Drop-Burst Length Evaluation of Urban VANETs

Awos Kh. Ali, Iain Phillips, Huanjia Yang

Abstract


Networks performance is traditionally evaluated using packet delivery ratio (PDR) and latency (delay). We propose an addition mechanism the drop-burst length (DBL). Many traffic classes display varying application-level performance according to the pattern of drops, even if the PDR is similar. In this paper we study a number of VANET scenarios and evaluate them with these three metrics.

Vehicular Ad-hoc Networks (VANETs) are an emerging class of Mobile Ad-hoc Network (MANETs) where nodes include both moving vehicles and fixed infrastructure. VANETs aim to make transportation systems more intelligent by sharing information to improve safety and comfort. Efficient and adaptive routing protocols are essential for achieving reliable and scalable network performance. However, routing in VANETs is challenging due to the frequent, high-speed movement of vehicles, which results in frequent network topology changes.

Our simulations are carried out using NS2 (for network traffic) and SUMO (for vehicular movement) simulators, with scenarios configured to reflect real-world conditions. The results show that OLSR is able to achieve a best DBL performance and demonstrates higher PDR performance comparing to AODV and GPSR under low network load. However, with GPSR, the network shows more stable PDR under medium and high network load. In term of delay OLSR is outperformed by GPSR.


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References


S. Zeadally, R. Hunt, Y.-S. Chen, A. Irwin, and A. Hassan, “Vehicular ad hoc networks (VANETS): status, results, and challenges,” Telecommun. Syst., vol. 50, no. 4, pp. 217–241, dec 2010.

F. Cunha, L. Villas, A. Boukerche, G. Maia, A. Viana, R. A. F. Mini, and A. A. F. Loureiro, “Data Communication in VANETs: Survey, Applications and Challenges,” Ad Hoc Networks, pp. 1–12, 2016.

C. Perkins and E. Royer, “Ad-hoc on-demand distance vector routing,” in Proc. WMCSA’99. Second IEEE Work. Mob. Comput. Syst. Appl., no. 3, 2009, pp. 90–100.

P. Jacquet, P. Muhlethaler, T. Clausen, A. Laouiti, A. Qayyum, and L. Viennot, “Optimized link state routing protocol for ad hoc networks,” in Proceedings. IEEE International Multi Topic Conference, 2001. IEEE INMIC 2001. Technology for the 21st Century., 2001, pp. 62–68.

B. Karp and H. T. Kung, “Gpsr,” Proc. 6th Annu. Int. Conf. Mob. Comput. Netw. - MobiCom ’00, pp. 243–254, 2000.

P. Rani, N. Sharma, and P. K. Singh, “Performance comparison of VANET routing protocols,” in 7th Int. Conf. Wirel. Commun. Netw. Mob. Comput. WiCOM 2011, 2011, pp. 1–4.

J. Zuo, Y. Wang, Y. Liu, and Y. Zhang, “Performance evaluation of routing protocol in VANET with vehicle-node density,” in 2010 6th Int. Conf. Wirel. Commun. Netw. Mob. Comput. WiCOM, 2010.

I. Khan and A. Qayyum, “Performance evaluation of AODV and OLSR in highly fading Vehicular Ad hoc Network environments,” in INMIC 2009 - 2009 IEEE 13th Int. Multitopic Conf., 2009, pp. 1–5.

R. Bala and C. R. Krishna, “Scenario based performance analysis of AODV and GPSR routing protocols in a VANET,” Proc. - 2015 IEEE Int. Conf. Comput. Intell. Commun. Technol. CICT 2015, pp. 432–437, 2015.

E. Spaho, M. Ikeda, L. Barolli, and F. Xhafa, “Performance comparison of OLSR and AODV protocols in a VANET crossroad scenario,” Lect. Notes Electr. Eng., vol. 253 LNEE, pp. 37–45, 2013.

E. Spaho, L. Barolli, G. Mino, F. Xhafa, V. Kolici, and R. Miho, “Performance Evaluation of AODV, OLSR and DYMO Protocols for Vehicular Networks Using CAVENET,” in 2010 13th Int. Conf. Network-Based Inf. Syst., 2010, pp. 527–534.

C. Haerri, J. and Filali, F. and Bonnet, “Performance comparison of AODV and OLSR in VANETs urban environments under realistic mobility patterns,” in Proc. 5th IFIP Mediterr. Ad-Hoc Netw. Work., no. i, 2006, pp. 14–17.

A. K. Ali, I. Phillips, and H. Yang, “Evaluating VANET Routing in Urban Environments,” 39th Int. Conf. Telecommun. Signal Process., pp. 60–63, 2016.

Crash Avoidance Metrics Partnership. Vehicle Safety Communications Consortium, Vehicle Safety Communications Project: Task 3 Final Report : Identify Intelligent Vehicle Safety Applications Enabled by DSRC. National Highway Traffic Safety Administration, 2004.

M. Behrisch, L. Bieker, J. Erdmann, and D. Krajzewicz, “SUMO - Simulation of Urban MObility - an Overview,” Proc. 3rd Int. Conf. Adv. Syst. Simul., no. c, pp. 63–68, 2011.

F. Bai, N. Sadagopan, and A. Helmy, “The IMPORTANT framework for analyzing the impact of mobility on performance of RouTing protocols for Adhoc NeTworks,” Ad Hoc Networks, vol. 1, no. 4, pp. 383–403, 2003.

M. Nakagami, “The m-distribution - A General Formula of Intensity Distribution of Rapid Fading,” Stat. Methods Radio Wave Propag., pp. 3–36, 1960.

L. Rubio, J. Reig, V. M. Rodrigo-Pearrocha, and N. Cardona, “A semi-deterministic propagation model for predicting short-term fading statistics in urban environments based on the Nakagami-m distribution,” AEU - Int. J. Electron. Commun., vol. 61, no. 9, pp. 595–604, 2007.




DOI: http://dx.doi.org/10.11601/ijates.v6i2.214

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