Concurrent Multitask Model and Real-Time Scheduling for AR Games

Augmented reality game software is a typical real-time multitask concurrent system.In order to solve the scheduling problem of traditional time-sharing scheduling models,a method based on preemptive time Petri net and particle swarm optimization algorithm is proposed in this paper.Firstly,a concurrent multitasking model based on preemptive timed Petri nets is introduced to describe the resource consumption,real-time performance and priority level of each task threading.Secondly,a method for searching optimal task sequence is presented based on particle swarm algorithm.The typical scheduling optimization process of this method is introduced by application cases.After comparing with related task scheduling algorithms,results show that the proposed method has better real-time performance.