A clustering approach to improve VANETs performance

Abstract

Vehicular ad-hoc network (VANET) is a technique that uses cars moved in cities or highways as nodes in wireless networks. Each car in these networks works as a router and allows cars in the range to communicate with each other. As a result of this movement, some cars will become out of range, but these networks can connect to the internet and the cars in these networks can connect to each other. This research proposes a unique clustering strategy to improve the performance of these networks by making their clusters more stable. One of the biggest problems these networks face is traffic data, which consumes network resources. Agent based modeling (ABM) evaluates better networks. The evaluation showed that the proposed strategy surpasses earlier techniques in reachability and throughput, but ad hoc on-demand distance vector (AODV) (on-demand/reactive) outperforms it in total traffic received since our hybrid approach needs more traffic than AODV.

Optimal Drone Nodes Deployment to Maximize Coverage and Energy in WSNs Using Genetic Algorithms

“…In [18], the research suggest unique compilation strategy to enhance performance of Wireless Sensor Networks due making their sets more stable. One of most important problem that face Wireless Sensor Networks is traffic data, which is consume network resources.…”

Big data vehicle density management in vehicular ad-hoc network

“…The experiment evaluation proves a good transfer performance amelioration of the proposed solution. On the other hand, Khudhair et al [26], they establish a clustering strategy to ameliorate the performance of wireless networks and having the clusters more stable.…”