Sterle, Claudio, Sforza, Antonio, Esposito Amideo, Annunziata, Piccolo, Carmela (2016) A unified solving approach for two and three dimensional coverage problems in sensor networks. Optimization Letters, 10 (5). pp. 1101-1123. ISSN 1862-4472. (doi:10.1007/s11590-016-1014-8) (KAR id:69978)
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Official URL: http://dx.doi.org/10.1007/s11590-016-1014-8 |
Abstract
The problem of designing a wired or a wireless sensor network to cover, monitor and/or control a region of interest has been widely treated in literature. This problem is referred to in literature as the sensor placement problem (SPP) and in the most general case it consists in determining the number and the location of one or more kind of sensors with the aim of covering all the region of interest or a significant part of it. In this paper we propose a unified and stepwise solving approach for two and three dimensional coverage problems to be used in omni-directional and directional sensor networks. The proposed approach is based on schematizing the region of interest and the sensor potential locations by a grid of points and representing the sensor coverage area by a circle or by a circular sector. On this basis, the SPP is reduced to an optimal coverage problem and can be formulated by integer linear programming (ILP) models. We will resume the main ILP models used in our approach, highlighting, for each of them, the specific target to be achieved and the design constraints taken into account. The paper concludes with an application of the proposed approach to a real test case and a discussion of the obtained results.
Item Type: | Article |
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DOI/Identification number: | 10.1007/s11590-016-1014-8 |
Uncontrolled keywords: | Camera placement Sensor network Sensor placement Two and three dimensional coverage |
Subjects: | H Social Sciences |
Divisions: | Divisions > Kent Business School - Division > Kent Business School (do not use) |
Depositing User: | Annunziata Esposito Amideo |
Date Deposited: | 07 Nov 2018 12:24 UTC |
Last Modified: | 05 Nov 2024 12:32 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/69978 (The current URI for this page, for reference purposes) |
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