Analysis of Job Completion Time in Vehicular Cloud Under Concurrent Task Execution

Pooling idle computing resources from stationary and computationally powerful vehicles at a nearby parking lot is one way to meet increasing computation demands from mobile devices at the network’s edge. This new computing paradigm is called vehicular cloud (VC). Despite the research in performance modeling of VC having gained increasing interest in recent years, a tractable solution for job completion time under concurrent task execution has yet to be seen. Thus, this work investigates the computation capabilities of a VC by analytically determining job completion time when the VC simultaneously executes several tasks. Under several stochastics assumptions, we derive the probability density functions of completion times of the tasks, which also include the job completion time and their first moments. Finally, we present the numerical results for the analysis and the simulation results to show the correctness of the work.