A co-evolutionary sensor deployment algorithm for full-coverage problems with space constraints = 공간 제약이 있는 완전-커버리지 문제를 풀기 위한 공진화적 센서 배치 알고리즘

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dc.contributor.advisorLee, Ju-Jang-
dc.contributor.advisor이주장-
dc.contributor.authorSeok, Joon-Hong-
dc.contributor.author석준홍-
dc.date.accessioned2015-04-23T06:12:43Z-
dc.date.available2015-04-23T06:12:43Z-
dc.date.issued2014-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=568596&flag=dissertation-
dc.identifier.urihttp://hdl.handle.net/10203/196560-
dc.description학위논문(박사) - 한국과학기술원 : 전기및전자공학과, 2014.2, [ x, 104 p. ]-
dc.description.abstractA coverage problem is one of the fundamental problems in wireless sensor networks, robotics, and various application fields. Coverage can be considered as a measure of the quality of services, thus a coverage problem becomes one of the fundamental problems for the composition of the sensor network. Each sensor may have own influence range to cover the region and various sensors has been used and deployed to keep and monitor a target region. Proper sensor deployment is required to perform surveillance and monitoring tasks successfully, since a single sensor by itself has resource constraints and the sensor can cover only a small part of the region of interest. The importance of sensor deployment strategies for the coverage in the target region cannot be overemphasized. First, Minimum Sensor Full-coverage Problems (MSFPs) with space constraints using various sensors are defined. Some given target region which has non-penetrable space constraints should be covered by a set of sensors. While maintaining the full-coverage state, the number of sensors or the cost of sensor network is also minimized. For this purpose, a map representation, a sensor representation, objective functions and coverage evaluation conditions are defined to represent the MSFPs in detail. The main characteristics of the problem are to deal with area coverage, non-penetrable obstacles. MSFPs are a NP-hard problem, so the metaheuristic methods are utilized to solve the problem with less computational cost. To solve the full-coverage problem intuitively, we decompose the MSFPs into two subproblems. One is a coverage increment problem and the other is a one-sensor reduction problem to solve the whole MSFPs efficiently. After then, we focus on co-evolutionary sensor deployment algorithm (ESDA) to acquire a full-coverage state with minimum number of sensors in the predetermined target region including non-penetrable obstacles. Variable-length chromosome representations include only feasible s...eng
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectSensor deployment-
dc.subject공간 제약-
dc.subject커버리지 문제-
dc.subject진화적 센서 배치 알고리즘-
dc.subject센서 배치-
dc.subjectSpace constaints-
dc.subjectEvolutionary sensor deployment algorithm-
dc.subjectFull-coverage problem-
dc.titleA co-evolutionary sensor deployment algorithm for full-coverage problems with space constraints = 공간 제약이 있는 완전-커버리지 문제를 풀기 위한 공진화적 센서 배치 알고리즘-
dc.typeThesis(Ph.D)-
dc.identifier.CNRN568596/325007 -
dc.description.department한국과학기술원 : 전기및전자공학과, -
dc.identifier.uid020107044-
dc.contributor.localauthorLee, Ju-Jang-
dc.contributor.localauthor이주장-
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