On-demand distance vector refinement-based car networking stable routing. (30th April 2020)

• Record Type: Journal Article
• Authors: Zhou, Shutao; Li, Chengxing; Yu, Hui
• Is Part Of: International journal of innovative computing and applications. Volume 11:Number 2/3(2020)
• Page Start: 79
• Page End: 83
• Publication Date: 2020-04-30
• Subjects: car networking -- distance vector refinement -- on-demand distance vector -- link quality -- communication path; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

Due to the high-speed movement of vehicles and obstacles in urban scenes, the communication paths between vehicles become extremely fragile. Specific to the routing problem of VANETs, a path criterion-based on-demand distance vector PA-AODV routing algorithm is proposed. The PA-AODV routing algorithm makes full use of the characteristics of AODV routing, and improves its routing decision. By calculating the path criterion weight and preferentially selecting the path with small weight for data transmission, the path stability is thus improved. The experimental data show that the proposed PA-AODV routing reduces the data packets loss rate and also shortens the end-to-end transmission delay.