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Optimized clustering for data dissemination using stochastic coalition game in vehicular cyber-physical systems

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Abstract

Vehicular cyber-physical systems (VCPS) have emerged as one of the most powerful technologies for providing cost-effective services to the end users with minimum delay even with high mobility of the end users. As the contact time of the vehicles with the nearest access points is very less, so by integrating vehicles with the cloud environment can provide various services to the end users even with their high mobility. Keeping focus on these points, this paper proposed a new optimized strategy selection for data dissemination using a stochastic coalition game in VCPS environment. Vehicles in the coalition game are assumed as the players of the game which access a finite number of resources from the cloud. Learning automata (LA) stationed on the vehicles collect and process the information from the environment based upon pre-defined strategies. They are assumed to form a coalition based upon predictive clustering among one another using a pre-defined metric. Based upon the payoff matrix, each player executes, algorithms for cluster and leadership formation. Moreover, an algorithm for centralized supervision is also designed. At any instant in the game, only those players are allowed to make a move which are having highest payoff value so as to make a balance with respect to the moves taken by all the players in the game. The performance of the proposed scheme is evaluated using various evaluation metrics in different network scenarios. The results obtained show that the proposed scheme is better than the case where it is not applied. Specifically, there is an increase of 10–20 % in packet delivery ratio and 20 % reduction in delay in accessing various services from the cloud using the proposed scheme.

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References

  1. Gubbi J, Buyya R, Marusic S, Palaniswami M (2013) Internet of things (IoT): a vision, architectural elements, and future directions. Future Gener Comput Syst 29(7):1645–1660

    Article  MATH  Google Scholar 

  2. Lu N, Cheng N, Zhang N, Shen X, Mark J (2014) Connected vehicles: solutions and challenges. IEEE Internet Things J 1(4):289–299

    Article  Google Scholar 

  3. Abid H, Phuong LTT, Wang J, Lee S, Qaisar S (2011) V-Cloud: vehicular cyber-physical systems and cloud computing. In: Proceedings of the 4th international symposium on applied sciences in biomedical and communication technologies. Barcelona

  4. Yu R, Zhang Y, Gjessing S, Xia W, Yang K (2013) Toward cloud-based vehicular networks with efficient resource management. IEEE Netw 27(5):48–55

    Article  MATH  Google Scholar 

  5. Taleb T, Ksentini A (2013) Follow me cloud: interworking federated clouds and distributed mobile networks. IEEE Netw 27(5):12–19

    Article  Google Scholar 

  6. Ma X, Zhao Y, Zhang L, Wang H, Peng L (2013) When mobile terminals meet the cloud: computation offloading as the bridge. IEEE Netw 27(5):28–33

    Article  Google Scholar 

  7. He W, Yan G, Xu L (2014) Developing vehicular data cloud services in the IoT environment. IEEE Trans Ind Inform 10(2):1587–1595

    Article  Google Scholar 

  8. Wan J, Zhang D, Sun Y, Lin K, Zou C, Cai H (2014) VCMIA: a novel architecture for integrating vehicular cyber-physical systems and mobile cloud computing. Mob Netw Appl 19(2):153–160

    Article  MATH  Google Scholar 

  9. Dua A, Kumar N, Bawa S (2014) A systematic review on routing protocols for vehicular ad hoc networks. Veh Commun 1(1):33–52

    Article  Google Scholar 

  10. Kumar N, Chilamkurti N, Rodrigues JJPC (2014) Learning automata-based opportunistic data aggregation and forwarding scheme for alert generation in vehicular ad hoc networks. Comput Commun 59(1):22–32

    Article  Google Scholar 

  11. Bali RS, Kumar N, Rodriques JJPC (2014) Clustering in vehicular ad hoc networks: taxonomy, challenges and solutions. Veh Commun 1(3):134–152

    Article  Google Scholar 

  12. Kumar N, Chilamkurti N (2014) Collaborative trust aware intelligent intrusion detection system in VANETs. Comput Electr Eng 40(6):1981–1996

    Article  Google Scholar 

  13. Kumar N, Lee JH (2014) Peer-to-peer cooperative caching for data dissemination on urban vehicular communications. IEEE Syst J 8(4):1136–1144

    Article  Google Scholar 

  14. Kumar N, Chilamkurti N, Park JH (2013) ALCA: agent learning-based clustering algorithm in vehicular ad hoc networks. Pers Ubiquitous Comput 17(8):1683–1692

    Article  Google Scholar 

  15. Kumar N, Misra S, Obaidat MS (2014) Collaborative learning automata-based routing for rescue operations in dense urban regions using vehicular sensor networks. IEEE Syst J. doi:10.1109/JSYST.2014.2335451

  16. Kumar N, Lee JH, Rodrigues JJPC (2014) Intelligent mobile video surveillance system as a bayesian coalition game in vehicular sensor networks: learning automata approach. IEEE Trans Intell Transp Syst. doi:10.1109/TITS.2014.2354372

  17. Kumar N, Misra S, Obaidat MS, Rodrigues JJPC, Pati B (2014) Networks of learning automata for vehicular environment: a performance analysis study. IEEE Wirel Commun Mag 21(6):41–47

    Article  Google Scholar 

  18. Kumar N, Rodrigues JJPC, Chilamkurti N (2014) Bayesian coalition game as-a-service for content distribution in internet of vehicles. IEEE Internet Thing J 1(6):544–555

    Article  Google Scholar 

  19. Dua A, Kumar N, Bawa S (2015) QoS aware data dissemination for dense urban regions in vehicular ad hoc networks. Mob Netw Appl. doi:10.1007/s11036-014-0553-4

  20. Bali RS, Kumar N, Rodrigues JJPC (In Press) An efficient energy-aware predictive clustering approach for vehicular ad hoc networks. Int J Commun Syst. doi:10.1002/dac.2924

  21. Kumar N, Misra S, Obaidat MS (2015) Coalition games for spatio-temporal big data in internet of vehicles environment: a comparative analysis. Internet Things J. doi:10.1109/JIOT.2015.2388588

  22. Kumar N, Chilamkurti N, Misra SC (2015) Bayesian coalition game for internet of things: an ambient intelligence approach. IEEE Commun Mag 53(1):48–55

    Article  Google Scholar 

  23. Kumar N, Zeadally S, Chilamkurti N, Vinel A (2015) Performance analysis of Bayesian coalition-based energy-aware virtual machine migration in vehicular mobile cloud. IEEE Netw Mag 29(2):62–69

    Article  Google Scholar 

  24. Kumar N, Lee JH, Chilamkurti N, Vinel A (2015) Energy-efficient multimedia data dissemination in vehicular clouds: stochastic reward nets based coalition game approach. IEEE Syst J. doi:10.1109/JSYST.2015.2409651

  25. Kumar N, Misra S, Chilamkurti N, Lee JH, Rodrigues JPC (2015) Bayesian coalition negotiation game as a utility for secure energy management in a vehicles-to-grid environment. IEEE Trans Dependable Secure Comput. doi:10.1109/TDSC.2015.2415489

  26. Guclu S S, Deniz T A (2014) Uplink utilization with V2V2R communications in clustered vehicular networks. In: Proceedings of the 4th IEEE international conference on wireless communications, vehicular technology, information theory and aerospace and electronics systems (VITAE), 2014

  27. Louazani A, Sidi MS, Mohammed AB (2014) Clustering-based algorithm for connectivity maintenance in vehicular ad-hoc networks. In: Proceedings of the 14th IEEE international conference on innovations for community services (I4CS)

  28. Chiti F, Romano F, Giovanni R (2014) A mobility driven joint clustering and relay selection for IEEE 802.11 p/WAVE vehicular networks, 2014 IEEE International Conference on Communications (ICC)

  29. Xiaonan W, Qian H (2012) Constructing a VANET based on cluster chains. Int J Commun Syst 27(11):2497–2517

    Google Scholar 

  30. www.isi.edu/nsnam/ns/

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Thapar University, Patiala, Punjab, India

    Neeraj Kumar & Rasmeet Singh Bali

  2. Faculty of Engineering, Coventry University, Coventry, UK

    Rahat Iqbal

  3. Department of Computer Science and Computer Engineering, LaTrobe University, Melbourne, Australia

    Naveen Chilamkurti

  4. Department of Multimedia, Sungkyul University, Anyang, Korea

    Seungmin Rho

Authors
  1. Neeraj Kumar
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  2. Rasmeet Singh Bali
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  3. Rahat Iqbal
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  4. Naveen Chilamkurti
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  5. Seungmin Rho
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Corresponding author

Correspondence to Naveen Chilamkurti.

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Kumar, N., Bali, R.S., Iqbal, R. et al. Optimized clustering for data dissemination using stochastic coalition game in vehicular cyber-physical systems. J Supercomput 71, 3258–3287 (2015). https://doi.org/10.1007/s11227-015-1436-6

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  • DOI: https://doi.org/10.1007/s11227-015-1436-6

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