Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs

F. Al-dolaimy, F. Al-dolaimy and Rabei Raad Al, Rabei Raad Al and Noor Nabeel, Noor Nabeel and Wisam Subhi Al-Dayyeni, Wisam Subhi Al-Dayyeni and Fatima Hashim Abbas, Fatima Hashim Abbas and Hussein Muhi Hariz, Hussein Muhi Hariz and Salama A Mostafa, Salama A Mostafa and Mohammed Ahmed Jubair, Mohammed Ahmed Jubair (2023) Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs. International Journal of Intelligent Engineering and Systems, 16 (4). pp. 69-79.

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Vehicular ad hoc networks (VANETs) recently covered a wide range of intelligent transportation systems (ITSs) and applications. VANETs consist of convinced unique characteristics such as dynamic movement and high speed. Due to these characteristics, link failures occur, and delay and routing overhead is greatly increased, directly affecting the effectiveness, Quality of Service (QoS), and stability of VANETs. To achieve an efficient and reliable network performance, this paper proposes QoS Aware Hybrid Optimization for Improving Path Selection (HOIPSVANETs) in VANETs. This hybrid optimization combines the Improved ant colony optimization (ACO) and Effective Whale Optimization Algorithm (EWOA). The EWOA algorithm is used for initial optimal path selection, and ACO is used to find the best optimal solution to achieve effective communication in VANETs. This optimization technique is also applied to low-density, medium-density, and high-density scenarios, as it is compared with the earlier methods. During the experimentation process, our findings reveal no noticeable change in the performance of the earlier methods when applied to the low-density and medium-density scenarios. Still, the performance is gradually reduced when applied to the high-density scenario. On the other hand, the performance of the proposed approach is better for all three tested scenarios and demonstrates effective communication for the VANETs.

Item Type: Article
Uncontrolled Keywords: Vehicular ad hoc networks, Intelligent transportation systems, Quality of service, Hybrid optimization, Improved ant algorithm, Effective whale optimization algorithm
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Mr. Mohamad Zulkhibri Rahmad
Date Deposited: 27 Nov 2023 07:24
Last Modified: 27 Nov 2023 07:24
URI: http://eprints.uthm.edu.my/id/eprint/10490

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