In recent years, various routing metrics such as throughput, end-to-end delay, packet delivery ratio, path duration, and so forth have been used to evaluate the performance of routing protocols in VANETs. Among these routing metrics, path duration is one of the most influential metrics. Highly mobile vehicles cause frequent topology change in vehicular network environment that ultimately affects the path duration. In this paper, we have derived a mathematical model to estimate path duration using border node-based most forward progress within radius (B-MFR), a position based routing protocol. The mathematical model for estimation of path duration consists of probability of finding next-hop node in forwarding region, estimation of expected number of hops, probability distribution of velocity of nodes, and link duration between each intermediate pair of nodes. The analytical results for the path duration estimation model have been obtained using MATLAB. The model for path duration estimation has been simulated in NS2. Each of the analytical results has been verified through respective simulation results. The result analysis clearly reveals that path duration increases with the increase in transmission range and node density and decreases with the increase in the number of hops in the path and velocity of the nodes. 1. Introduction The intelligent transport system (ITS) has been working to make the road safer and efficient to cope up with increasing number of on-road vehicles day by day. The number of accidents on the roads is continuously increasing due to high growth in on-road vehicle population. The increasing number of accidents has become an issue of concern worldwide. It has made the roads vulnerable and threatening as every year millions of people are dying in accidents throughout the world. A modern network concept, VANETs, has become the hope for providing safer and well-organized transportation in near future [1]. In VANETs, routing is the process of finding optimal path for information forwarding between source and destination node. Position-based routing protocols have become one of the most investigated choices among researches due to geographic region sharing of on-road vehicles [2–7]. In position-based routing, forwarding of information is performed either through direct communication or through intermediate nodes between source and destination node. The intermediate nodes are high speed moving vehicles in VANETs that act as router during forwarding of information from source to destination. Due to ad hoc network architecture, no fixed
References
[1]
WHO, Status Report on Road Safety, World Health Organization (WHO), Geneva, Switzerland, 2013.
[2]
T. Taleb, E. Sakhaee, A. Jamalipour, K. Hashimoto, N. Kato, and Y. Nemoto, “A stable routing protocol to support ITS services in VANET networks,” IEEE Transactions on Vehicular Technology, vol. 56, no. 6, pp. 3337–3347, 2007.
[3]
O. Kaiwartya and S. Kumar, “Geocast routing: Recent advances and future challenges in vehicular adhoc networks,” in Proceedings of Signal Processing and Integrated Networks (SPIN '14), pp. 291–296, 2014.
[4]
O. Kaiwartya and S. Kumar, “Cache agent based geocasting (CAG) in VANETs,” International Journal of Information and Communication Technology. In press.
[5]
O. Kaiwartya, S. Kumar, and R. Kasana, “Traffic light based time stable geocast (T-TSG) routing for urban VANETs,” in Proceedings of the 6th International Conference on Contemporary Computing (IC3 '13), pp. 113–117, 2013.
[6]
O. Kaiwartya and S. Kumar, “GeoPSO: geocasting through particle swarm optimization in vehicular adhoc networks,” in Proceedings of Information Systems and Design of Communication (ISDOC '14), ACM, May 2014.
[7]
O. Kaiwartya and S. Kumar, “Enhanced caching for geocast routing in vehicular Ad-Hoc networks (ECGR),” in Proceedings of the International Conference on Advanced Computing, Networking and Informatics (ICACNI '13), vol. 243, pp. 213–220, Springer, 2013.
[8]
J. J. Blum, A. Eskandarian, and L. J. Huffman, “Challenges of intervehicle Ad Hoc networks,” IEEE Transactions on Intelligent Transportation Systems, vol. 5, no. 4, pp. 347–351, 2004.
[9]
W. Alasmary and W. Zhuang, “Mobility impact in IEEE 802.11p infrastructure less vehicular networks,” Ad Hoc Networks, vol. 10, no. 2, pp. 222–230, 2012.
[10]
R. J. La and Y. Han, “Distribution of path durations in mobile ad hoc networks and path selection,” IEEE/ACM Transactions on Networking, vol. 15, no. 5, pp. 993–1006, 2007.
[11]
“DSRC Standards: What's New?” ITS Standards Advisory number 3, US Department of Transportation, http://www.its.dot.gov/DSRC/.
[12]
R. Popescu-Zeletin, I. Radusch, and M. A. Rigani, Vehicular-2-X Communication: State-Of-The-Art and Research in Mobile Vehicular Ad Hoc Networks, Springer, New York, NY, USA, 2010.
[13]
A. F. Molisch, F. Tufvesson, J. Karedal, and C. F. Mecklenbr？uker, “A survey on vehicle-to-vehicle propagation channels,” IEEE Wireless Communications, vol. 16, no. 6, pp. 12–22, 2009.
[14]
J. Gozalvez, M. Sepulcre, and R. Bauza, “IEEE 802.11p vehicle to infrastructure communications in urban environments,” IEEE Communications Magazine, vol. 50, no. 5, pp. 176–183, 2012.
[15]
N. Sadagopan, F. Bai, B. Krishnamachari, and A. Helmy, “PATHS: analysis of PATH duration statistics and their impact on reactive MANET routing protocols,” in Proceedings of the 4th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MOBIHOC '03), pp. 245–256, June 2003.
[16]
G. Lim, K. Shin, S. Lee, H. Yoon, and J. S. Ma, “Link stability and route lifetime in ad-hoc networks,” EURASIP Journal on Wireless Communications and Networking, pp. 1–6, 2007.
[17]
Y. Han and R. J. La, “Maximizing path durations in mobile ad-hoc networks,” in Proceedings of the 40th Annual Conference on Information Sciences and Systems (CISS '06), pp. 26–31, Princeton, NJ, USA, March 2006.
[18]
S. De, A. Caruso, T. Chaira, and S. Chessa, “Bounds on hop distance in greedy routing approach in wireless ad hoc networks,” International Journal of Wireless and Mobile Computing, vol. 1, no. 2, pp. 131–140, 2006.
[19]
R. S. Raw and D. K. Lobiyal, “B-MFR routing protocol for vehicular ad hoc networks,” in Proceedings of the International Conference on Networking and Information Technology (ICNIT '10), pp. 420–423, Manila, Philippines, June 2010.
[20]
R. S. Raw and D. K. Lobiyal, “E-DIR: a directional routing protocol for VANETs in a city traffic environment,” International Journal of Information and Communication Technology, vol. 3, no. 3, pp. 242–257, 2011.
[21]
S. Ukkusuri and L. Du, “Geometric connectivity of vehicular ad hoc networks: analytical characterization,” Transportation Research Part C: Emerging Technologies, vol. 16, no. 5, pp. 615–634, 2008.
[22]
S. M. Harb and J. McNair, “Analytical study of the expected number of hops in wireless Ad Hoc network,” in Wireless Algorithms, Systems, and Applications, vol. 5258 of Lecture Notes in Computer Science, pp. 63–71, 2008.
[23]
K. Namuduri and R. Pendse, “Analytical estimation of path duration in mobile ad hoc networks,” IEEE Sensors Journal, vol. 12, no. 6, pp. 1828–1835, 2012.
[24]
R. S. Raw and S. Das, “Performance analysis of P-GEDIR protocol for vehicular ad hoc network in urban traffic environments,” Wireless Personal Communications, vol. 68, no. 1, pp. 65–78, 2013.
[25]
H. Ghafoor, K. Insoo, and G. Nasirud-Din, “Neighboring and connectivity-aware routing in VANETs,” The Scientific World Journal, vol. 2014, Article ID 789247, 10 pages, 2014.
[26]
C. Chen, Y. Jin, Q. Pei, and N. Zhang, “A connectivity-aware intersection-based routing in VANETs,” EURASIP Journal on Wireless Communications and Networking, vol. 2014, article 42, 2014.
[27]
F. K. Karnadi, Z. H. Mo, and K. Lan, “Rapid generation of realistic mobility models for VANET,” in Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC '07), pp. 2508–2513, IEEE, March 2007.
