A novel adaptive deployment method for the single-target tracking of mobile wireless sensor networks

Shihu Xiang and Jun Yang

Reliability Engineering and System Safety, 2023, vol. 234, issue C

Abstract: Single-target tracking is an important application of mobile wireless sensor networks. It is imperative to adaptively adjust the network deployment to achieve a satisfactory comprehensive tracking performance incorporating reliability, energy efficiency, connectivity, and tracking accuracy, which are all significant aspects for target tracking. However, the existing methods cannot ensure the optimization of the comprehensive tracking performance. Moreover, they are inapplicable to the realistic scenario with the common uncertainties, including the randomness of sensing, the randomness of received signal power, and the correlation between received signal powers. To solve these problems, a network model is proposed by modeling the common uncertainties to properly capture the characteristics of sensing and wireless communication. The reliability-energy index is defined to assess the comprehensive tracking performance. Furthermore, an adaptive deployment method is proposed to dynamically optimize the comprehensive tracking performance. Especially, to determine the optimal deployment at a sensing instant, an optimization algorithm is proposed by analyzing the monotonicity of the reliability-energy index and the impact of the positional relationship of nodes. Finally, a scenario of habitat monitoring is considered, and simulations are conducted to compare the proposed method with the existing methods to demonstrate the effectiveness of the proposed method.

Keywords: Mobile wireless sensor network; Single-target tracking; Adaptive deployment method; Comprehensive tracking performance; Realistic network model; Reliability-energy index (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:234:y:2023:i:c:s0951832023000509

DOI: 10.1016/j.ress.2023.109135

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