Personal and Ubiquitous Computing

, Volume 17, Issue 8, pp 1683–1692 | Cite as

ALCA: agent learning–based clustering algorithm in vehicular ad hoc networks

  • Neeraj Kumar
  • Naveen Chilamkurti
  • Jong Hyuk Park
Original Article

Abstract

Vehicular ad hoc network (VANET) is an emerging technology which can be used in various applications such as intelligent transport technology, safety applications, etc. But one of the major issues in VANETs is how to cluster the vehicles on the road for efficient operations such as routing, mobility management and generating safety alarms. Clustering of vehicles has been widely used for routing and data dissemination in VANETs. But due to the high mobility of the vehicles/nodes on the road, it is quite difficult to find the exact route in VANETs. Keeping in view of the above issue, in this paper, we propose a new agent learning–based clustering and routing in VANETs. Agents learn from the environment in which they are deployed, and accordingly, their action performed is rewarded or penalized with certain values. Each agent performs its task in collaboration with the other agents, i.e. agents communicate with each other in collaborative manner for information sharing. The deployed agents estimate the mobility of the vehicles, and based upon their learning, clustering of vehicles is performed. An Agent Learning–based Algorithm for Clustering is proposed. The performance of the proposed scheme is evaluated using extensive simulation with respect to the various metrics such as message transmission ratio, percentage of connectivity, node participation, cluster head duration, and connectivity preservation ratio. The results obtained show that the proposed scheme is effective in performing fast clustering and converges quickly to the final solution.

Keywords

Agents Clustering Routing Vehicular ad hoc networks 

References

  1. 1.
    Balasubramanian R, Mahajan A, Venkataramani BN, Levine BN, Zahorjan J (2008) Interactive WiFi connectivity for moving vehicles. SIGCOMM Comput Commun Rev 38(4):427–438CrossRefGoogle Scholar
  2. 2.
    Eriksson J, Balakrishnan H, Madden S (2008) Cabernet: vehicular content delivery using WiFi, In: Proceedings of the 14th ACM international conference on mobile computing and networking (MobiCom’08), San Francisco, California, USA, pp 199–210Google Scholar
  3. 3.
    Lee SH, Lee U, Lee KW, Gerla M (2008) Content distribution in VANETs using network coding: the effect of disk I/O and processing O/H. In: Proceedings of the 5th annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks (SECON’08), San Francisco, California, USA, pp 117–125Google Scholar
  4. 4.
    Yang Q, Lim A, Li S, Fang J, Agrawal P (2010) ACAR: adaptive connectivity aware routing for vehicular ad hoc networks in city scenarios. Mobile Netw Appl 15(1):36–60CrossRefGoogle Scholar
  5. 5.
    Parno B, Perrig A (2005) Challenges in securing vehicular networks. In: Proceedings of the fourth workshop on hot topics in networks (HotNets-IV), College park, Mryland, USA, pp 347–351Google Scholar
  6. 6.
    Zhou T, Sharif H, Hempel M, Mahasukhon P, Wang W, Ma T (2011) A novel adaptive distributed cooperative relaying mac protocol for vehicular networks. IEEE J Sel Areas Commun 29(1):72–82CrossRefGoogle Scholar
  7. 7.
  8. 8.
    Yang Q, Lim A, Agrawal P (2008) Connectivity aware routing in vehicular networks. In: Proceedings of wireless communications and networking conference (WCNC), Las Vegas, Nevada, USA, pp 2218–2223Google Scholar
  9. 9.
    Daeinabi A, Rahbar AG, Khademzadeh A (2011) VWCA: an efficient clustering algorithm in vehicular adhoc networks. J Netw Comput Appl 34(1):207–222CrossRefGoogle Scholar
  10. 10.
    Manvi SS, Kakkasageri MS, Pitt J (2009) Multiagent based information dissemination in vehicular ad hoc networks. Mobile Inf Syst 5(4):363–389Google Scholar
  11. 11.
    Nehra N, Patel RB, Bhat VK (2007) Routing with load balancing in ad hoc network: a mobile agent approach. In: Proceedings of 6th annual IEEE/ACIS international conference on computer and information science (ICIS 2007), Melbourne, Australia, 11–13 July 2007, pp 489–495Google Scholar
  12. 12.
    Nehra N, Patel RB, Bhat VK (2007) MASD: mobile agent based service discovery in ad hoc networks. In: Proceeding of 14th international high performance computing conference (HiPC 2007), Goa, India, 18–21 Dec 2007, pp 612–624Google Scholar
  13. 13.
    Chatterjee M, Das SK, Turgut D (2002) WCA: a weighted clustering algorithm for mobile ad hoc networks. J Clust Comput 5(2):193–204Google Scholar
  14. 14.
    Blum J, Eskandarian A, Hoffman L (2003) Mobility management in IVC networks. In: Proceedings of the IEEE intelligent vehicles symposium, Washington, DC, USA, 9–11 June 2003, pp 150–155Google Scholar
  15. 15.
    Fan P, Mohamadian A, Nelson P, Haran J, Dillenburg J (2007) A novel direction-based clustering algorithm in vehicular ad hoc networks. In: Proceedings of the transportation research board 86th annual meeting, Washington DC, United StatesGoogle Scholar
  16. 16.
    Yang Q, Lim A, Shuang L, Fang J, Agrawal P (2010) ACAR: adaptive connectivity aware routing in vehicular adhoc networks for city scenarios. Mobile Netw Appl 15:36–60CrossRefGoogle Scholar
  17. 17.
    Wu H, Fujimoto R, Guensler R, Hunter M (2004) MDDV: a mobility-centric data dissemination algorithm for vehicular networks. In: VANET’04: proceedings of the 1st ACM international workshop on vehicular ad hoc networks. ACM, New York, pp 47–56Google Scholar
  18. 18.
    Liu G, Lee B, Seet B, Foh C, Lee K (2004) A routing strategy for metropolis vehicular communications, In: Proceedings of international conference on information networking. pp 533–542Google Scholar
  19. 19.
    LeBrun J, Chuah CN, Ghosal D, Zhang M (2005) Knowledge-based opportunistic forwarding in vehicular wireless ad hoc networks. In: Vehicular technology conference, VTC 2005-Spring. 2005 IEEE 61st, vol 4. IEEE, Piscataway, pp 2289–2293Google Scholar
  20. 20.
    Zhao J, Cao G (2006) VADD: vehicle-assisted data delivery in vehicular ad hoc networks. In: Proceedings of 25th IEEE international conference on computer communications (INFOCOM 2006), Barcelona, Spain, pp 1–12Google Scholar
  21. 21.
    Tatchikou R, Biswas S, Dion F (2005) Cooperative vehicle collision avoidance using inter-vehicle packet forwarding. In: Proceedings of IEEE global telecommunications conference (IEEE GLOBECOM 2005), St. Louis, MO, USA, pp 2762–2766Google Scholar
  22. 22.
    Buchenscheit A, Schaub F, Kargl F, Weber M (2009) A VANET-based emergency vehicle warning system. In: Proceedings of first IEEE vehicular networking conference (IEEE VNC 2009), Tokyo, Japan, pp 1–8Google Scholar
  23. 23.
    Fiore M, Barcelo-Ordinas JM (2009) Cooperative download in urban vehicular networks. In: Proceedings of the sixth IEEE international conference on mobile ad-hoc and sensor systems (IEEE MASS 2009), University of Macau, Macau SAR, PRC, pp 20–29Google Scholar
  24. 24.
    Leontiadis I, Mascolo C (2007) GeOpps: geographical opportunistic routing for vehicular networks. In: Proceedings of IEEE international symposium on a world of wireless, mobile and multimedia networks 2007 (WoWMoM 2007), Espoo, Finland, pp 1–6Google Scholar
  25. 25.
    Zhang M, Wolff RS (2010) A border node based routing protocol for partially connected vehicular ad hoc networks. J Commun 5(2):130–143Google Scholar
  26. 26.
    Abuelela M, Olariu S (2007) Traffic-adaptive packet relaying in VANET. In: Proceedings of fourth ACM international workshop on vehicular ad hoc networks (VANET 2007), in conjunction with ACM MobiCom 2007, Montréal, QC, Canada, pp 77–78Google Scholar
  27. 27.
    Soares VNJ, Farahmand F, Rodrigues JPC (2009) A layered architecture for vehicular delay-tolerant networks. In: Proceedings of fourteenth IEEE symposium on computers and communications (ISCC 2009), Sousse, Tunisia, pp 122–127Google Scholar
  28. 28.
    Lee U, Magistretti E, Gerla M, Bellavista P, Corradi A (2009) Dissemination and harvesting of urban data using vehicular sensing platforms. IEEE Trans Veh Technol 58(2):882–901CrossRefGoogle Scholar
  29. 29.
    Rawat DB, Popescu D, Yan C, Gongjun O (2011) Enhancing VANET performance by jointadaptation of transmission power and contention window size. IEEE Trans Parallel Distrib Syst 22(9):1528–1535CrossRefGoogle Scholar
  30. 30.
    Moez J, Mohammed S, Tinku R, Ghamri DY (2009) Towards efficient geographic routing in urban vehicular networks. IEEE Trans Veh Technol 58(9):5048–5059CrossRefGoogle Scholar
  31. 31.
    Pan R, Guandong X, Bin F, Dolog P, Wang Z, Leginus M (2012) Improving recommendations by the clustering of tag neighbours. J converg 3(1):13–20Google Scholar
  32. 32.
    Li T, Fajiang Y, Lin Y, Kong X, Yue Yu (2011) Trusted computing dynamic attestation using a static analysis based behaviour model. J converg 2(1):61–68Google Scholar
  33. 33.
    Silas Salaja, Ezra Kirubakaran, Rajsingh EB (2012) A novel fault tolerant service selection framework for pervasive computing. HCIS 2:5Google Scholar
  34. 34.
    Hsiao Kuei-Fang, Rashvand HF (2011) Integrating body language movements in augmented reality learning environment. HCIS 1(1):2011Google Scholar
  35. 35.
    Härri J, Filali F, Bonnet C, Fiore M (2006) VanetMobiSim: generating realistic mobility patterns for vanets. In: Proceedings of the 3rd international workshop on vehicular ad hoc networks, (VANET,’06), Los Angles, California, USA, pp 96–97Google Scholar

Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  • Neeraj Kumar
    • 1
  • Naveen Chilamkurti
    • 2
  • Jong Hyuk Park
    • 3
  1. 1.Department of Computer Science and EngineeringThapar UniversityPatialaIndia
  2. 2.Department of Computer Science and Computer EngineeringLaTrobe UniversityMelbourneAustralia
  3. 3.Seoul National University of Science and TechnologySeoulKorea

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