计算机应用 ›› 2014, Vol. 34 ›› Issue (4): 1149-1154.DOI: 10.11772/j.issn.1001-9081.2014.04.1149

• 计算机软件技术 • 上一篇    下一篇

支持上下文感知应用程序的动态自适应中间件框架

许楠,张维石   

  1. 大连海事大学 信息科学技术学院,辽宁 大连 116026
  • 收稿日期:2013-10-25 修回日期:2013-12-23 发布日期:2014-04-29 出版日期:2014-04-01
  • 通讯作者: 许楠
  • 作者简介:许楠(1984-),女,辽宁营口人,博士研究生,主要研究方向:上下文感知计算、软件工程、形式化方法;
    张维石(1962-),男,辽宁大石桥人,教授,博士生导师,主要研究方向:软件工程、服务计算、交通信息系统、形式化方法。
  • 基金资助:

    国家自然科学基金资助项目;中央高校基本科研基金资助项目;中央高校基本科研业务费专项资金资助项目

Dynamic and self-adaptive middleware infrastructure for supporting context-aware applications

XU Nan,ZHANG Weishi   

  1. College of Information Science and Technology, Dalian Maritime University, Dalian Liaoning 116026, China
  • Received:2013-10-25 Revised:2013-12-23 Online:2014-04-29 Published:2014-04-01
  • Contact: XU Nan

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摘要：

上下文感知计算是当前开发和部署智能应用不可或缺的关键技术之一。上下文能否在计算中真正发挥其作用，主要取决于两方面：一是如何连续稳定地从动态交互环境中获取高质量上下文，二是如何推理上下文并制定适应决策。为了实现上述目标，设计了一个分层的中间件框架，该中间件能够根据上下文质量参数，动态地选择能提供高质量上下文的信息源，并对这些原始上下文进行预处理和推理，进而自动地制定适应决策为用户提供合适的服务。实验测试了平台的性能，并与同类系统进行了比较，结果表明该中间件能够快速有效地支持上下文感知应用的开发部署，并且在计算性能方面有显著提高。

Abstract:

Context-aware computing is one of the indispendable key technologies for developing and deploying intelligent applications. Whether the context can really contribute to the applications mainly depends on the following two aspects: the first is how to continuously and steadily monitor/capture high-quality context information from the dynamic interaction environment, the second is how to reason on contexts and make adaptation decisions for applications. A layered middleware infrastructure was designed to achieve the above objectives. It afforded effective supports for not only gathering, managing, interpreting and making use of context information to dynamically adapt applications, but also selecting the most appropriate context sources dynamically at runtime based upon Qualities of Context (QoC). Finally, the experimental results show that the middleware can quickly and efficiently support the development and deployment of context-aware applications, and has better computing performance in comparison with others.

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