A concise and factual abstract is required. The abstract should state Target coverage and lifetime maximization problems are major challenges for mobile wireless sensor networks (MWSN). In this paper, we propose a Multi-Objective formulation for MaxiMizing lifetime with Target Coverage called MO-MMTC, which accounts for the energy fluctuation among mobile sensors after each movement. We prove the formulation to be NP-hard and propose the Enhanced Non-dominated Sorting Genetic Algorithm II (ENSGA-II), a multi-population genetic algorithm, to solve this problem. Experiments are performed to compare ENSGA-II with TV-Greedy, an existing state-of-the-art heuristic for MMTC. Our results show that the proposed algorithm significantly improves many evaluation metrics compared to baseline methods.
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A bi-population Genetic algorithm based on multi-objective optimization for a relocation scheme with target coverage constraints in mobile wireless sensor networks
A bi-population Genetic algorithm based on multi-objective optimization for a relocation scheme with target coverage constraints in mobile wireless sensor networks
La Văn Quân, Nguyễn Thị Hạnh, Huỳnh Thị Thanh Bình, Vũ Đức Toàn, Bùi Thu Lâm, Đặng Thế Ngọc
Xuất bản trên:
Ngày đăng:
2023
Nhà xuất bản:
Elsevier
Địa điểm:
Từ khoá:
Bi-population, Genetic algorithm Target coverage, Mobile wireless sensor network, NSGA-II, Multi-objective
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