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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

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.

Xuất bản trên:

Expert Systems With Applications


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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