A critical observation collection method for sensor networks inspired by behavioral ecology

Fan Bai, Kumudu S. Munasinghe, Abbas Jamalipour

Research output: A Conference proceeding or a Chapter in BookConference contribution

2 Citations (Scopus)

Abstract

In this paper, inspirations from behavioral ecology are applied for mobile agent assisted data collection in a Wireless Sensor Networks (WSNs). With the help of the marginal value theorem based strategy (MVTS), each observation (A), which is gathered by a given sensor node, is considered as a marginal information source with a relative entropy H(A). The mobile agent exploits the correlation and chooses the next sensor node to be visited, which is deemed that the information contribution of the contained observation is not smaller than a predefined threshold (TH). Therefore, understanding the correlation models can benefit the WSNs system from two aspects. On one hand, the resource consumption could be reduced during the acquisition process of the observation; on the other hand, the accuracy of the reconstructed field data is least compromised, due to relatively critical observations being collected by the mobile agent over a dynamically changing environmental. The resource consumption such as energy and bandwidth, is proportional to the number of visited sensors. With MVTS, the resource consumption is optimized through bypassing the sensors with relatively unimportant observations. Illustrated analytical and simulation results confirm the above achievements.

Original languageEnglish
Title of host publication2010 IEEE 21st International Symposium on Personal Indoor and Mobile Radio Communications, PIMRC 2010
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1625-1630
Number of pages6
ISBN (Electronic)9781424480166
ISBN (Print)9781424480173
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event2010 IEEE 21st International Symposium on Personal Indoor and Mobile Radio Communications, PIMRC 2010 - Istanbul, Turkey
Duration: 26 Sep 201030 Sep 2010

Conference

Conference2010 IEEE 21st International Symposium on Personal Indoor and Mobile Radio Communications, PIMRC 2010
CountryTurkey
CityIstanbul
Period26/09/1030/09/10

Fingerprint

Mobile agents
Ecology
Sensor networks
Sensor nodes
Wireless sensor networks
Sensors
Entropy
Bandwidth

Cite this

Bai, F., Munasinghe, K. S., & Jamalipour, A. (2010). A critical observation collection method for sensor networks inspired by behavioral ecology. In 2010 IEEE 21st International Symposium on Personal Indoor and Mobile Radio Communications, PIMRC 2010 (pp. 1625-1630). [5671941] IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/PIMRC.2010.5671941
Bai, Fan ; Munasinghe, Kumudu S. ; Jamalipour, Abbas. / A critical observation collection method for sensor networks inspired by behavioral ecology. 2010 IEEE 21st International Symposium on Personal Indoor and Mobile Radio Communications, PIMRC 2010. IEEE, Institute of Electrical and Electronics Engineers, 2010. pp. 1625-1630
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Bai, F, Munasinghe, KS & Jamalipour, A 2010, A critical observation collection method for sensor networks inspired by behavioral ecology. in 2010 IEEE 21st International Symposium on Personal Indoor and Mobile Radio Communications, PIMRC 2010., 5671941, IEEE, Institute of Electrical and Electronics Engineers, pp. 1625-1630, 2010 IEEE 21st International Symposium on Personal Indoor and Mobile Radio Communications, PIMRC 2010, Istanbul, Turkey, 26/09/10. https://doi.org/10.1109/PIMRC.2010.5671941

A critical observation collection method for sensor networks inspired by behavioral ecology. / Bai, Fan; Munasinghe, Kumudu S.; Jamalipour, Abbas.

2010 IEEE 21st International Symposium on Personal Indoor and Mobile Radio Communications, PIMRC 2010. IEEE, Institute of Electrical and Electronics Engineers, 2010. p. 1625-1630 5671941.

Research output: A Conference proceeding or a Chapter in BookConference contribution

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N2 - In this paper, inspirations from behavioral ecology are applied for mobile agent assisted data collection in a Wireless Sensor Networks (WSNs). With the help of the marginal value theorem based strategy (MVTS), each observation (A), which is gathered by a given sensor node, is considered as a marginal information source with a relative entropy H(A). The mobile agent exploits the correlation and chooses the next sensor node to be visited, which is deemed that the information contribution of the contained observation is not smaller than a predefined threshold (TH). Therefore, understanding the correlation models can benefit the WSNs system from two aspects. On one hand, the resource consumption could be reduced during the acquisition process of the observation; on the other hand, the accuracy of the reconstructed field data is least compromised, due to relatively critical observations being collected by the mobile agent over a dynamically changing environmental. The resource consumption such as energy and bandwidth, is proportional to the number of visited sensors. With MVTS, the resource consumption is optimized through bypassing the sensors with relatively unimportant observations. Illustrated analytical and simulation results confirm the above achievements.

AB - In this paper, inspirations from behavioral ecology are applied for mobile agent assisted data collection in a Wireless Sensor Networks (WSNs). With the help of the marginal value theorem based strategy (MVTS), each observation (A), which is gathered by a given sensor node, is considered as a marginal information source with a relative entropy H(A). The mobile agent exploits the correlation and chooses the next sensor node to be visited, which is deemed that the information contribution of the contained observation is not smaller than a predefined threshold (TH). Therefore, understanding the correlation models can benefit the WSNs system from two aspects. On one hand, the resource consumption could be reduced during the acquisition process of the observation; on the other hand, the accuracy of the reconstructed field data is least compromised, due to relatively critical observations being collected by the mobile agent over a dynamically changing environmental. The resource consumption such as energy and bandwidth, is proportional to the number of visited sensors. With MVTS, the resource consumption is optimized through bypassing the sensors with relatively unimportant observations. Illustrated analytical and simulation results confirm the above achievements.

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Bai F, Munasinghe KS, Jamalipour A. A critical observation collection method for sensor networks inspired by behavioral ecology. In 2010 IEEE 21st International Symposium on Personal Indoor and Mobile Radio Communications, PIMRC 2010. IEEE, Institute of Electrical and Electronics Engineers. 2010. p. 1625-1630. 5671941 https://doi.org/10.1109/PIMRC.2010.5671941