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A Cooperative Heterogeneous Vehicular Clustering Mechanism for Road Traffic Management

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Abstract

The vehicular ad-hoc networks integrates with long-term evolution (LTE) forming a heterogeneous network, capable of providing seamless connectivity, which meets the communication requirements of intelligent transportation systems. However, heterogeneous network-based applications involve LTE resource (data and spectrum) usage cost and must be taken care while developing such a solution. One of the scenarios is the access of the information to/from remote server over the internet via LTE for road traffic management applications. Although clustering of the vehicle is significant to minimize the data and LTE network usage, however, the problem of non-cooperation of the vehicles in clustering process and within a cluster are major issues in sharing costly data acquired from the internet. Because, who and why one (vehicle) should pay the cost is the big question, proliferating the non-cooperative behavior among the cluster members. To solve these issues, strategic game-theoretic based clustering mechanism named as cooperative interest-aware clustering (CIAC) is developed. The proposed CIAC not only balance the cost of usage by controlling non-cooperative behavior among the vehicles within the cluster but at the same time motivate vehicles to participate in the clustering process to share the data and cost as well. It consists of a cluster head selection process based on the strategic game-theoretic approach and a fair-use policy. The implementation results show superiority in performance of our protocol over the existing approaches.

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References

  1. Al-Sultan, S., Al-Doori, M.M., Al-Bayatti, A.H., Zedan, H.: A comprehensive survey on vehicular ad hoc network. J. Netw. Comput. Appl. 37, 380–392 (2014)

    Article  Google Scholar 

  2. Bali, R.S., Kumar, N., Rodrigues, J.J.: Clustering in vehicular ad hoc networks: taxonomy, challenges and solutions. Veh. Commun. 1(3), 134–152 (2014)

    Google Scholar 

  3. Dey, K.C., Rayamajhi, A., Chowdhury, M., Bhavsar, P., Martin, J.: Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication in a heterogeneous wireless networkperformance evaluation. Transp. Res. Part C: Emerg. Technol. 68, 168–184 (2016)

    Article  Google Scholar 

  4. Drira, W., Ahn, K., Rakha, H., Filali, F.: Development and testing of a 3g/lte adaptive data collection system in vehicular networks. IEEE Trans. Intell. Transp. Syst. 17(1), 240–249 (2016)

    Article  Google Scholar 

  5. Zheng, K., Zheng, Q., Chatzimisios, P., Xiang, W., Zhou, Y.: Heterogeneous vehicular networking: a survey on architecture, challenges, and solutions. IEEE Commun. Surv. Tutor. 17(4), 2377–2396 (2015)

    Article  Google Scholar 

  6. Krajzewicz, D., Erdmann, J., Behrisch, M., Bieker, L.: Recent development and applications of sumo-simulation of urban mobility. Int. J. Adv. Syst. Meas. 5(3 and 4), 128–138 (2012)

    Google Scholar 

  7. Sommer, C., German, R., Dressler, F.: Bidirectionally coupled network and road traffic simulation for improved IVC analysis. IEEE Trans. Mobile Comput. 10, 3–15 (2011)

  8. Virdis, A., Stea, G., Nardini, G.: Simulating LTE/LTE-Advanced Networks with SimuLTE, Book Section Simulating LTE/LTE-Advanced Networks with SimuLTE, pp. 83–105. Springer, Berlin (2015)

    Google Scholar 

  9. Hagenauer, F., Dressler, F., Sommer, C.: Poster: A simulator for heterogeneous vehicular networks. In: Vehicular Networking Conference (VNC), 2014 IEEE, IEEE, pp. 185–186 (2014)

  10. Wolny, G.: Modified DMAC clustering algorithm for VANETs. In: Systems and Networks Communications, 2008. ICSNC’08. 3rd International Conference on, IEEE, pp. 268–273 (2008)

  11. Ucar, S., Ergen, S.C., Ozkasap, O.: Multihop-cluster-based IEEE 802.11 p and LTE hybrid architecture for VANET safety message dissemination. IEEE Trans. Veh. Technol. 65(4), 2621–2636 (2016)

    Article  Google Scholar 

  12. Ahmad, I., Noor, R.M., Ahmedy, I., Shah, S.A.A., Yaqoob, I., Ahmed, E., Imran, M.: Vanetlte based heterogeneous vehicular clustering for driving assistance and route planning applications. Comput. Netw. 145, 128–140 (2018)

    Article  Google Scholar 

  13. Mohandas, B.K., Liscano, R., Yang, O.W.: Vehicle traffic congestion management in vehicular ad-hoc networks. In: Local Computer Networks, 2009. LCN 2009. IEEE 34th Conference on, IEEE, pp. 655–660 (2009)

  14. Ramakrishnan, B., Nishanth, R.B., Joe, M.M., Selvi, M.: Cluster based emergency message broadcasting technique for vehicular ad hoc network. Wirel. Netw. pp. 1–16 (2015)

  15. Gupte, S., Younis, M.: Vehicular networking for intelligent and autonomous traffic management. In: Communications (ICC), 2012 IEEE International Conference on, IEEE, pp. 5306–5310 (2012)

  16. Remy, G., Senouci, S.M., Jan, F., Gourhant, Y., LTE4V2X: LTE for a centralized VANET organization. In: Global Telecommunications Conference (GLOBECOM, : 2011 IEEE. IEEE 2011, pp. 1–6 (2011)

  17. Chen, S., Hu, J., Shi, Y., Zhao, L.: LTE-V: A TD-LTE-based V2X solution for future vehicular network. IEEE Internet Things J. 3(6), 997–1005 (2016)

    Article  Google Scholar 

  18. Wu, C., Gerla, M., Mastronarde, N.: Incentive driven LTE content distribution in VANETs. In: Ad Hoc Networking Workshop (MED-HOC-NET), 14th Annual Mediterranean. IEEE 2015, pp. 1–8 (2015)

  19. Zhao, H., Garcia-Palacios, E., Wei, J., Xi, Y.: Accurate available bandwidth estimation in ieee 802.11-based ad hoc networks. Comput. Commun. 32(6), 1050–1057 (2009)

    Article  Google Scholar 

  20. Korowajczuk, L.: LTE, WiMAX and WLAN Network Design, Optimization and Performance Analysis. Wiley, London (2011)

    Book  Google Scholar 

  21. Mir, Z.H.: LTE and IEEE 802.11 p for vehicular networking: a performance evaluation. EURASIP J. Wirel. Commun. Netw. 2014(1), 1 (2014)

    Article  MathSciNet  Google Scholar 

  22. Sommer, C., Schmidt, A., Chen, Y., German, R., Koch, W., Dressler, F.: On the feasibility of umts-based traffic information systems. Ad Hoc Netw. 8(5), 506–517 (2010)

    Article  Google Scholar 

  23. Uppoor, S., Fiore, M.: Characterizing pervasive vehicular access to the cellular ran infrastructure: an urban case study. IEEE Trans. Veh. Technol. 64(6), 2603–2614 (2015)

    Article  Google Scholar 

  24. Lu, D., Li, Z., Huang, D., Lu, X., Deng, Y., Chowdhary, A., Li, B.: VC-bots: a vehicular cloud computing testbed with mobile robots. In: Proceedings of the First International Workshop on Internet of Vehicles and Vehicles of Internet, ACM, pp. 31–36 (2016)

  25. Gerla, M., Lee, E.K., Pau, G., Lee, U.: Internet of vehicles: from intelligent grid to autonomous cars and vehicular clouds. In: Internet of Things (WF-IoT), IEEE World Forum on. IEEE 2014, pp. 241–246 (2014)

  26. Lin, D., Tang, Y., Labeau, F., Yao, Y., Imran, M., Vasilakos, A.V.: Internet of vehicles for e-health applications: a potential game for optimal network capacity. IEEE Syst. J. 11(3), 1888–1896 (2017)

    Article  Google Scholar 

  27. Wu, C., Gerla, M., Mastronarde, N.: Incentive driven LTE content distribution in VANETs. In: 2015 14th Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET), pp. 1–8 (2015). https://doi.org/10.1109/MedHocNet.2015.7173168

  28. Wang, J., Liu, K., Xiao, K., Chen, C., Wu, W., Lee, VC., Son, SH.: Dynamic clustering and cooperative scheduling for vehicle-to-vehicle communication in bidirectional road scenarios. IEEE Trans. Intell. Transp. Syst. (2017)

  29. Das, B., Almhana, J.: A new cooperative communication algorithm for improving connectivity in the event of network failure in vanets. Comput. Netw. (2017)

  30. Hassanabadi, B., Shea, C., Zhang, L., Valaee, S.: Clustering in vehicular ad hoc networks using affinity propagation. Ad Hoc Netw. 13, 535–548 (2014)

    Article  Google Scholar 

  31. Araniti, G., Campolo, C., Condoluci, M., Iera, A., Molinaro, A.: LTE for vehicular networking: a survey. IEEE Commun. Mag. 51(5), 148–157 (2013)

    Article  Google Scholar 

  32. Ahmad, I., Md Noor, R., Reza Z’aba, M.: LTE efficiency when used in traffic information systems: a stable interest aware clustering. Int. J. Commun. Syst. e3853 (2018)

  33. Liu, K., Ng, J.K., Lee, V.C., Son, S.H., Stojmenovic, I.: Cooperative data scheduling in hybrid vehicular ad hoc networks: VANET as a software defined network. EEE/ACM Trans. Netw. 24(3), 1759–1773 (2015)

    Article  Google Scholar 

  34. Benslimane, A., Taleb, T., Sivaraj, R.: Dynamic clustering-based adaptive mobile gateway management in integrated VANET—3G heterogeneous wireless networks. IEEE J. Sel. Areas Commun. 29(3), 559–570 (2011)

    Article  Google Scholar 

  35. Chiti, F., Fantacci, R., Gu, Y., Han, Z.: Content sharing in internet of vehicles: two matching-based user-association approaches. Veh. Commun. 8, 35–44 (2017)

    Google Scholar 

  36. Huang, W., Wang, L.: ECDS: efficient collaborative downloading scheme for popular content distribution in urban vehicular networks. Comput. Netw. 101, 90–103 (2016)

    Article  Google Scholar 

  37. Luan, T.H., Cai, L.X., Chen, J., Shen, X.S., Bai, F.: Engineering a distributed infrastructure for large-scale cost-effective content dissemination over urban vehicular networks. IEEE Trans. Veh. Technol. 63(3), 1419–1435 (2014)

    Article  Google Scholar 

  38. Zhou, Z., Gao, C., Xu, C., Zhang, Y., Mumtaz, S., Rodriguez, J.: Social big data based content dissemination in internet of vehicles. IEEE Trans. Ind. Inform. PP(99):1–1 (2017). https://doi.org/10.1109/TII.2017.2733001

  39. Morales, M.M.C., Haw, R., Cho, E.J., Hong, C.S., Lee, S.W.: An adaptable destination-based dissemination algorithm using a publish/subscribe model in vehicular networks. J. Comput. Sci. Eng. 6(3), 227–242 (2012)

    Article  Google Scholar 

  40. Zhao, H., Ding, K., Sarkar, NI., Wei, J., Xiong, J.: A simple distributed channel allocation algorithm for D2D communication pairs. IEEE Trans. Veh. Technol. (2018)

  41. Lianghai, J., Liu, M., Weinand, A., Schotten, H.D., Direct vehicle-to-vehicle communication with infrastructure assistance in 5G network. In: Ad Hoc Networking Workshop (Med-Hoc-Net), 16th Annual Mediterranean. IEEE 2017, pp. 1–5 (2017)

  42. Shah, S.A.A., Ahmed, E., Imran, M., Zeadally, S.: 5G for vehicular communications. IEEE Commun. Mag. 56(1), 111–117 (2018)

    Article  Google Scholar 

  43. Fallucchi, F., Luccasen, RA., Turocy, TL.: Behavioural types in public goods games: a re-analysis by hierarchical clutering. Report, School of Economics, University of East Anglia, Norwich, UK (2017)

  44. Haklay, M.: How good is volunteered geographical information? A comparative study of openstreetmap and ordnance survey datasets. Environ. Plan. B: Plan. Des. 37(4), 682–703 (2010)

    Article  Google Scholar 

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Acknowledgements

This research is supported by Grand Challenge Grant UM.0000007/HRU.GC.SS GC002B-15SUS from Sustainable Science Cluster, University of Malaya, Malaysia. This research work is also sponsored by the Mirpur University of Science and Technology, Mirpur-10250 (AJK), Pakistan. The work of M. Imran and M. Shoaib is supported by the Deanship of Scientific Research, King Saud University through Research Group No. RG-1439-036.

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Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia

    Iftikhar Ahmad, Rafidah Md Noor & Muhammad Reza Zaba

  2. Center for Mobile Cloud Computing Research (C4MCCR), University of Malaya, Kuala Lumpur, Malaysia

    Rafidah Md Noor

  3. Department of CS and IT, Mirpur University of Science and Technology, Mirpur, 10250, AJK, Pakistan

    Iftikhar Ahmad

  4. Department of Computer Science and Software Engineering, International Islamic University Islamabad, Islamabad, Pakistan

    Muhammad Ahsan Qureshi

  5. College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

    Muhammad Imran & Muhammad Shoaib

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  1. Iftikhar Ahmad
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Correspondence to Iftikhar Ahmad or Rafidah Md Noor.

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Ahmad, I., Noor, R.M., Zaba, M.R. et al. A Cooperative Heterogeneous Vehicular Clustering Mechanism for Road Traffic Management. Int J Parallel Prog 48, 870–889 (2020). https://doi.org/10.1007/s10766-019-00629-y

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