Wireless Personal Communications

, Volume 89, Issue 4, pp 1165–1176 | Cite as

Energy Efficient Data Aggregation in Mobile Agent Based Wireless Sensor Network

  • Divya Lohani
  • Shirshu Varma


Energy efficiency have always been a priority while designing wireless sensor networks. Introduction of mobile agent technology in wireless sensor networks for collaborative signal and information processing has provided the new scope for efficient processing and aggregation of data. Mobile agent based distributed computing paradigm offers numerous benefits over the existing and commonly used client/server computing paradigm in wireless sensor networks. Mobile agent performs the task of data processing and data aggregation at the node level rather than at the sink, thus, eliminating the redundant network overhead. One of the most important issues in mobile agent based paradigm is planning of an itinerary for agent traversal. In this paper, we have proposed a dynamic mobile agent based data aggregation approach that takes into consideration energy efficiency, network lifetime, end to end delay and aggregation ration while making the decision for migration of agent in multihop sensor network. As our approach focuses on finding the most informative route by traversing comparatively less number of nodes consequently mobile agent takes less time to return to processing element, thus, exhibiting lower delay.


Wireless sensor networks Distributed computing paradigm Collaborative information processing Client server Mobile agent Itinerary planning 


  1. 1.
    Akyildiz, I. F., Su, W., Subramaniam, Y., & Cayirci, E. (2002). A survey on sensor networks. IEEE Communications Magazine, 40(8), 104–112.CrossRefGoogle Scholar
  2. 2.
    Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Elsevier Computer Networks, 52, 2292–2330.CrossRefGoogle Scholar
  3. 3.
    Qi, H., Iyengar, S., & Chakrabarty, K. (2001). Distributed sensor networks—A review of recent research. Journal of the Franklin Institute, 338, 655–668.CrossRefzbMATHGoogle Scholar
  4. 4.
    Zhao, F., Shin, J., & Reich, J. (2002). Information-driven dynamic sensor collaboration. IEEE Signal Processing Magazine, 19(2), 61–72.CrossRefGoogle Scholar
  5. 5.
    Xu, Y., Qi, H., & Kuruganti, P. T. (2003). Distributed computing paradigm for collaborative processing in sensor networks. In IEEE GlobeCom (pp. 3531–3535).Google Scholar
  6. 6.
    Xu, Y., & Qi, H. (2004). Distributed computing paradigm for collaborative signal and information processing in sensor networks. Journal of Parallel and Distributed Computing, 64(8), 945–959.CrossRefzbMATHGoogle Scholar
  7. 7.
    Qi, H., Xu, Y., & Wang, X. (2003). Mobile-agent-based collaborative signal and information processing in sensor networks. Proceedings of the IEEE, 91(8), 1172–1183.CrossRefGoogle Scholar
  8. 8.
    Chen, M., Kwon, T., Yuan, Y., & Leung, V. C. M. (2006). Mobile agent based wireless sensor networks. Journal of Computers, 1, 6–10.Google Scholar
  9. 9.
    Xu, Y., & Qi, H. (2008). Mobile agent migration modelling and design for target tracking in wireless sensor networks. Ad Hoc networks Journal, 6(1), 1–16.MathSciNetCrossRefGoogle Scholar
  10. 10.
    Biswas, P. K., Qi, H., & Xu, Y. (2008). Mobile agent based collaborative sensor fusion. Information Fusion Journal, 9(3), 399–411.CrossRefGoogle Scholar
  11. 11.
    Chen, M., Gonzalez, S., & Leung, V. C. (2007). Applications and design issues of mobile agents in wireless sensor networks. IEEE Wireless Communications Magazine (Special Issue on Wireless Sensor Networking), 14(6), 20–26.CrossRefGoogle Scholar
  12. 12.
    Qi, H., & Wang, F. (2001). Optimal itinerary analysis for mobile agents in adhoc wireless sensor networks. In Proceedings of the IEEE international conference on communications (ICC), Helsinki, Finland.Google Scholar
  13. 13.
    Chen, M., Kwon, T., Yuan, Y., Choi Y., & Leung, V. C. (2007). Mobile agent-based directed diffusion in wireless sensor networks. EURASIP Journal on Advances in Signal Processing, 2007(1), 219.Google Scholar
  14. 14.
    Wu, Q., Rao, N. S. V., Barhen, J., Sitharama Iyengar, S., Vaishnavi, V. K., Qi, H., & Chakrabarty, K. (2004). On computing mobile agent routes for data fusion in distributed sensor networks. IEEE Transactions on Knowledge and Data Engineering, 16(6), 740–753.CrossRefGoogle Scholar
  15. 15.
    Chen, M., Leung, V., Mao, S., Kwon, T., & Li, M. (2009). Energy-efficient itinerary planning for mobile agents in wireless sensor networks. In Proceedings of the IEEE international conference on communications (ICC), Bresden, Germany (pp. 1–5).Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Indian Institute of Information Technology, AllahabadAllahabadIndia

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