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Adaptive-ARW: Adaptive Autoregressive Whale Optimization Algorithm for Traffic-Aware Routing in Urban VANET

Deepak Rewadkar1 , Dharmpal Doye2

  1. Department Information Technology, Government Polytechnic Awasari, Pune, India.
  2. Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded, India.

Correspondence should be addressed to: deepakrewadkar27@gmail.com.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-3 , Page no. 40-49, Mar-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i3.4049

Online published on Mar 30, 2018

Copyright © Deepak Rewadkar, Dharmpal Doye . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Deepak Rewadkar, Dharmpal Doye, “Adaptive-ARW: Adaptive Autoregressive Whale Optimization Algorithm for Traffic-Aware Routing in Urban VANET,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.3, pp.40-49, 2018.

MLA Style Citation: Deepak Rewadkar, Dharmpal Doye "Adaptive-ARW: Adaptive Autoregressive Whale Optimization Algorithm for Traffic-Aware Routing in Urban VANET." International Journal of Computer Sciences and Engineering 6.3 (2018): 40-49.

APA Style Citation: Deepak Rewadkar, Dharmpal Doye, (2018). Adaptive-ARW: Adaptive Autoregressive Whale Optimization Algorithm for Traffic-Aware Routing in Urban VANET. International Journal of Computer Sciences and Engineering, 6(3), 40-49.

BibTex Style Citation:
@article{Rewadkar_2018,
author = {Deepak Rewadkar, Dharmpal Doye},
title = {Adaptive-ARW: Adaptive Autoregressive Whale Optimization Algorithm for Traffic-Aware Routing in Urban VANET},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2018},
volume = {6},
Issue = {3},
month = {3},
year = {2018},
issn = {2347-2693},
pages = {40-49},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1758},
doi = {https://doi.org/10.26438/ijcse/v6i3.4049}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i3.4049}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1758
TI - Adaptive-ARW: Adaptive Autoregressive Whale Optimization Algorithm for Traffic-Aware Routing in Urban VANET
T2 - International Journal of Computer Sciences and Engineering
AU - Deepak Rewadkar, Dharmpal Doye
PY - 2018
DA - 2018/03/30
PB - IJCSE, Indore, INDIA
SP - 40-49
IS - 3
VL - 6
SN - 2347-2693
ER -

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Abstract

A traffic-aware routing in VANET is a prime step in transmitting the long data for applications. Researchers’ address that the traditionally used routing protocols employed in Mobile Ad Hoc Networks are not suitable for routing in VANET, as VANETs differ from MANETs in the mobility model and environment. The demand to develop a traffic-aware protocol in VANET initiated to propose a routing protocol, termed as Adaptive Autoregressive Whale Optimization algorithm (Adaptive-ARW). The main goal of the proposed algorithm is to select the optimal path for performing routing in VANETs, for which the traffic required to be predicted. For predicting the traffic in the road segment, Exponential Weighed Moving Average (EWMA) is employed that predicts the traffic based on the average vehicle speed and the average traffic density. The minimum values of average speed and vehicles average traffic density to the less traffic density. Using the predicted traffic, the routing paths are generated, and the optimal paths are selected using the proposed algorithm that exhibits adaptive property. The analysis of the proposed algorithm provides the End-to-End delay, distance, average traffic density, and throughput of 2.938, 2.08, 0.0095, and 0.1354, respectively.

Key-Words / Index Term

Exponential Weighed Moving Average (EWMA), End-to-End Delay (EED), Whale Optimization algorithm (WOA), Autoregressive Model, Adaptive property

References

[1] Mayouf, Y. RafidBahar, M. Ismail, N.F. Abdullah, A.W.A. Wahab, O.A. Mahdi, S. Khan, and K.K.R. Choo. "Efficient and Stable Routing Algorithm Based on User Mobility and Node Density in Urban Vehicular Network" , PloS one, vol.11, no.11, 2016.
[2] A. Ibrahim, A. Ahmed; A.Gani, S.A. Hamid; S. Khan, N. Guizani, KwangmanKo, "Intersection-based Distance and Traffic-Aware Routing (IDTAR) protocol for smart vehicular communication", In Proceedings of the 13th International Wireless Communications and Mobile Computing Conference (IWCMC), pp.489 - 493, 2017.
[3] H.T. Cheng, H. Shan, W. Zhuang, “Infotainment and road safety servicesupport in vehicular networking: From a communication perspective”, Mechanical Systems and Signal Processing, vol.25, no.6,pp.2020−2038, 2011.
[4] Y. Ding, Y. Liu, X. Gong, W. Wang, "Road traffic and geography topology based opportunistic routing for VANETs", The Journal of China Universities of Posts and Telecommunications, vol.21, no.4, pp.32-39, August 2014.
[5] Kosch, Timo, Adler, Christian, Eichler, Stephan, Schroth, Christoph, Strassberger, Markus,"The Scalability Problem of Vehicular Ad Hoc Networks and How to Solve it", IEEE Wireless Communications Magazine, vol.13, no.5, pp.22-28, 2006.
[6] Khekare, S. Ganesh. and V. Apeksha, Sakhare, "A smart city framework for intelligent traffic system using VANET", In Proceedings of the IEEE International Multi-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s), pp. 302-305, 2013.
[7] Mamta Devi, Dr Rakesh Kumar, and Er Nidhi Bhatla, "Secure and Enhanced Vehicular Ad-Hoc Networks Using DSR Protocol and BFOA Algorithm," International Journal on Computer Science and Engineering (IJCSE), Vol. 9 No.8, pp. 506-516, August 2017.
[8] M. Jerbi, S.M. Senouci., R. Meraihi, and Y.G. Doudane,"An improved vehicular ad hoc routing protocol for city environments", In Proceedings of the IEEE International Conference on Communications (ICC 07), pp. 3972–3979, June 2007.
[9] C. Liu, Y. Shu, O. Yang, Z. Xia and R. Xia, “SDR: A Stable Direction-Based Routing for Vehicular Ad Hoc Networks”, Wireless Personal Communication, vol. 73, no. 3, pp. 1298-1308, 2013.
[10] C. Li, L. Wang, Y. He, C. Zhao, H. Lin, and L. Zhu, "A link state aware geographic routing protocol for vehicular ad hoc networks", EURASIP Journal on Wireless Communications and Networking, pp.176, 2014.
[11] C.C. Lo, and Y.H. Kuo, “Traffic-aware routing protocol with cooperative coverage-oriented information collection method for VANET", IET Communications, vol.11, no.3, pp.444 - 450, 2017.
[12] Y. Zhu, Y. Qiu, Y. Wu, M. Gao, B. Li and Y. Hu, “On adaptive routing in urban vehicular networks”, In Proceedings of IEEE Global Communication Conference, pp. 1593-1598, 2013.
[13] D. Kumari, N. Venkatramana, S.B. Srikantaiah, J. Moodabidri, "SCGRP: SDN-enabled connectivity-aware geographical routing protocol of VANETs for urban environment", IET Networks, vol.6, no.5, pp.102 - 111, 2017.
[14] S. Mirjalili, A. Lewis, "The Whale Optimization Algorithm", Advances in Engineering Software, vol. 95, pp. 51–67, 2016.
[15] M. Balachandra, K.V. Prema, K. Makkithaya, "Multiconstrained and multipath QoS aware routing protocol for MANETs", Wireless Networks, vol. 20, no.8, pp. 2395–2408, November 2014.
[16] A.K. Yadav, S. Tripathi, "QMRPRNS: Design of QoS multicast routing protocol using reliable node selection scheme for MANETs", Peer-to-Peer Networking and Applications, pp. 1–13, Feb 2016.
[17] R.F. Engle, S. Manganelli, "CAViaR: Conditional Value at Risk by Quantile Regression", Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pp. 367-381, October 1999.
[18] M.A. Togou, AbdelhakimHafid, and LyesKhoukhi, “SCRP: Stable CDS-Based Routing Protocol for Urban Vehicular Ad Hoc Networks”, IEEE Transactions on Intelligent Transportation Systems, vol. 17, no. 5, pp. 1298-1307, 2015.
[19] B. Wu, C. Qian, W. Ni, S. Fan, "The improvement of glow worm swarm optimization for continuous optimization problems", Expert Systems with Applications, vol. 39, no. 7, pp. 6335–6342, 2012.