Dynamic cooperative co-evolutionary automated mobile sensor deployment via localized fitness evaluation
Thesis (M.Sc.)--Memorial University of Newfoundland, 2008. Computer Science Includes bibliographical references (leaves 72-78) A wireless sensor network is a self-organized network consisting of a large number of small sensor nodes distributed over an area of interests. Such networks are capable of...
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ftmemorialunivdc:oai:collections.mun.ca:theses4/53854 2023-05-15T17:23:33+02:00 Dynamic cooperative co-evolutionary automated mobile sensor deployment via localized fitness evaluation Jiang, Xingyan. Memorial University of Newfoundland. Dept. of Computer Science 2008 x, 80 leaves : ill. Image/jpeg; Application/pdf http://collections.mun.ca/cdm/ref/collection/theses4/id/53854 Eng eng Electronic Theses and Dissertations (8.08 MB) -- http://collections.mun.ca/PDFs/theses/Jiang_Xingyan.pdf a2696174 http://collections.mun.ca/cdm/ref/collection/theses4/id/53854 The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission. Paper copy kept in the Centre for Newfoundland Studies, Memorial University Libraries Evolutionary computation Wireless sensor networks Text Electronic thesis or dissertation 2008 ftmemorialunivdc 2015-08-06T19:22:02Z Thesis (M.Sc.)--Memorial University of Newfoundland, 2008. Computer Science Includes bibliographical references (leaves 72-78) A wireless sensor network is a self-organized network consisting of a large number of small sensor nodes distributed over an area of interests. Such networks are capable of observing and sensing the environment, and sending the collected data to a data sink for further processing. Sensors must be deployed before they can provide useful data. Therefore the deployment of static or mobile sensors is an important basis for sensor networking. -- Automated mobile sensor deployment of a wireless sensor network has a significant impact on the network performance, such as network sensing coverage, communication or mobile costs, and connectivity. Due to the small size of sensors, they are equipped with small batteries and have low-power computing and communication resources. The lifetime of a sensor is determined by its battery life and it cannot operate for an infinite amount of time. Therefore, a good deployment yields a high utilization of power resources. -- In this thesis, we propose an innovative cooperative co-evolutionary computation framework, Localized Distributed Coevolution (LODICO), to optimize the automated sensor deployment with arbitrary initial positions. LODICO is a fully distributed and localized algorithm. It can be executed on all sensors of the network in parallel. Meanwhile the information exchange has to be done locally as each sensor can only communicate with those within a distance. Further, we extend LODICO to LODICO/D to provide dynamic interaction to neighboring computing agents during the evolutionary process. It models the potential local interactions between computing agents, and uses the imaginary neighboring movements to improve its local fitness and to help escaping from local optima. -- This thesis is a powerful extension work to the traditional Cooperative Revolutionary Algorithm. One feature of it is the utilization of local fitness to achieve a global optimum, which makes co-evolutionary algorithms applicable to localized distributed environments, such as network computing. Another salient feature is that the proposed algorithms can adjust and adapt the frequent dynamic change of network structures due to the position changes or failures of computing agents. LODICO/D incorporates LODICO with mode D to help to escape local optima. Mode D creates the third feature of imaginary collaboration with the neighboring computing agents during the evolutionary process to improve its local fitness. Our experiments show that LODICO and LODICO/D are effective in obtaining good solutions under such dynamic, distributed, and localized condition constraints. Thesis Newfoundland studies University of Newfoundland Memorial University of Newfoundland: Digital Archives Initiative (DAI) |
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Memorial University of Newfoundland: Digital Archives Initiative (DAI) |
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English |
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Evolutionary computation Wireless sensor networks |
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Evolutionary computation Wireless sensor networks Jiang, Xingyan. Dynamic cooperative co-evolutionary automated mobile sensor deployment via localized fitness evaluation |
topic_facet |
Evolutionary computation Wireless sensor networks |
description |
Thesis (M.Sc.)--Memorial University of Newfoundland, 2008. Computer Science Includes bibliographical references (leaves 72-78) A wireless sensor network is a self-organized network consisting of a large number of small sensor nodes distributed over an area of interests. Such networks are capable of observing and sensing the environment, and sending the collected data to a data sink for further processing. Sensors must be deployed before they can provide useful data. Therefore the deployment of static or mobile sensors is an important basis for sensor networking. -- Automated mobile sensor deployment of a wireless sensor network has a significant impact on the network performance, such as network sensing coverage, communication or mobile costs, and connectivity. Due to the small size of sensors, they are equipped with small batteries and have low-power computing and communication resources. The lifetime of a sensor is determined by its battery life and it cannot operate for an infinite amount of time. Therefore, a good deployment yields a high utilization of power resources. -- In this thesis, we propose an innovative cooperative co-evolutionary computation framework, Localized Distributed Coevolution (LODICO), to optimize the automated sensor deployment with arbitrary initial positions. LODICO is a fully distributed and localized algorithm. It can be executed on all sensors of the network in parallel. Meanwhile the information exchange has to be done locally as each sensor can only communicate with those within a distance. Further, we extend LODICO to LODICO/D to provide dynamic interaction to neighboring computing agents during the evolutionary process. It models the potential local interactions between computing agents, and uses the imaginary neighboring movements to improve its local fitness and to help escaping from local optima. -- This thesis is a powerful extension work to the traditional Cooperative Revolutionary Algorithm. One feature of it is the utilization of local fitness to achieve a global optimum, which makes co-evolutionary algorithms applicable to localized distributed environments, such as network computing. Another salient feature is that the proposed algorithms can adjust and adapt the frequent dynamic change of network structures due to the position changes or failures of computing agents. LODICO/D incorporates LODICO with mode D to help to escape local optima. Mode D creates the third feature of imaginary collaboration with the neighboring computing agents during the evolutionary process to improve its local fitness. Our experiments show that LODICO and LODICO/D are effective in obtaining good solutions under such dynamic, distributed, and localized condition constraints. |
author2 |
Memorial University of Newfoundland. Dept. of Computer Science |
format |
Thesis |
author |
Jiang, Xingyan. |
author_facet |
Jiang, Xingyan. |
author_sort |
Jiang, Xingyan. |
title |
Dynamic cooperative co-evolutionary automated mobile sensor deployment via localized fitness evaluation |
title_short |
Dynamic cooperative co-evolutionary automated mobile sensor deployment via localized fitness evaluation |
title_full |
Dynamic cooperative co-evolutionary automated mobile sensor deployment via localized fitness evaluation |
title_fullStr |
Dynamic cooperative co-evolutionary automated mobile sensor deployment via localized fitness evaluation |
title_full_unstemmed |
Dynamic cooperative co-evolutionary automated mobile sensor deployment via localized fitness evaluation |
title_sort |
dynamic cooperative co-evolutionary automated mobile sensor deployment via localized fitness evaluation |
publishDate |
2008 |
url |
http://collections.mun.ca/cdm/ref/collection/theses4/id/53854 |
genre |
Newfoundland studies University of Newfoundland |
genre_facet |
Newfoundland studies University of Newfoundland |
op_source |
Paper copy kept in the Centre for Newfoundland Studies, Memorial University Libraries |
op_relation |
Electronic Theses and Dissertations (8.08 MB) -- http://collections.mun.ca/PDFs/theses/Jiang_Xingyan.pdf a2696174 http://collections.mun.ca/cdm/ref/collection/theses4/id/53854 |
op_rights |
The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission. |
_version_ |
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