Abstract
Intrusion detection is an important application of wireless sensor network. A belt region is said to be k-barrier covered if any intruder crossing the width of this region can be detected by at least k sensors. After initial random sensor deployment, k-barrier coverage can be achieved by relocating mobile sensors to construct k barriers appropriately. Due to energy limit of mobile sensors, it is important to reduce the amount of movements of mobile sensors. Existing algorithms focused on forming k linear barriers energy-efficiently. However, large redundant sensor movement are needed by mobile sensors to move to linear barriers. In this paper, we will study how to form k non-linear barriers energy-efficiently, which can result smaller sensor movement than linear barriers. We define a notion of horizontal virtual force by considering the euclidean distance and also horizontal angle and then propose an energy-efficient algorithm to form k non-linear barriers based on the initial deployment of mobile sensors. The algorithm first divides the region into several subregions and then constructs k sub-barriers from the left boundary of each subregion to the right boundary respectively by always choosing the mobile sensor chain with the largest horizontal virtual force and also flattening it and finally connects the sub-barriers in neighbor subregions for forming k barriers in the whole region. Simulation results show that this algorithm efficiently decreases the movements of mobile sensors compared to a linear k-barrier coverage algorithm and it can be applicable to large scale sensor networks.
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Acknowledgment
This work is supported by National Natural Science Foundation of China (Grant No. 61702198 and 61772005). The corresponding author is Shuangjuan Li.
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Ma, Z., Li, S., Guo, L., Wang, G. (2020). Non-linear K-Barrier Coverage in Mobile Sensor Network. In: Shen, H., Sang, Y. (eds) Parallel Architectures, Algorithms and Programming. PAAP 2019. Communications in Computer and Information Science, vol 1163. Springer, Singapore. https://doi.org/10.1007/978-981-15-2767-8_2
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DOI: https://doi.org/10.1007/978-981-15-2767-8_2
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