Mobile Agent Routing Based on a Two-Stage Optimization Model and a Hybrid Evolutionary Algorithm in Wireless Sensor Networks

  • Shaojun Yang
  • Rui Huang
  • Haoshan Shi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4222)


A new two-stage optimization model for mobile agent routing in the wireless sensor network is presented as a integer linear programming problem based on the virtual connection topology sub graph. In the model, the solution is presented by two subpaths instead of the closed path which is usually applied in many path search methods to keep balance between computation cost and accuracy. A hybrid technique of genetic algorithm (GA) integrated with discrete particle swarm optimization (PSO), GAPSO is designed to solve the problem. Simulation experiments with different sizes and distributions of nodes show the effectiveness of the new model and GAPSO algorithm.


Sensor Network Particle Swarm Optimization Sensor Node Path Loss Mobile Agent 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Akyildiz, I., Su, W., Cayirci, E.: Wireless sensor networks: A survey. Computer Networks 38, 393–422 (2002)CrossRefGoogle Scholar
  2. 2.
    Estrin, D., Govindan, R., Heidemann, J., et al.: Next century challenges: Scalable coordination in sensor networks. In: Proc. ACM/IEEE International Conference on Mobile Computing and Networking, Seattle, Washington, USA, pp. 263–270 (1999)Google Scholar
  3. 3.
    Chong, C.Y., Kumar, S.: Sensor networks evolution, opportunities, and challenge. Proc. IEEE 91, 1247–1256 (2003)CrossRefGoogle Scholar
  4. 4.
    Tripathi, A., Ahmed, T., Pathak, S., et al: Paradigms for mobile agent based active monitoring of network systems. In: IEEE/IFIP Network Operations and Management Symposium, pp. 65–78 (2002)Google Scholar
  5. 5.
    Wang, T., Guan, S., Chan, T.: Integrity protection for code-on-demand mobile agents in e-commerce. Journal of System and Software 60, 211–221 (2002)MATHCrossRefGoogle Scholar
  6. 6.
    Qi, H., Xu, Y.: Mobile-agent-based collaborative signal and information processing in sensor networks. Proc. IEEE 91, 1172–1183 (2003)CrossRefGoogle Scholar
  7. 7.
    Qi, H., Iyengar, S., Chakrabarty, K.: Multiresolution data integration using mobile agents in distributed sensor networks. IEEE Trans. Syst., Man, Cybern. 31, 383–391 (2001)CrossRefGoogle Scholar
  8. 8.
    Migas, N., Buchanan, W.J., McAartney, K.A.: Mobile agents for routing, topology discovery, and automatic network reconfiguration in ad-hoc networks. In: Proc. 10th IEEE International Conference on Engineering of Computer-Based Systems, Huntsville, AL, USA, pp. 200–206 (2003)Google Scholar
  9. 9.
    Lu, S., Xu, C.: A formal framework for agent itinerary specification, security reasoning and logic analysis. In: Proc. 3rd International Workshop on Mobile Distributed Computing, Columbus, Ohio, USA, pp. 580–586 (2005)Google Scholar
  10. 10.
    Avramopoulos, I.C., Anagnostou, M.E.: Optimal component configuration and component routing. IEEE Trans. Mobile Comput. 1, 303–312 (2002)CrossRefGoogle Scholar
  11. 11.
    Qi, H., Wang, F.: Optimal itinerary analysis for mobile agents in ad hoc wireless sensor networks. In: Proc. 13th International Conference on Wireless Communications, Calgary, Canada, vol. 1, pp. 147–153 (2001)Google Scholar
  12. 12.
    Wang, L.P. (ed.): Soft Computing in Communications. Springer, Heidelberg (2003)Google Scholar
  13. 13.
    Selamat, A., Omatu, S.: Analysis on route selection by mobile agents using genetic algorithm. In: SICE 2003 Annual Conference, vol. 2, pp. 2088–2093 (2003)Google Scholar
  14. 14.
    Wu, Q., Rao, N.S., Barhen, J., et al.: On computing mobile agent routes for data fusion in distributed sensor networks. IEEE Trans. Knowledge Data Eng. 16, 740–753 (2004)CrossRefGoogle Scholar
  15. 15.
    Rappaport, T.: Wireless Communications Principles and Practice, 2nd edn. Publishing House of Electronics Industry, Beijing (2004)Google Scholar
  16. 16.
    Eberhan, R.C., Kennedy, J.: A new optimizer using particle swarm theory. In: Proc. 6th International Symposium on Micromachine and Human Science, Nagoya, Japan, pp. 39–43 (1995)Google Scholar
  17. 17.
    Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proc. IEEE International Conference on Neural Networks, Perth, Australia, pp. 1942–1948 (1995)Google Scholar
  18. 18.
    Shi, Y., Eberhart, R.C.: Empirical study of particle swarm optimization. In: Proc. Congress on Evolutionary Computation, Piscataway, USA, pp. 1945–1950 (1999)Google Scholar
  19. 19.
    Kennedy, J., Eberhart, R.C.: A discrete binary version of the particle swarm algorithm. In: Proc. IEEE International Conference on Systems, Man, and Cybernetics, Piscataway, New Jersey, USA, pp. 4104–4109 (1997)Google Scholar
  20. 20.
    Agrafiotis, D.K., Ceden̂o, W.: Feature selection for qsar and qspr using binary particle swarms. J. Med. Chem. 45, 1098–1107 (2002)CrossRefGoogle Scholar
  21. 21.
    Clerc, M.: Discrete particle swarm optimization illustrated by the traveling salesman problem (2000),
  22. 22.
    Yang, S., Shi, H., Huang, R.: Study of spatio-temporal information integration framework based on directed diffusion and mobile-agen for wireless sensor networks. Journal of Electronics and Information Technology 27, 1994–1999 (2005)Google Scholar
  23. 23.
    Intanagonwiwat, C., Govinda, R., Estrin, D., et al.: Directed diffusion for wireless sensor networking. IEEE/ACM Transactions on Networking 11, 2–16 (2002)CrossRefGoogle Scholar
  24. 24.
    Silva, F., Heidemann, J., Govindan, R., et al.: Directed diffusion. Technical Report ISI-TR-2004-586, USC/Information Sciences Institute (2004)Google Scholar
  25. 25.
    Yuan, P., Ji, C., Zhang, Y., et al.: Optimal multicast routing in wireless ad hoc sensor networks. In: Proc. 2004 IEEE International Conference on Networking, Sensing and Control, Taipei, Taiwan, pp. 367–371 (2004)Google Scholar
  26. 26.
    Koskinen, H.: Connectivity and reliability in ad hoc networks. Master’s thesis, Department of Electrical and Communications Engineering, Helsinki University of Technology, Helsinki, Finland (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shaojun Yang
    • 1
  • Rui Huang
    • 1
  • Haoshan Shi
    • 1
  1. 1.School of Electronics and InformationNorthwestern Polytechnical UniversityXi’anP.R. China

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