International Journal of Modern Education and Computer Science (IJMECS)
IJMECS Vol. 8, No. 1, 8 Jan. 2016
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Favorable Trail Detection using ACO-Bellman Algorithm in VANETs
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Author(s)
Yogesh
1,*
Parminder Singh
1
Index Terms
Vehicular Ad-hoc Networks, IEEE 802.11, Ant Colonization Optimization, Bellman Ford Algorithm, Dynamic source routing, Ad-hoc On Demand Vector
Abstract
Vehicular ad hoc networks (VANETs) are the networks, which configured themselves, where the nodes are moving vehicles. These provide the communications required to deploy Intelligent Transportation Systems (ITS). A major dispute in VANETs is distribution of efficient and computable information because during communication nodes may leave or join the network dynamically. There is no guarantee about node availability at any given time, which leads to traffic problem, congestion problem. Therefore trailing the favorable path is a challengeable issue. Multiple routing algorithms have been developed for routing solution. In this paper the swarm-based algorithm has been presented, which helps to find out the optimal route using Bellman Ford algorithm. Ant colonization searches out the path using pheromones level. Higher the pheromone count of a route gives the optimal choice of path that can be used for packet delivery. Bellman Ford Algorithm optimizes the paths found by Ant Colony Optimization (ACO) by comparing the distance of source to all the nodes of network or cost given to the networks.
Cite This Paper
Yogesh, Parminder Singh,"Favorable Trail Detection using ACO-Bellman Algorithm in VANETs", International Journal of Modern Education and Computer Science(IJMECS), Vol.8, No.1, pp.33-39, 2016.DOI: 10.5815/ijmecs.2016.01.05
Reference
[1] Mrs. Padma .P, Mr. R. Suresh. “Literature Survey on latest research issue in MANET” International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), vol. 2, issue 7, July 2013.
[2] Fan, Peng, James G. Haran, John Dillenburg, and Peter C. Nelson. "Cluster-based framework in vehicular ad-hoc networks." In Ad-hoc, mobile, and wireless networks, pp. 32-42. Springer Berlin Heidelberg, 2005.
[3] Karnadi, Feliz Kristianto, Zhi Hai Mo, and Kun-chan Lan. "Rapid generation of realistic mobility models for VANET." In Wireless Communications and Networking Conference, 2007. WCNC 2007. IEEE, pp. 2506-2511. IEEE, 2007.
[4] Kaur, Navroop, Harjit Singh, and Amandeep Nagpal. “Pros and Cons: Various Routing Protocols based on VANET's: A Survey.” International Journal of Computer Applications 106, no. 8 (2014).
[5] Silva, Rodrigo, Heitor Silvério Lopes, and Walter Godoy. "A Heuristic Algorithm Based on Ant Colony Optimization for Multi-objective Routing in Vehicle Ad Hoc Networks." In Computational Intelligence and 11th Brazilian Congress on Computational Intelligence (BRICS-CCI & CBIC), 2013 BRICS Congress on, pp. 435-440. IEEE, 2013.
[6] Daniel jiang, Luca Delgrossi, “IEEE 802.11p: towards an international standard for wireless access in vehicular environments” vol. 3, pp. 2036-2040, IEEE, 2008.
[7] JagdeepKaur, Er. Parminder Singh “Performance comparison between unicast and multicast protocols in VANET’s” International journal of advanced technology & engineering research, vol-3, pp. 109-115, Jan 2013.
[8] Lee, Kevin C., Uichin Lee, and Mario Gerla. "Survey of routing protocols in vehicular ad hoc networks." Advances in vehicular ad-hoc networks: Developments and challenges (2010): 149-170.
[9] Shubhrant Jibhkate, Smith khare, Ashwin Kamble, Amutha Jayakumar “Advanced Adaptive Routing Protocol Algorithm for Highway and City Scenarios in VANET” in International journal of Innovative Research in Computer and Communication Engineering (IJIRCCE) vol.3, issue 3, March 2015.
[10] Dweepna Garg & Parth Gohil, “Ant Colony Optimized Routing for Mobile Adhoc Networks (Manet)” International Journal of Smart Sensors and Ad Hoc Networks, vol-2, pp. 8-13, 2012.
[11] Jabbarpour, Mohammad Reza, Ali Jalooli, Erfan Shaghaghi, Rafidah Md Noor, Leon Rothkrantz, Rashid Hafeez Khokhar, and Nor Badrul Anuar. "Ant-based vehicle congestion avoidance system using vehicular networks." Engineering Applications of Artificial Intelligence 36 (2014): 303-319.
[12] Abdel-Moniem, Ahmed M., Marghny H. Mohamed, and Abdel-Rahman Hedar. "An ant colony optimization algorithm for the mobile ad hoc network routing problem based on AODV protocol." In Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on, pp. 1332-1337. IEEE, 2010.
[13] Martins, José Alex Pontes, Sergio Luis OB Correia, and Joaquim Celestino. "Ant-DYMO: a bio-inspired algorithm for MANETS." In Telecommunications (ICT), 2010 IEEE 17th International Conference on, pp. 748-754. IEEE, 2010.
[14] Roy, Bibhash, Suman Banik, Parthi Dey, Sugata Sanyal, and Nabendu Chaki. "Ant colony based routing for mobile ad-hoc networks towards improved quality of services." Journal of Emerging Trends in Computing and Information Sciences 3, no. 1 (2012): 10-14.
[15] Jaya Sehgal, poonam Arora “Delay Optimization in VANET using Ant Colony Optiumization and WI-MAX” in International journal of advanced Research in Electrical, Electroinics and Instrumentation Engineering, vol. 3, issue 8, August 2014.
[16] Rao, DB Jagannadha, Karnam Sreenu, and Parsi Kalpana. "A Study on Dynamic Source Routing Protocol for Wireless Ad Hoc Networks." International Journal of Advanced Research in Computer and Communication Engineering 1, no. 8 (2012): 2319-5940.
[17] Sultana, Sharmin, Salma Begum, Nazma Tara, and Ahsan Raja Chowdhury. "Enhanced-DSR: A New Approach to Improve Performance of DSR Algorithm." International Journal of Computer Science and Information Technology 2, no. 2 (2010): 113-123.
[18] Monika, S. Batish, and Amardeep Dhiman. "Comparative Study of AODV, DSDV and DSR Routing Protocols in Vehicular Network Using EstiNet Simulator." International Journal of Scientific & Engineering Research 3, no. 6 (2012): 1.
[19] Bellman Ford Algorithm available at: “http://en.m.wikipedia.org/wiki/bellman” (last accessed 26th august 2015).
[20] Dynamic Programming | set Set 23 (Bellman-Ford Algorithm) “http://www.geeksforgeeks.org/dynamic-programming-set-23-bellman ford algorithm” (last accessed 26th august 2015).
[21] Sangita Roy, Samir Biswas, Sheli Sinha Chaudhuri “Nature-Inspired Swarm Intelligence and Its Applications” I.J Modern Education and Computer Science, vol. 12, pp. 55-65, 2014.
[22] Sangita Roy, Sheli Sinha Chaudhuri “Bio-inspired Ant Algorithms: A review” I.J Modern Education and Computer Science, vol. 4, pp. 25-35, 2013.