Skip to main content
SpringerLink
Log in

Autonomous network-based integration architecture for multi-agent systems under dynamic and heterogeneous environment

  • Published:
Automatic Control and Computer Sciences Aims and scope Submit manuscript

Abstract

Multi-agent systems fit nicely into domains that are naturally distributed and require artificial intelligence technology. Has been designed an autonomous information services integration architecture based on network to support the rapid changing environments and needs. However, substantial increase of users requests and redirects it may cause the system to unbalance loading and part overloading. This paper proposes an integrated access method by reduces the number of Pull Mobile Agents to reduces the total load of the system in order to achieveautonomous load distribution. In addition, the information structure of integrated service area is effective to improve the ratio of the satisfaction of Pull-Mas (Pull Mobile Agents) with joint request on one node. Through simulation tests show that this system can be guaranteed that services requests and related services requests is uniformly distributed to the nodes of system and ensure that the system load balancing.

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

Similar content being viewed by others

References

  1. Mori, K., Autonomous fading and navigation for information allocation and search under evolving service system, Proc. IEEE Conf. on APSITT, 1999, pp. 326–330.

    Google Scholar 

  2. Ahmad, H.F. and Mori, K., Autonomous information provision to achieve reliability for users and providers, Proc. IEEE Conf. onISADS, 2001, pp. 65–72.

    Google Scholar 

  3. OMG, The common object request broker: Architecture and specification. http://www.omg.org/corba/.

  4. UDDI.ORG, UDDI technical white paper. http://www.uddi.org/.

  5. Sakaida, N., Takahashi, H., T., Yoshida, M., and Hibi, T., SDN software switch lagopus and NFV service orchestrator vConductor for developing SDN/NFV.NTT, Tech. Rev., 2006, vol. 14, no. 3.

    Google Scholar 

  6. Tao Zhao, Tao Li, Biao Han, Zhigang Sun, and Jinfeng Huang, Design and implementation of software defined hardware counters for SDN, Comput. Networks, 2016, vol. 102, pp. 129–144.

    Article  Google Scholar 

  7. Boukaye Boubacar Traore, Bernard Kamsu-Foguem, and Fana Tangara, Integrating MDA and SOA for improving telemedicine services, Telematics Inf., 2016, vol. 33, no. 3, pp. 733–741.

    Article  Google Scholar 

  8. Ponnalagu, K., Narendra, N.C., and Gangadharan, G.R., Integrated asset analysis framework for model-driven development of SOA based solutions, Lect. Notes Comput. Sci., 2012, vol. 7221, pp. 257–269.

    Article  Google Scholar 

  9. Ran, Ch.-Sh. and Li, N., Design and implementation of communication model based on Silverlight and WCF in EAM system, Proceedings–2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010, 2010, pp. 590–593.

    Chapter  Google Scholar 

  10. He, J., Geng, Y., and Pahlavan, K., Modeling indoor TOA ranging error for body mounted sensors, 2012 IEEE 23nd International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC), Sydney, 2012, pp. 682–686.

    Chapter  Google Scholar 

  11. Li, S., Geng, Y., He, J., and Pahlavan, K., Analysis of three-dimensional maximum likelihood algorithm for capsule endoscopy localization, 2012 5th International Conference on Biomedical Engineering and Informatics (BMEI), Chongqing, 2012, pp. 721–725.

    Chapter  Google Scholar 

  12. Huhns, M., Jacobs, N., Ksiezyk, T., Shen, W.M., Singh, M., and Canata, P., Enterprise information modeling and model integration in carnot, Proc. Enterprise Integration Modeling, 1992, pp. 290–299.

    Google Scholar 

  13. Etzioni, O., Golden, K., and Weld, D., Sound and efficient closeworld reasoning for planning, J. Artif. Intell., 1997, vol. 89, nos. 1—2, pp. 113–148.

    Article  MathSciNet  MATH  Google Scholar 

  14. Duschka, O.M. and Levy, A.Y., A recursive plans for information gathering, Proc. 15th Int. Joint Conf. Artif. Intell., 1997, pp. 225–231.

    Google Scholar 

  15. Duschka, O.M., Query optimization using local completeness, Proc. 14th National Conference on Artificial Intelligence, 1997, pp. 225–231.

    Google Scholar 

  16. Lu, X.D., Moriyama, K., Luque, I., Kanda, M., Jiang, Y., Takanuki, R., and Mori, K., Timeliness and reliability oriented autonomous network-based information services integration in multi-agent systems, IEICE Trans. Inf. Syst., 2005, vol. E88-D, no. 9, pp. 2089–2097.

    Article  Google Scholar 

  17. Lu, X.D. and Mori, K., Autonomous integration and optimal allocation of heterogeneous information services for high-assurance in distributed information service system," IEICE Trans. Inf. Syst., 2003, vol. E86-D, no. 10, pp. 2087–2094.

    Google Scholar 

  18. SUN, Jini network technology. http://www.sun.com/software/jini/.

  19. Mori, K., Autonomous decentralized systems: Concepts, data field architecture and future trends, Proc. IEEE Conf. on ISADS, 1993, pp. 28–34.

    Google Scholar 

  20. Zhou, Y., Ahmad, H.F., Arfaoui, H., and Mori, K., Autonomous information allocation through mobile agents to achieve load balancing in distributed information service system, Proc. IEEE Conf. on IWADS2002, 2002, pp. 35–41.

    Google Scholar 

  21. Bayardo, Jr., R.J., Bohrer, W., Brice, R., Cichocki, A., Fowler, J., Helal, A., Ksiezyk, T., Martin, G., Nodine, M., Rashid, M., Rusinkiewicz, M., Shea, R., Unnikrishnan, C., Unruh, A., and Woelk, D., InfoSleuth: Agentbased semantic integration of information in open and dynamic environments, Proc. ACM SIGMOD, 1997, pp. 195–206.

    Google Scholar 

  22. Arens, Y., Knoblock, C.A., and Shen, W., Query reformulation for dynamic information integration, J. Intell. Inf. Syst., 1996, vol. 6, nos. 2–3, pp. 99–130.

    Article  Google Scholar 

  23. Geng, Y., He, J., Deng, H., and Pahlavan, K., Modeling the effect of human body on TOA ranging for indoor human tracking with wrist mounted sensor, 16th International Symposium on Wireless Personal Multimedia Communications (WPMC), Atlantic City, NJ, 2013.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Hubei Polytechnic Institute, Xiao’gan, 432000, China

    Hujun Li

  2. School of Teacher Education, Wenzhou University, Wenzhou, 325035, China

    XiaoZhi Li

  3. College of Physics and Electronic Information Engineering, Wenzhou University, Wenzhou, 325035, China

    Yi Wan

Authors
  1. Hujun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. XiaoZhi Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yi Wan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hujun Li.

Additional information

The article is published in the original.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, H., Li, X. & Wan, Y. Autonomous network-based integration architecture for multi-agent systems under dynamic and heterogeneous environment. Aut. Control Comp. Sci. 50, 347–360 (2016). https://doi.org/10.3103/S0146411616050060

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0146411616050060

Keywords

Search

Navigation