Bee Optimized Fuzzy Geographical Routing Protocol for VANET

Authors: P. Saravanan, T. Arunkumar

Abstract:

Vehicular Adhoc Network (VANET) is a new technology which aims to ensure intelligent inter-vehicle communications, seamless internet connectivity leading to improved road safety, essential alerts, and access to comfort and entertainment. VANET operations are hindered by mobile node’s (vehicles) uncertain mobility. Routing algorithms use metrics to evaluate which path is best for packets to travel. Metrics like path length (hop count), delay, reliability, bandwidth, and load determine optimal route. The proposed scheme exploits link quality, traffic density, and intersections as routing metrics to determine next hop. This study enhances Geographical Routing Protocol (GRP) using fuzzy controllers while rules are optimized with Bee Swarm Optimization (BSO). Simulations results are compared to conventional GRP.

Keywords: Bee Swarm Optimization (BSO), Geographical Routing Protocol (GRP), Vehicular Adhoc Network (VANET).

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1099640

References:

[1] Paul, B., Ibrahim, M., Bikas, M., & Naser, A. (2012). VANET Routing Protocols: Pros and Cons. arXiv preprint arXiv:1204.1201.
[2] Al-Sultan, S., Al-Doori, M. M., Al-Bayatti, A. H., & Zedan, H. (2013). A comprehensive survey on vehicular Ad Hoc network. Journal of network and computer applications.
[3] Mustafa, B., & Raja, U. W. (2010). Issues of Routing in VANET. School of computing at Blekinge Institute of Technology.
[4] Sharma, N., & Thakur, J. (2013). Performance analysis of AODV &GPSR routing protocol in VANET. International Journal of Computer Science & Engineering Technology (IJCSET), 4(2).
[5] Venkatesh., A, Indra., R, Murali., (2014). Routing Protocols for Vehicular Adhoc Networks (VANETs): A Review. Journal of Emerging Trends in Computing and Information Sciences, 5(1), 25-43.
[6] Lee, K. C., Lee, U., & Gerla, M. (2010). Survey of routing protocols in vehicular ad hoc networks. Advances in vehicular ad-hoc networks: Developments and challenges, 149-170.
[7] Kakarla, J., Sathya, S. S., & Laxmi, B. G. (2011). A Survey on Routing Protocols and its Issues in VANET.
[8] Sachan, G., Sharma, D. K., Tyagi, K., & Prasad, A. (2013). Enhanced Energy Aware Geographic Routing Protocol in MANET: A Review.
[9] Maghsoudlou, A., St-Hilaire, M., & Kunz, T. (2011). A Survey on Geographic Routing Protocols for Mobile Ad hoc Networks. Systems and Computer Engineering, Technical Report SCE-11-03.–Carleton University.–2011.–49 p.
[10] Menon, V. G., & PM, J. P. (2013). Performance analysis of geographic routing protocols in highly mobile ad hoc network. Journal of Theoretical & Applied Information Technology, 53(1).
[11] Jerbi, M., Senouci, S. M., & Ghamri-Doudane, Y. (2006). Towards efficient routing in vehicular Ad Hoc networks. In proceedings of the 3rd IEEE international workshop on Mobile Computing and Networking.
[12] Mohammadzadeh, H., & Bigdello, S. J. (2013). UTCARP: Urban Traffic Control Aware Routing Protocol. International Journal.
[13] Raw, R. S., & Das, S. (2011). Performance comparison of Position based routing Protocols in vehicle-to-vehicle (V2V) Communication. International Journal of Engineering Science and Technology, 3(1), 435- 444.
[14] Antunes, J. N. (2011). Fuzzy Logic Based Quality of Service Models Relatório Final.
[15] Xia, F., Zhao, W., Sun, Y., & Tian, Y. C. (2007). Fuzzy logic control based QoS management in wireless sensor/actuator networks. Sensors, 7(12), 3179-3191.
[16] Ishibuchi, H., & Yamamoto, T. (2002, July). Fuzzy Rule Selection By Data Mining Criteria And Genetic Algorithms. In GECCO (pp. 399- 406).
[17] Ishibuchi, H., & Nojima, Y. (2005). Multiobjective Formulations of Fuzzy Rule-Based Classification System Design. In EUSFLAT Conf. (pp. 285-290).
[18] Wang, W., Xie, F., & Chatterjee, M. (2009). Small-scale and large-scale routing in vehicular ad hoc networks. Vehicular Technology, IEEE Transactions on, 58(9), 5200-5213.
[19] Pandit, K., Ghosal, D., Zhang, H. M., & Chuah, C. N. (2013). Adaptive Traffic Signal Control With Vehicular Ad hoc Networks. IEEE T. Vehicular Technology, 62(4), 1459-1471.
[20] Li, Y., Jin, D., Wang, Z., Zeng, L., & Chen, S. (2013). Exponential and power law distribution of contact duration in urban vehicular ad hoc networks. Signal Processing Letters, IEEE, 20(1), 110-113.
[21] Sou, S. I. (2013). Modeling emergency messaging for car accident over dichotomized headway model in vehicular Ad-hoc networks. IEEE transactions on communications, 61(2), 802-812.
[22] Vaqar, S. A., & Basir, O. (2009). Traffic pattern detection in a partially deployed vehicular ad hoc network of vehicles. Wireless Communications, IEEE, 16(6), 40-46.
[23] Khabazian, M., Mehmet-Ali, M., & Aissa, S. (2013). Analysis of continuous communication availability in vehicular ad hoc networks. Systems Journal, IEEE, 7(1), 137-150.
[24] Salahuddin, M. A., Al-Fuqaha, A., & Guizani, M. (2014). Exploiting Context Severity to Achieve Opportunistic Service Differentiation in Vehicular Ad hoc Networks.
[25] Hafeez, K. A., Zhao, L., Mark, J. W., Shen, X., & Niu, Z. (2013). Distributed Multichannel and Mobility-Aware Cluster-Based MAC Protocol for Vehicular Ad Hoc Networks. Vehicular Technology, IEEE Transactions on, 62(8), 3886-3902.
[26] Mohimani, G. H., Ashtiani, F., Javanmard, A., & Hamdi, M. (2009). Mobility modeling, spatial traffic distribution, and probability of connectivity for sparse and dense vehicular ad hoc networks. Vehicular Technology, IEEE Transactions on, 58(4), 1998-2007.
[27] Sun, J., Zhang, C., Zhang, Y., & Fang, Y. (2010). An identity-based security system for user privacy in vehicular ad hoc networks. Parallel and Distributed Systems, IEEE Transactions on, 21(9), 1227-1239.
[28] Dhurandher, S. K., Misra, S., Obaidat, M. S., Gupta, M., Diwakar, K., & Gupta, P. (2010). Efficient angular routing protocol for inter-vehicular communication in vehicular ad hoc networks. Communications, IET, 4(7), 826-836.
[29] Taynnan Albuquerque de Oliveira Barros, M., Cezar de Morais Gomes, R., & Fabiano Batista Ferreira da Costa, A. (2013). A Top-down Multilayer Routing Architecture for Vehicular Ad-Hoc Networks. Latin America Transactions, IEEE (Revista IEEE America Latina), 11(6), 1344-1352.
[30] Nzouonta, J., Rajgure, N., Wang, G., & Borcea, C. (2009). VANET routing on city roads using real-time vehicular traffic information. Vehicular Technology, IEEE Transactions on, 58(7), 3609-3626.
[31] Goonewardene, R. T., Ali, F. H., & Stipidis, E. L. I. A. S. (2009). Robust mobility adaptive clustering scheme with support for geographic routing for vehicular ad hoc networks. Intelligent Transport Systems, IET, 3(2), 148-158.
[32] Al-Rabayah, M., & Malaney, R. (2012). A new scalable hybrid routing protocol for VANETs. Vehicular Technology, IEEE Transactions on, 61(6), 2625-2635.
[33] Booysen, M. J., Zeadally, S., & Van Rooyen, G. J. (2011). Survey of media access control protocols for vehicular ad hoc networks. IET communications, 5(11), 1619-1631.
[34] Alcalá, R., Gacto, M. J., Herrera, F., & Alcalá-Fdez, J. (2007). A multiobjective genetic algorithm for tuning and rule selection to obtain accurate and compact linguistic fuzzy rule-based systems. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 15(05), 539-557.
[35] Dervis, K. and A. Bahriye, 2009. A comparative study of artificial bee colony algorithm. Appl. Math. Comput., 214: 108-132.
[36] Hemalatha, K. S. K. M. (2014). An Innovative Potential on Rule Optimization using Fuzzy Artificial Bee Colony.
[37] Niittymäki, J. (2001). General fuzzy rule base for isolated traffic signal control-rule formulation. Transportation Planning and Technology, 24(3), 227-247..