Exploiting dynamic attributes and annotations for service discovery in pervasive computing

Iqra Lakho, Lachhman Das Dhomeja, Y. A. Malkani, S. Memon, Mahmoud Aljawarneh
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Abstract

Pervasive computing environments offer a huge number of services that need to be discovered and interacted with to support users in their daily life activities with minimal or no user distraction. The discovery of services and selection of the best possible service from discovered services, which best fulfills user needs is one of the key requirements for pervasive computing environments. While literature suggests that existing discovery systems have attempted to incorporate mechanisms to improve discovery in pervasive computing environments, they still lack mechanisms and supporting infrastructure which can contribute towards provision of the best possible service. In this paper, we address this issue and put forward an approach that selects the best possible service from a list of discovered services based on both service dynamic attributes and user provided service annotations. The proposed approach has been partially implemented and details of which have been presented in the paper.
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利用动态属性和注解来发现普适计算中的服务
普适计算环境提供了大量需要被发现和交互的服务,以支持用户在日常生活活动中尽量减少或不分散用户的注意力。发现服务并从发现的服务中选择最能满足用户需求的最佳服务是普适计算环境的关键需求之一。虽然文献表明,现有的发现系统已经尝试合并机制来改善普适计算环境中的发现,但它们仍然缺乏机制和支持基础设施,无法为提供尽可能好的服务做出贡献。在本文中,我们解决了这个问题,并提出了一种基于服务动态属性和用户提供的服务注释从发现的服务列表中选择可能的最佳服务的方法。建议的方法已部分实施,其细节已在文件中提出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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