Improvising the Performance of Nomadic Vehicular Cloud by Reducing Task Migrations

Abstract

The introduction of vehicle clouds, whose processing, sensor, and networking capabilities are forcefully dispersed to authorised users, is prompted by the rising popularity of cloud computing. When certain vehicles enter and exit the cloud, new computational resources become available, creating an unpredictable environment that makes measuring key performance indicators like job completion time very challenging. As part of a Nomadic Vehicular Cloud (NVC) system that includes automobiles on a roadway, our main contribution is to reduce job migrations. It has been calculated how long it will take to complete the task without spending more money because of vehicular cloud operations. The simulation outcome showed that the suggested approach successfully reduces task completion time and enhances NVC performance. According to the performance data, our technique shortens work completion time by 25% compare to other approaches.