可穿戴测试系统启发式任务调度研究

Research of Heuristic Task Scheduling for Wearable Test Assistant System

近年来,可穿戴计算技术在工业、军事等领域得到了广泛的关注和应用。针对基于可穿戴计算机构建现场设备数据采集等测试系统时常遇到的任务规划和调度问题,通过企业本体知识库生成基于Petri网标识语言(PNML)的动态工作流对象,针对其提出一种基于A*算法的启发式任务调度方法。采用该算法可以根据一定的启发函数产生必要的局部可达图,并在这一局部可达图所代表的路径中选择最优或次优的路径,能有效缩短计算时间,化简搜索过程,避免死锁或资源冲突等情况的发生,从而提高系统在场景自适应、高效的用户指导和辅助等方面的实用性能。

Research of wearable computing in cent years. Aiming at the problems of task planning industry and military applications has got much attention in reand scheduling in building wearable operation assistant system, firstly the dynamic workflow object is acquired via enterprise domain ontology, then a task scheduling method based on A^＊ heuristic search algorithm is applied to produce the local reachable graph and find the optimal path. The algorithm can shorten calculation time and avoid deadlock or resource confliction. With these methods the wearable operation assistant system has achieved better practical performances such as better adaptive capability to application scenario, efficient user instructive and assistant abilities.