任务计算中基于语义Web的上下文感知服务选择

针对普适环境中任务计算的特点，分析了任务计算的层次结构和复杂任务的分解策略，设计了一种任务计算中服务发现的体系结构。此体系结构依赖于服务和内容的语义表示，而这种语义表示是基于本体的、共享的。它不仅可以增强精确度和调用率，而且能够实现知识共享、基于能力的搜索、自主推理以及语义匹配等功能。据此，提出了一种基于语义Web的上下文感知动态服务选择机制，这种机制可以根据待匹配的服务的动态上下文属性来对其进行过滤和排序，从而进一步优化了发现的过程、节约了用户的时间和精力。此外，该选择机制可用于发现有用的静态或动态上下文信息，从而为用户提供最合适、最相关的服务。

Semantic Web-based context-aware service selection in task-computing

The hierarchy of task-computing and the decomposition strategy of complex task were analyzed according to the characteristics of task-computing in pervasive environment.The architecture relied on the semantic representation of service and content based on shared ontology.It could not only improve the accuracy and recall,but also realize the functions such as knowledge sharing,capability-based search,autonomous reasoning and semantic matchmaking.Thus,a dynamic context-aware service selection mechanism based ...