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Dynamic User Task Composition Based on User Preferences

机译:基于用户首选项的动态用户任务组合

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As the number of devices in a pervasive environment is increased, the number of components available on the network also grows rapidly. In such cases, it is possible to compose various applications through a combination of different sets of components. Considering the multifaceted problem of having varying device capabilities supporting a different set of protocols, and each device hosting a number of components providing the same functionality, it becomes very difficult to choose a particular device hosting a required component which can be the best-fit for the user. This becomes practically impossible when the required components are distributed across various devices in the networked environment. We propose a solution for dynamic user task composition considering user preferences, device capabilities, and heterogeneity of communication protocols. With our proposed approach, a user task can be instantiated in different environments using a different set of devices and components, depending upon their capabilities and user preferences. We propose mechanisms for modeling device capabilities and user preferences and for modeling the user task as a graph. We then propose algorithms for selection of devices based on user preferences and task requirements. Since the underlying network is also modeled as a graph, we describe an algorithm for mapping of services in the user task on to the components distributed across devices in the pervasive environment. We also give an overview of our initial implementation and some results of our evaluations.
机译:随着普及环境中设备数量的增加,网络上可用组件的数量也迅速增长。在这种情况下,可以通过组合不同组的组件来构成各种应用程序。考虑到具有支持不同协议集的不同设备功能的多方面问题,并且每个设备承载着许多提供相同功能的组件,因此很难选择特定的设备来承载最适合的组件用户。当所需组件分布在网络环境中的各种设备上时,这实际上变得不可能。我们提出一种考虑用户偏好,设备功能和通信协议异构性的动态用户任务组合解决方案。使用我们提出的方法,可以根据用户的功能和用户偏好,在不同的环境中使用一组不同的设备和组件来实例化用户任务。我们提出了用于对设备功能和用户偏好进行建模以及将用户任务建模为图形的机制。然后,我们根据用户的偏好和任务要求提出了用于选择设备的算法。由于基础网络也被建模为图形,因此我们描述了一种算法,用于将用户任务中的服务映射到遍历环境中跨设备分布的组件上。我们还概述了我们的初始实施情况以及评估的一些结果。

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