sensors has been the main goal for handling the barrier coverage problem. This paper presents a decentralized FBCA mechanism which consists of Region Partitioning Phase, Grid Excluding Phase, Grid Verification Phase and Full-View Barrier Construction Phase. In Region Partitioning Phase, the given R is partitioned into a set of equal-sized grids, aiming to simplify the construction problem of the full-view barrier. In Grid Excluding Phase, a certain amount of grids is removed, aiming to reduce the computational complexity. In Grid Verification Phase, each visual sensor aims to check if its neighboring grids satisfy the full-view coverage criteria. Finally, the Full-View Barrier Construction Phase aims to construct as many as possible full-view barriers. Experimental study shows that the proposed FBCA outperforms existing work SP, and likely approaches to the optimal solution (MCSPS) in terms of the average success ratio for constructing a full-view barrier.
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