Abstract
Barrier coverage (BC) is a potential coverage model in wireless multimedia sensor networks (WMSNs) for applications such as intrusion detection and border surveillance. This model necessitates a chain of sensors positioned across the deployment region with overlapping sensing fields. However, achieving k-strong barrier coverage following the initial random sensor deployment poses significant challenges. BC holes frequently emerge within the sensing fields, even in high-density sensor. Previous research primarily focused on addressing the problem of constructing k-strong barrier coverage under a Boolean disk or a sector coverage model. This approach leads to inaccurate assessments of barrier coverage quality. To address the limitation, this paper presents an efficient scheme for achieving k-strong barrier coverage in heterogeneous WMSNs (HeWMSNs) using the minimum number of mobile sensors, while employing a probabilistic sector coverage model. By leveraging the proposed probabilistic sector sensing coverage model, we formulate the problem of attaining k-strong barrier coverage in HeWMSNs as a combinatorial optimization problem called KSB-HeWMSN. Subsequently, an efficient evolutionary algorithm is developed to tackle this problem. Through both analytical analysis and experimental evaluations conducted on multiple instances, the proposed algorithm demonstrates its suitability for the KSB-HeWMSN problem and its superior solution quality compared to previous approaches.
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Acknowledgement
This research is funded by Hanoi University of Industry under grant number \(25 -2022-RD/HD-DHCN\) for Nguyen Thi My Binh.
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Binh, N.T.M., Thien, N.V., Luong, H.V.D., Ngoc, D.T. (2024). An Efficient Approach to the k-Strong Barrier Coverage Problem Under the Probabilistic Sensing Model in Wireless Multimedia Sensor Networks. In: Thi Dieu Linh, N., Hoang, M.K., Dang, T.H. (eds) Ad Hoc Networks. ADHOCNETS 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 558. Springer, Cham. https://doi.org/10.1007/978-3-031-55993-8_13
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