TY - GEN
T1 - Heuristic Based Routing Algorithms for Vehicular Network Using Tabu Search and ANN
AU - Ignatious, Henry Alexander
AU - Harous, Saad
AU - Hesham-El-Sayed,
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12/12
Y1 - 2020/12/12
N2 - Efficient routing to guide the vehicles to reach their destinations is a challenging problem in vehicular networks. Many solutions have been proposed in the literature to address the routing problem in vehicular networks. However, most of these solutions are graph-based and do not properly address the dynamic characteristics of vehicular networks. This paper proposes two novel heuristic routing algorithms based on Tabu search and Neural Networks. The proposed algorithms are evaluated and their findings are presented using the UK RTA based roadside dataset. Experimental results along with the comparative analysis made with other related studies are provided to prove the efficiency of the proposed algorithms. The findings highlight the superior performance achieved by the suggested routing algorithms.
AB - Efficient routing to guide the vehicles to reach their destinations is a challenging problem in vehicular networks. Many solutions have been proposed in the literature to address the routing problem in vehicular networks. However, most of these solutions are graph-based and do not properly address the dynamic characteristics of vehicular networks. This paper proposes two novel heuristic routing algorithms based on Tabu search and Neural Networks. The proposed algorithms are evaluated and their findings are presented using the UK RTA based roadside dataset. Experimental results along with the comparative analysis made with other related studies are provided to prove the efficiency of the proposed algorithms. The findings highlight the superior performance achieved by the suggested routing algorithms.
KW - Artificial Neural Networks (ANN)
KW - Tabu Search
KW - Vehicular ad hoc network (V ANET)
UR - http://www.scopus.com/inward/record.url?scp=85101425088&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85101425088&partnerID=8YFLogxK
U2 - 10.1109/GCAIoT51063.2020.9345893
DO - 10.1109/GCAIoT51063.2020.9345893
M3 - Conference contribution
AN - SCOPUS:85101425088
T3 - 2020 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2020
BT - 2020 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2020
Y2 - 12 December 2020 through 16 December 2020
ER -