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A 1/2 Approximation Algorithm for Energy-Constrained Geometric Coverage Problem

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Theoretical Computer Science (NCTCS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1693))

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Abstract

This paper studies the energy-constrained geometric coverage problem, which is to find an energy allocation that maximizes sensor coverage benefits while satisfying budget constraints. In this paper, we give a \(Greedy+\) algorithm with 1/2-approximation. The time complexity is \(O(m^2n^2)\). This algorithm is an improvement of the greedy algorithm. In each iteration of the greedy algorithm, the single element with the largest revenue that satisfy budget constraints is added. The solution with the largest revenue as the output of the algorithm. We show that the approximation ratio of the algorithm is tight.

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Author information

Authors and Affiliations

  1. School of Mathematics and Statistics, Yunnan University, Kunming, 650504, People’s Republic of China

    Huan Lan

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  1. Huan Lan
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Correspondence to Huan Lan .

Editor information

Editors and Affiliations

  1. National University of Defense Technology, Changsha, China

    Zhiping Cai

  2. Shanghai Jiao Tong University, Shanghai, China

    Yijia Chen

  3. Chinese Academy of Sciences, Beijing, China

    Jialin Zhang

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Lan, H. (2022). A 1/2 Approximation Algorithm for Energy-Constrained Geometric Coverage Problem. In: Cai, Z., Chen, Y., Zhang, J. (eds) Theoretical Computer Science. NCTCS 2022. Communications in Computer and Information Science, vol 1693. Springer, Singapore. https://doi.org/10.1007/978-981-19-8152-4_7

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  • DOI: https://doi.org/10.1007/978-981-19-8152-4_7

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-8151-7

  • Online ISBN: 978-981-19-8152-4

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