Research Article

Distribution of mobile agents in vulnerable networks

  1. Wenyu Qu1,*,
  2. Masaru Kitsuregawa1,
  3. Hong Shen2,
  4. Yingwei Jin3

Article first published online: 28 SEP 2006

DOI: 10.1002/cpe.1095

Issue

Concurrency and Computation: Practice and Experience

Concurrency and Computation: Practice and Experience

Special Issue: Autonomous Grid Computing

Volume 19, Issue 7, pages 1047–1064, May 2007

Additional Information

How to Cite

Qu, W., Kitsuregawa, M., Shen, H. and Jin, Y. (2007), Distribution of mobile agents in vulnerable networks. Concurrency Computat.: Pract. Exper., 19: 1047–1064. doi: 10.1002/cpe.1095

Author Information

  1. 1

    Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan

  2. 2

    Graduate School of Information Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Tatsunokuchi, Ishikawa 923-1292, Japan

  3. 3

    Department of Computer Science and Engineering, Dalian University of Technology, 2 Linggong Road, Ganjingzi District, Dalian 116024, People's Republic of China

*Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba Meguro-ku, Tokyo 153-8505, Japan

Publication History

  1. Issue published online: 26 MAR 2007
  2. Article first published online: 28 SEP 2006
  3. Manuscript Accepted: 5 MAY 2006
  4. Manuscript Received: 26 APR 2006

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Keywords:

  • routing;
  • mobile agents;
  • distribution;
  • Markov process

Abstract

Advances in the Internet and the computer industry have created many new application areas for network routing such as Grid computing and also brings new challenges to traditional routing techniques. In this paper we propose a mobile agent-based routing model in vulnerable networks for these applications. To characterize the behaviors of mobile agents and their effects on the network performance, we analyze the population distribution of mobile agents as a measurement of the computational resource consumption. Our analysis reveals theoretical insights into the statistical behaviors of mobile agents and provides useful tools for effectively managing mobile agents in large networks. Copyright © 2006 John Wiley & Sons, Ltd.

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