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Optimal Online and Offline Algorithms for Robot-Assisted Restoration of Barrier Coverage

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Approximation and Online Algorithms (WAOA 2014)

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Abstract

Cooperation between mobile robots and wireless sensor networks is a line of research that is currently attracting a lot of attention. In this context, we study the following problem of barrier coverage by stationary wireless sensors that are assisted by a mobile robot with the capacity to move sensors. Assume that \(n\) sensors are initially arbitrarily distributed on a line segment barrier. Each sensor is said to cover the portion of the barrier that intersects with its sensing area. Owing to incorrect initial position, or the death of some of the sensors, the barrier is not completely covered by the sensors. We employ a mobile robot to move the sensors to final positions on the barrier such that barrier coverage is guaranteed. We seek algorithms that minimize the length of the robot’s trajectory, since this allows the restoration of barrier coverage as soon as possible. We give an optimal linear-time offline algorithm that gives a minimum-length trajectory for a robot that starts at one end of the barrier and achieves the restoration of barrier coverage. We also study two different online models: one in which the online robot does not know the length of the barrier in advance, and the other in which the online robot knows it in advance. For the case when the online robot does not know the length of the barrier, we prove a tight bound of \(3/2\) on the competitive ratio, and we give a tight lower bound of \(5/4\) on the competitive ratio in the other case. Thus for each case we give an optimal online algorithm.

This work was partially supported by NSERC grants.

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Correspondence to E. Kranakis .

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Czyzowicz, J., Kranakis, E., Krizanc, D., Narayanan, L., Opatrny, J. (2015). Optimal Online and Offline Algorithms for Robot-Assisted Restoration of Barrier Coverage. In: Bampis, E., Svensson, O. (eds) Approximation and Online Algorithms. WAOA 2014. Lecture Notes in Computer Science(), vol 8952. Springer, Cham. https://doi.org/10.1007/978-3-319-18263-6_11

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  • DOI: https://doi.org/10.1007/978-3-319-18263-6_11

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