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    曹科宁, 王永恒, 李仁发, 王凤娟. 面向物联网的分布式上下文敏感复杂事件处理方法[J]. 计算机研究与发展, 2013, 50(6): 1163-1176.
    引用本文: 曹科宁, 王永恒, 李仁发, 王凤娟. 面向物联网的分布式上下文敏感复杂事件处理方法[J]. 计算机研究与发展, 2013, 50(6): 1163-1176.
    Cao Kening, Wang Yongheng, Li Renfa, Wang Fengjuan. A Distributed Context-Aware Complex Event Processing Method for Internet of Things[J]. Journal of Computer Research and Development, 2013, 50(6): 1163-1176.
    Citation: Cao Kening, Wang Yongheng, Li Renfa, Wang Fengjuan. A Distributed Context-Aware Complex Event Processing Method for Internet of Things[J]. Journal of Computer Research and Development, 2013, 50(6): 1163-1176.

    面向物联网的分布式上下文敏感复杂事件处理方法

    A Distributed Context-Aware Complex Event Processing Method for Internet of Things

    • 摘要: 物联网产生的数据具有大数据特征,而这些数据难以用现有数据处理技术进行有效处理.作为物联网中间件的核心技术,复杂事件处理技术具备大数据的海量、复杂性等特征和实时处理的需求.上下文敏感是复杂事件处理引擎的重要特征.提出一种高效的面向物联网的分布式上下文敏感复杂事件处理架构和方法.该方法使用模糊本体进行上下文建模,以支持事件的不确定性及模糊事件查询问题.以基于模糊本体的查询和基于相似性的分布式推理为基础,生成复杂事件查询规划,并通过查询重写,把上下文相关查询转换为上下文无关子查询.根据不同的事件模型和上下文划分数据,并通过优化和多级并行来提高性能.实验结果表明该方法能够处理模糊事件上下文,对于面向物联网的分布式上下文敏感复杂事件处理具有比一般方法更好的性能和可伸缩性.

       

      Abstract: The data produced by Internet of things has the characteristic of big-data and those data can hardly be processed by present data processing technologies. As the key part of Internet of things, complex event process (CEP) has two characteristics of big data: quantity, complexity and has the need of on-time processing. Context-awareness is an important feature of CEP engine. In this paper, a high-performance distributed context-aware CEP architecture and method is proposed for Internet of things. The method uses fuzzy ontology to create query model to support event query of uncertainty and fuzzy. Based on fuzzy ontology query and similarity based distributed reasoning, complex event query plans are generated and context-aware queries are rewritten into context independent sub-queries. The sub-queries are optimized and executed parallel based on data partition. The experimental results show that this method can support fuzzy context in CEP and has better performance and scalability than other methods.

       

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