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Title:	Genetic optimized location aided routing protocol for VANET based on rectangular estimation of position
Authors:	Ahmed Naeem Jasim (P74192)
Supervisor:	Ravie Chandren Muniyandi, Assoc. Prof. Dr.
Keywords:	Vehicular ad hoc networks (Computer networks) Routing (Computer network management) Universiti Kebangsaan Malaysia -- Dissertations Dissertations, Academic -- Malaysia
Issue Date:	25-May-2017
Description:	The Vehicle Ad Hoc Network (VANET) is a dynamic decentralized network consisting of wireless Mobile Nodes (MNs) that cooperatively perform the routing discovery without specific user administration. There are many routing protocols used in VANETs. One of them is location aided routing (LAR) routing protocol. The LAR protocol uses location information provided by GPS sensors to reduce the search space for the desired route. Limiting the search space results in fewer route discovery messages. Unfortunately, applying LAR directly in VANET types of network environment ignores two essential aspects of VANET nature. In other words, nodes in LAR predict destination node position while ignoring the fact that a pre-defined constraint on the destination node navigation is met. Secondly, nodes in LAR in use before selecting any route location information has high likelihood to be expired because of the fast speed of the nodes in the VANET environment. This paper presents an estimation based on a heuristic approach that has been developed to reject bad GPS location data and accept good ones based on a moving rectangular zone according to the nodes mobility model. The proposed approach is called Rectangle Aided LAR (RALAR). In addition, the RALAR protocol was optimized using a genetic algorithm by selecting the most suitable time out variable. The proposed algorithm has been compared with the Kalman Filter Aided LAR and LAR protocol in terms of the performance metrics using MATLAB 2015a. The performance of the proposed heuristic RALAR has outperformed the Kalman Filter Aided LAR and LAR protocol in terms of regular network performance measures in the VANET environment. The results showed that RALAR has achieved an improvement over the Kalman Filter Aided LAR in terms of packet delivery ratio of 4.7%, end-to-end delay of 60%, overhead of 15.5%, and 10.7% of energy consumption,“Certification of Master's/Doctoral Thesis” is not available,Master of Computer Science
Pages:	87
Call Number:	TE228.37.J347 2017 3 tesis
Publisher:	UKM, Bangi
Appears in Collections:	Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat

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