Mobile Agents for CPS in Intelligent Transportation Systems

  • Yingying Wang
  • Hehua YanEmail author
  • Jiafu Wan
  • Keliang Zhou
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 260)


Recently, cyber-physical systems (CPS) have emerged as a promising direction to enrich the interactions between physical and virtual worlds. Because of the large-scale features of CPS, mobile agents (MA) technology can promote the performance of CPS. In this article, we first introduce the concept and characteristics of CPS, MA, and intelligent transportation system (ITS). Then, we propose the structure of intelligent transportation CPS (ITCPS). On this basis, giving the case of mobile agents for ITCPS, we exploit a mobile agent by three levels (node level, task level, and combined task level) to reduce the information redundancy and communication overhead. Finally, we in brief outline the technical challenges for ITCPS.


Adaptive mobile agents Cyber-physical systems Intelligent transportation system 



The authors would like to thank the National Natural Science Foundation of China (No. 61262013), the Natural Science Foundation of Guangdong Province, China (No. S2011010001155), and the High-level Talent Project for Universities, Guangdong Province, China (No. 431, YueCai Jiao 2011) for their support in this research.


  1. 1.
    Wen JR, Wu MQ, Su JF (2012) Cyber–physical system. Acta Automatica Sinica 38(4):507–515CrossRefGoogle Scholar
  2. 2.
    Wang ZJ, Xie LL (2011) Cyber–physical systems: a survey. Acta Automatica Sinica 37(10):1157–1166MathSciNetGoogle Scholar
  3. 3.
    Wang X, Xing G, Zhang Y, Lu C, Pless R, Gill C (2003) Integrated coverage and connectivity configuration in wireless sensor networks. In: Proceedings of the 1st international conference on Embedded networked sensor systems, Los Angeles, California, USA, pp 28–39Google Scholar
  4. 4.
    Han L, Potter S, Beckett G, Pringle G, Welch S, Koo SH, Tate A (2010) FireGrid: an e-infrastructure for next-generation emergency response support. J Parallel Distrib Comput 70(11):1128–1141CrossRefGoogle Scholar
  5. 5.
    Ranjan S, Gupta A, Basu A, Meka A, Chaturvedi A (2000) Adaptive mobile agents: modeling and a case study. In: Proceedings of 2nd workshop on distributed computing IEEE Ind CFP, WDCGoogle Scholar
  6. 6.
    Zhao J, Liu B (2010) An overview of mobile agent (Mogent). Micro Process 31(1):1–5zbMATHGoogle Scholar
  7. 7.
    Chen M, Gonzalez S, Leung V (2007) Applications and design issues for mobile agents in wireless sensor networks. IEEE Wirel Commun 14(6):20–26CrossRefGoogle Scholar
  8. 8.
    Wang R, Zhou C (2001) The study of mogent (mobile agent): an overview. Appl Res Comput 18(6):9–11Google Scholar
  9. 9.
    Beresford AR, Bacon J (2006) Intelligent transportation systems. IEEE Pervasive Comput 5(4):63–67CrossRefGoogle Scholar
  10. 10.
    Dimitrakopoulos G, Demestichas P (2010) Intelligent transportation systems. IEEE Veh Technol Mag 5(1):77–84CrossRefGoogle Scholar
  11. 11.
    Weiland RJ, Purser LB (2000) Intelligent transportation systems, transportation in the new millenniumGoogle Scholar
  12. 12.
    Miller J (2008) Vehicle–to–vehicle–to–infrastructure (V2V2I) intelligent transportation system architecture. IEEE intelligent vehicles Symposium, pp. 715–720Google Scholar
  13. 13.
    Wang F (2010) Parallel control and management for intelligent transportation systems: concepts, architectures, and applications. IEEE Intell Transp Syst 11(3):630–638CrossRefGoogle Scholar
  14. 14.
    Chen M, Wan J, Li F (2012) Machine-to-machine communications: architectures, standards, and applications. KSII Trans Internet Inf Syst 6(2):480–497Google Scholar
  15. 15.
    Li LI, Liu YA, Tang BH (2007) SNMS: an intelligent transportation system network architecture based on WSN and P2P network. J China Univ Posts Telecommun 14(1):65–70MathSciNetCrossRefGoogle Scholar
  16. 16.
    Suo H, Wan J, Huang L, Zou C (2012) Issues and challenges of wireless sensor networks localization in emerging applications. In: Proceedings of 2012 international conference on computer science and electronic engineering, Hangzhou, China, pp 447–451Google Scholar
  17. 17.
    Wan J, Li D (2010) Fuzzy feedback scheduling algorithm based on output jitter in resource–constrained embedded systems. In Proceedings of international conference on challenges in environmental science and computer engineering, Wuhan, China, pp 457–460Google Scholar
  18. 18.
    Chen M, Gonzalez S, Zhang Q, Leung VC (2010) Code-centric RFID system based on software agent intelligence. IEEE Intell Syst 25(2):12–19CrossRefGoogle Scholar
  19. 19.
    Tseng YC, Kuo SP, Lee HW, Huang CF (2004) Location tracking in a wireless sensor network by mobile agents and its data fusion strategies. Comput J 47(4):448–460CrossRefGoogle Scholar
  20. 20.
    Zou C, Wan J, Chen M, Li D (2012) Simulation modeling of cyber-physical systems exemplified by unmanned vehicles with WSNs navigation. In Proceedings of the 7th international conference on embedded and multimedia computing technology and service, Gwangju, Korea, pp 269–275Google Scholar
  21. 21.
    Chen M, Leung V, Mao S, Kwon T (2009) Receiver-oriented load-balancing and reliable routing in wireless sensor networks. Wirel Commun Mob Comput 9(3):405–416CrossRefGoogle Scholar
  22. 22.
    Wan J, Yan H, Suo H, Li F (2011) Advances in cyber-physical systems research. KSII Trans Internet Inf Syst 5(11):1891–1908Google Scholar
  23. 23.
    Chen M, Gonzalez S, Zhang Y, Leung V (2009) Multi-agent itinerary planning for wireless sensor networks. Qual Serv Heterogen Netw 22:584–597CrossRefGoogle Scholar
  24. 24.
    Wu FJ, Kao YF, Tseng YC (2011) From wireless sensor networks towards cyber physical systems. Pervasive Mob Comput 7(4):397–413CrossRefGoogle Scholar
  25. 25.
    Liu J, Wang Q, Wan J, Xiong J (2012) Towards real-time indoor localization in wireless sensor networks. In: Proceedings of 12th IEEE international conference on computer and information technology, Chengdu, China, pp 877–884Google Scholar
  26. 26.
    Yan H, Wan J, Suo H (2011) Adaptive resource management for cyber–physical systems. In: Proceedings of international conference on mechatronics and applied mechanics, HongKong, pp 747–751Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Yingying Wang
    • 1
  • Hehua Yan
    • 1
    Email author
  • Jiafu Wan
    • 1
  • Keliang Zhou
    • 2
  1. 1.School of Information EngineeringGuangdong Jidian PolytechincGuangzhouChina
  2. 2.College of Electrical Engineering and AutomationJiangxi University of Science and TechnologyGanzhouChina

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