Research On Task Allocation Strategy Based On QoS Of Autonomous Vehicular Cloud On The Highway

Vehicles with computing resources can be aggregated by Autonomous Vehicular Cloud(AVC),and provide on resource distribution demand just like cloud computing.Reasonable allocation of tasks,on the one hand,can make a lot of idle resources in the AVC to be fully utilized,and can improve the efficiency of the implementation of the task on the other hand.The Quality of Service(QoS)is one of the key problems in the research of task allocation in AVC.And time index is an important index in QoS indexes.When there’s a time index requirement,the choice of vehicle to run the task will affect success rate within a fixed time.This is because the vehicle of AVC has high mobility on the highway,the communication link maintaining time between the vehicle and the task requesting vehicle is different and so is the computing ability of each vehicle.The choice of vehicle to undertake the task will affect success rate within a particular time.In this thesis,we proposed a set of methods for choosing task nodes to meet the requirement of QoS under AVC on the highway.We take factors such as the duration time of communication link and computing ability of each vehicle into account.We also considered the optimal way to re-schedule the task.In the end,the effectiveness of the proposed strategy is simulated using the OPNET network simulation platform.The simulation results show that the success rate of the task allocation strategy proposed in this paper is at least 8.7%and at most 10.4%,compared with the strategy of taking the vehicle node strategy randomly.