Skip to main content

Advertisement

SpringerLink
Log in

A Genetic Algorithm Approach to Multi-Agent Itinerary Planning in Wireless Sensor Networks

  • Published:
Mobile Networks and Applications Aims and scope Submit manuscript

Abstract

It has been shown recently that using Mobile Agents (MAs) in wireless sensor networks (WSNs) can help to achieve the flexibility of over-the-air software deployment on demand. In MA-based WSNs, it is crucial to find out an optimal itinerary for an MA to perform data collection from multiple distributed sensors. However, using a single MA brings up the shortcomings such as large latency, inefficient route, and unbalanced resource (e.g. energy) consumption. Then a novel genetic algorithm based multi-agent itinerary planning (GA-MIP) scheme is proposed to address these drawbacks. The extensive simulation experiments show that GA-MIP performs better than the prior single agent algorithms in terms of the product of delay and energy consumption.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Notes

  1. Even if they do not have the same length segment currently, Source-Grouping-Codes are changed by the mutation process at each iteration, to be detailed later. Thus, they will have the same length segment at some later iteration.

  2. OPNET, http://www.opnet.com/.

References

  1. Romer K, Mattern F (2004) The design space of wireless sensor networks. IEEE Wirel Commun 11(6):14–21

    Article  Google Scholar 

  2. Tong L, Zhao Q, Adireddy S (2003) Sensor networks with mobile agents. In: Proceedings of the 2003 IEEE international conference on military communications (MILCOM 2003). Boston, Massachusetts

  3. Beigl M, Krohn A, Zimmer T, Decker C, Robinson P (2003) AwareCon: situation aware context communication. In: Proceedings of the 5th IEEE international conference on ubiquitous computing (UbiComp 2003). Seattle, Washington, pp 132–139

  4. Chen M, Gonzalez S, Leung V (2007) Applications and design issues for mobile agents in wireless sensor networks. Wirel Commun IEEE 14(6):20–26

    Article  Google Scholar 

  5. Chen M, Kwon T, Yuan Y, Leung VC (2006) Mobile agent based wireless sensor networks. Journal of Computers 1(1):14–21

    Article  Google Scholar 

  6. Chen M, Kwon T, Yuan Y, Choi Y, Leung VCM (2007) Mobile agent-based directed diffusion in wireless sensor networks. EURASIP J Appl Signal Process 2007(1):219–219

    Google Scholar 

  7. Qi H, Wang F (2001) Optimal itinerary analysis for mobile agents in ad hoc wireless sensor networks. In: Proceedings of the IEEE 2001 international conference on communications (ICC 2001). Helsinki, Finland

  8. 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 2009 international conference on communications (ICC 2009). Bresden, Germany, pp 1–5

  9. Wu Q, Rao NSV, Barhen J, Iyengar SS, Vaishnavi VK, Qi H, Chakrabarty K, Member S, Member S (2004) On computing mobile agent routes for data fusion in distributed sensor networks. IEEE Trans Knowl Data Eng 16:740–753

    Article  Google Scholar 

  10. Chen M, Gonzlez S, Zhang Y, Leung VC (2009) Multi-agent itinerary planning for sensor networks. In: Proceedings of the IEEE 2009 international conference on heterogeneous networking for quality, reliability, security and robustness (QShine 2009). Las Palmas de Gran Canaria, Spain

  11. Szewczyk R, Mainwaring A, Polastre J, Anderson J, Culler D (2004) An analysis of a large scale habitat monitoring application. In: Proceedings of the ACM 2004 2nd international conference on embedded networked sensor systems (SenSys 2004). Boston, MA, pp 214–226

  12. Mitchell M (1998) An introduction to genetic algorithms. MIT

  13. Poli R, Langdon WB (1998) Schema theory for genetic programming with One-Point crossover and point mutation. Evol Comput 6(3):231–252

    Article  Google Scholar 

  14. Jong KAD, Spears WM (1992) A formal analysis of the role of multi-point crossover in genetic algorithms. Ann Math Artif Intell 5(1):1–26

    Article  MATH  Google Scholar 

  15. Zhao Y, Wang Q, Jiang D, Wu W, Hao L, Wang K (2008) An agent-based routing protocol with mobile sink for wsn in coal mine. In: Proceedings of the 3rd international conference on pervasive computing and applications (ICPCA 2008). Alexandria, Egypt

  16. Cheng L, Chen C, Ma J, Shu L, Chen H, Yang LT (2009) Residual time aware forwarding for randomly duty-cycled wireless sensor networks. In: Proceedings of the 7th IEEE/IFIP international conference on embedded and ubiqutious computing (EUC 2009). Vancouver, Canada

Download references

Acknowledgements

This work was supported by the IT R&D program of MKE/KEIT. [KI001862, MKE/KEIT], and was partially supported by Grant-in-Aid for Scientific Research (S)(21220002) of the Ministry of Education, Culture, Sports, Science and Technology, Japan.

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Seoul National University, Seoul, Korea

    Wei Cai, Min Chen & Taekyoung Kwon

  2. Department of Multimedia Engineering, Osaka University, Osaka, Japan

    Takahiro Hara & Lei Shu

Authors
  1. Wei Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Min Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Takahiro Hara
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lei Shu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Taekyoung Kwon
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Taekyoung Kwon.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cai, W., Chen, M., Hara, T. et al. A Genetic Algorithm Approach to Multi-Agent Itinerary Planning in Wireless Sensor Networks. Mobile Netw Appl 16, 782–793 (2011). https://doi.org/10.1007/s11036-010-0269-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11036-010-0269-z

Keywords

Search

Navigation