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Performance Evaluation of Personal Agent Migration Policies in an Ambient Use Case Scenario

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3295))

Abstract

This paper investigates the impact of agent migration on the performance of personal agents in an ambient use case scenario. Four migration policies are proposed and a performance model, based on two quantitative performance metrics, network load and response time for processing the user request, is applied to compare the performance of the proposed migration policies. Scenario mapping to performance model and analytical results are also discussed in this paper. An agent emulator is designed and implemented in the Java programming language based on the Jatlite agent framework. The emulator is used to produce the experimental results of this study. It has been shown that, in this scenario, the policy in which a user agent follows the mobile user in the wired side of wireless network lowers the response time when the agent size is smaller than the reply size. However, when the reply size is smaller than the agent size, a simple stay-at-home policy outperforms the other three policies.

The work reported in this paper has formed part of the Software Based Systems area of the Core 2 Research Programme of the Virtual Centre of Excellence in Mobile & Personal Communications, Mobile VCE, (www.mobilevce.co.uk) whose funding support is gratefully acknowledged. More detailed technical reports on this research are available to Industrial Members of Mobile VCE.

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© 2004 Springer-Verlag Berlin Heidelberg

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Homayounvala, E., Aghvami, A.H. (2004). Performance Evaluation of Personal Agent Migration Policies in an Ambient Use Case Scenario. In: Markopoulos, P., Eggen, B., Aarts, E., Crowley, J.L. (eds) Ambient Intelligence. EUSAI 2004. Lecture Notes in Computer Science, vol 3295. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30473-9_3

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  • DOI: https://doi.org/10.1007/978-3-540-30473-9_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23721-1

  • Online ISBN: 978-3-540-30473-9

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