摘要
增强现实游戏软件系统属于典型的多任务并发实时系统.针对传统的分时调度模型不能很好地应对其实时调度的问题,提出一种基于抢占式时间Petri网和粒子群算法的方法.首先建立基于抢占式时间Petri网的并发多任务模型,描述了各任务线程的资源占用、时间性能指标和优先级关系等;其次提出基于粒子群算法的任务优化序列搜索方法,并通过构建应用实例阐述了使用该方法进行系统调度优化的典型过程.与相关的任务调度算法进行对比分析的结果表明,该方法具有良好的实时性能特征.
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.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2014年第2期211-216,共6页
Journal of Computer-Aided Design & Computer Graphics
基金
国家国际科技合作项目(2009DFA12100)
中德科学中心中德合作研究项目(GZ817)
中央高校基本科研业务费专项资金(ZYGX2010J079
ZYGX2012J090)
关键词
增强现实游戏
并发多线程调度
抢占式时间Petri网
粒子群算法
augmented reality game
concurrent multitask scheduling
preemptive timed Petri nets
particle swarm optimization
