An ecologically inspired intelligent agent assisted wireless sensor network for data reconstruction

Fan Bai, Kumudu S. Munasinghe, Abbas Jamalipour

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

4 Citations (Scopus)

Abstract

One of the most important problems studied in data harvesting wireless sensor networks (WSNs) is the optimization of the tradeoff between the accuracy of the reconstructed field data and the resource consumption. In order to optimize the resource consumption, whilst not compromising the accuracy of the reconstructed field data, an ecologically inspired marginal value theorem strategy (MVTS) is proposed for a mobile agent for choosing the next sensor node to be visited in the data acquisition process. The proposed MVTS can adaptively gain new knowledge during the process of collecting observations from a WSN comprising of static sensor nodes. Therefore, only the relatively important sensor observations will be collected by the agent according to the variety of the background environmental data. This is thought as an efficient way to reserve the resources, such as energy and bandwidth, because only the important observations are collected. Illustrated analytical and simulation results confirm the above achievements.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Communications, ICC 2010
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-5
Number of pages5
ISBN (Electronic)9781424464043
ISBN (Print)9781424464029
DOIs
Publication statusPublished - 23 May 2010
Externally publishedYes
Event2010 IEEE International Conference on Communications, ICC 2010 - Cape Town, South Africa
Duration: 23 May 201027 May 2010

Conference

Conference2010 IEEE International Conference on Communications, ICC 2010
CountrySouth Africa
CityCape Town
Period23/05/1027/05/10

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  • Cite this

    Bai, F., Munasinghe, K. S., & Jamalipour, A. (2010). An ecologically inspired intelligent agent assisted wireless sensor network for data reconstruction. In 2010 IEEE International Conference on Communications, ICC 2010 (pp. 1-5). [5502289] IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICC.2010.5502289