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An efficient distributed mutual exclusion algorithm for intersection traffic control


As vehicular networking has recently been developed and commercialized, vehicular cloud computing has received much attention in various research areas, such as intelligent transportation systems and vehicular ad hoc networks. An efficient intersection traffic control using vehicular cloud computing is one of the key research topics in intelligent transportation systems. To efficiently deal with intersection traffic control via vehicle-to-vehicle communications, we design a distributed mutual exclusion algorithm that does not rely on broadcast, which introduces communication overheads; instead, our algorithm use point-to-point messages sent between the vehicles to keep network traffic load lower. In our algorithmic design, to pass an intersection, the lead vehicle on a lane must get permissions from a subset of other vehicles and its following vehicles on the same lane can follow the lead vehicle without permissions unlike the previous research. To evaluate the performance of our distributed mutual exclusion algorithm, we conduct extensive experiments. The results show that our algorithmic design is both effective and efficient.

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  1. Diakaki C, Papageorgiou M, Papamichail I, Nikolos I (2015) Overview and analysis of vehicle automation and communication systems from a motorway traffic management perspective. Transp Res Part A Policy Pract 75:147–165. doi:10.1016/j.tra.2015.03.015

    Article  Google Scholar 

  2. Conti M, Giordano S (2014) Mobile ad hoc networking: milestones, challenges, and new research directions. IEEE Commun Mag 52(1):85–96. doi:10.1109/MCOM.2014.6710069

    Article  Google Scholar 

  3. Al-Sultan S, Al-Doori MM, Al-Bayatti AH, Zedan H (2014) A comprehensive survey on vehicular ad hoc network. J Netw Computer Appl 37:380–392. doi:10.1016/j.jnca.2013.02.036

    Article  Google Scholar 

  4. Zeadally S, Hunt R, Chen Y-S, Irwin A, Hassan A (2010) Vehicular ad hoc networks (VANETS): status, results, and challenges. Telecommun Syst 50(4):217–241. doi:10.1007/s11235-010-9400-5

    Article  Google Scholar 

  5. Dimitrakopoulos G, Bravos G, Nikolaidou M, Anagnostopoulos D (2013) Proactive, knowledge-based intelligent transportation system based on vehicular sensor networks. IET Intell Transp Syst 7(4):454–463. doi:10.1049/iet-its.2012.0138

    Article  Google Scholar 

  6. Cheng X, Yang L, Shen X (2015) D2D for intelligent transportation systems: a feasibility study. IEEE Trans Intell Transp Syst 16(4):1784–1793. doi:10.1109/TITS.2014.2377074

    Article  Google Scholar 

  7. Toor Y, Muhlethaler P, Laouiti A (2008) Vehicle ad hoc networks: applications and related technical issues. IEEE Commun Surv Tutor 10(3):74–88. doi:10.1109/COMST.2008.4625806

    Article  Google Scholar 

  8. Karagiannis G, Altintas O, Ekici E, Heijenk G, Jarupan B, Lin K, Weil T (2011) Vehicular networking: a survey and tutorial on requirements, architectures, challenges, standards and solutions. IEEE Commun Surv Tutor 13(4):584–616. doi:10.1109/SURV.2011.061411.00019

    Article  Google Scholar 

  9. Pereira PR, Casaca A, Rodrigues JJPC, Soares VNGJ, Triay J, Cervello-Pastor C (2012) From delay-tolerant networks to vehicular delay-tolerant networks. IEEE Commun Surv Tutor 14(4):1166–1182. doi:10.1109/SURV.2011.081611.00102

    Article  Google Scholar 

  10. Sharma V, Singh H, Kant S (2013) AODV based energy efficient IEEE 802.16G VANET network. In: Fifth international conference on advances in recent technologies in communication and computing (ARTCom 2013), 20–21 Sept. 2013, pp 35–43. doi:10.1049/cp.2013.2221

  11. Zhang H, Li J (2015) Topology analysis of VANET based on complex network. In: Zhang Z, Shen MZ, Zhang J, Zhang R (eds) LISS 2014: Proceedings of 4th international conference on logistics, informatics and service science. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 1143–1148. doi:10.1007/978-3-662-43871-8_165

  12. Kumar A, Sinha M (2014) Overview on vehicular ad hoc network and its security issues. In: 2014 International conference on computing for sustainable global development (INDIACom), 5–7 March 2014, pp 792–797. doi:10.1109/IndiaCom.2014.6828071

  13. Engoulou RG, Bellaïche M, Pierre S, Quintero A (2014) VANET security surveys. Computer Commun 44:1–13. doi:10.1016/j.comcom.2014.02.020

    Article  Google Scholar 

  14. Xiang Y, Liu Z, Liu R, Sun W, Wang W (2013) GeoSVR: a map-based stateless VANET routing. Ad Hoc Netw 11(7):2125–2135. doi:10.1016/j.adhoc.2012.02.015

    Article  Google Scholar 

  15. Ali F, Shaikh FK, Ansari AQ, Mahoto NA, Felemban E (2015) Comparative analysis of VANET routing protocols: on road side unit placement strategies. Wirel Pers Commun 85(2):393–406. doi:10.1007/s11277-015-2745-z

    Article  Google Scholar 

  16. Sahoo A, Swain SK, Pattanayak BK, Mohanty MN (2016) An optimized cluster based routing technique in VANET for next generation network. In: Satapathy CS, Mandal KJ, Udgata KS, Bhateja V (eds) Information systems design and intelligent applications: proceedings of third international conference INDIA 2016, vol 1. Springer India, New Delhi, pp 667–675. doi:10.1007/978-81-322-2755-7_69

  17. Bitam S, Mellouk A, Zeadally S (2015) VANET-cloud: a generic cloud computing model for vehicular ad hoc networks. IEEE Wirel Commun 22(1):96–102. doi:10.1109/MWC.2015.7054724

    Article  Google Scholar 

  18. Bitam S, Mellouk A (2015) Cloud computing-based message dissemination protocol for vehicular ad hoc networks. In: Aguayo-Torres CM, Gómez G, Poncela J (eds) Wired/wireless internet communications: 13th international conference, WWIC 2015, Malaga, Spain, May 25–27, 2015, revised selected papers. Springer International Publishing, Cham, pp 32–45. doi:10.1007/978-3-319-22572-2_3

  19. Cunha F, Villas L, Boukerche A, Maia G, Viana A, Mini RAF, Loureiro AAF (2016) Data communication in VANETs: survey, applications and challenges. Ad Hoc Netw. doi:10.1016/j.adhoc.2016.02.017

  20. Rahimi MR, Ren J, Liu CH, Vasilakos AV, Venkatasubramanian N (2013) Mobile cloud computing: a survey, state of art and future directions. Mob Netw Appl 19(2):133–143. doi:10.1007/s11036-013-0477-4

    Article  Google Scholar 

  21. Sanaei Z, Abolfazli S, Gani A, Buyya R (2014) Heterogeneity in mobile cloud computing: taxonomy and open challenges. IEEE Commun Surv Tutor 16(1):369–392. doi:10.1109/SURV.2013.050113.00090

    Article  Google Scholar 

  22. Pasha M, Farooq MU, Khan K-U-R (2016) A proof-of-concept model for vehicular cloud computing using OMNeT++ and SUMo. In: Saini SH, Sayal R, Rawat SS (eds) Innovations in computer science and engineering: proceedings of the third ICICSE, 2015. Springer Singapore, Singapore, pp 193–198. doi:10.1007/978-981-10-0419-3_23

  23. Whaiduzzaman M, Sookhak M, Gani A, Buyya R (2014) A survey on vehicular cloud computing. J Netw Computer Appl 40:325–344. doi:10.1016/j.jnca.2013.08.004

    Article  Google Scholar 

  24. Lamport L (1987) A fast mutual exclusion algorithm. ACM Trans Comput Syst 5(1):1–11. doi:10.1145/7351.7352

    Article  Google Scholar 

  25. Raynal M (2013) The mutual exclusion problem. In: Raynal M (ed) Concurrent programming: algorithms, principles, and foundations: algorithms, principles, and foundations. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 3–13. doi:10.1007/978-3-642-32027-9_1

  26. Maekawa M (1985) AN algorithm for mutual exclusion in decentralized systems. ACM Trans Comput Syst 3(2):145–159. doi:10.1145/214438.214445

    Article  Google Scholar 

  27. Yuh-Jzer J (2003) Quorum-based algorithms for group mutual exclusion. IEEE Trans Parallel Distrib Syst 14(5):463–476. doi:10.1109/TPDS.2003.1199064

    Article  MATH  Google Scholar 

  28. Weigang W, Jiebin Z, Aoxue L, Jiannong C (2015) Distributed mutual exclusion algorithms for intersection traffic control. IEEE Trans Parallel Distrib Syst 26(1):65–74. doi:10.1109/TPDS.2013.2297097

    Article  Google Scholar 

  29. Sichitiu ML, Kihl M (2008) Inter-vehicle communication systems: a survey. IEEE Commun Surv Tutor 10(2):88–105. doi:10.1109/COMST.2008.4564481

    Article  Google Scholar 

  30. Lim J, Suh T, Gil J, Yu H (2014) Scalable and leaderless Byzantine consensus in cloud computing environments. Inf Syst Front 16(1):19–34. doi:10.1007/s10796-013-9460-7

    Article  Google Scholar 

  31. Lim J, Suh T, Yu H (2014) Unstructured deadlock detection technique with scalability and complexity-efficiency in clouds. Int J Commun Syst 27(6):852–870. doi:10.1002/dac.2638

    Article  Google Scholar 

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Correspondence to HwaMin Lee.

Additional information

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2014R1A1A2057878) and by the Soonchunhyang University Research Fund.

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Lim, J., Jeong, Y.S., Park, DS. et al. An efficient distributed mutual exclusion algorithm for intersection traffic control. J Supercomput 74, 1090–1107 (2018).

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  • Mutual exclusion
  • Intersection traffic control
  • Intelligent transportation system
  • Vehicular cloud computing