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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >LASEC: A Localized Approach to Service Composition in Pervasive Computing Environments
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LASEC: A Localized Approach to Service Composition in Pervasive Computing Environments

机译:LASEC:普适计算环境中服务组合的本地化方法

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Pervasive computing environments (PvCE) are embedded with interconnected smart devices which provide users with services desired. To meet requirements of users, smart devices with different kinds of functions may need to be associated together to provide the service described in the user requirement, which is called service composition. As the service composition environment may be dynamic and large scale, centralized service composition algorithm is usually inefficient due to message cost. On the other hand, a decentralized approach, which employs pre-determined coordinators to search and compose service, may have high cost as well. In this paper, we discuss a localized approach for service composition based on the Ubiquitous Interacting Object (UIO) model we have proposed earlier. UIO is an abstraction of physical devices in PvCE with ability to find and collaborate with other devices through exposing their capabilities as services. In our localized service composition algorithm (LASEC), UIOs collaborate with each other in a bottom-up, localized manner to compose required service without requiring global knowledge. To solve the problem of blind compositions in LASEC, we propose a novel mechanism called Alien-information-based Acknowledging (A-Ack), in which a UIO decides on collaborating with another UIO only after obtaining some additional information from the collaboration candidate. Specifically, this information refers to ability of a given UIO to compose another part of the service. Proposed LASEC is message-efficient and quality-guaranteed. Extensive simulations of LASEC as well as existing decentralized and pull-based centralized algorithms have been conducted. The results show the relatively low communication cost and composition time of LASEC. Moreover, we demonstrate feasibility of our approach with a prototype implementation.
机译:普适计算环境(PvCE)嵌入了相互连接的智能设备,这些设备可为用户提供所需的服务。为了满足用户的需求,可能需要将功能不同的智能设备关联在一起,以提供用户需求中所述的服务,称为服务组合。由于服务组合环境可能是动态且大规模的,因此集中式服务组合算法通常由于消息成本而效率低下。另一方面,采用预定协调器来搜索和组合服务的分散方法也可能具有很高的成本。在本文中,我们讨论了一种基于我们先前提出的泛在交互对象(UIO)模型的服务组合本地化方法。 UIO是PvCE中物理设备的抽象,能够通过将其他设备公开为服务来查找并与其他设备协作。在我们的本地化服务组合算法(LASEC)中,UIO以自下而上,本地化的方式相互协作,以在不需要全局知识的情况下组合所需的服务。为了解决LASEC中盲目组合的问题,我们提出了一种称为“基于外来信息的确认”(A-Ack)的新机制,其中,只有在从协作候选者获得一些其他信息之后,UIO才会决定与另一个UIO进行协作。具体而言,此信息是指给定UIO组成服务另一部分的能力。拟议的LASEC是消息有效且质量得到保证的。进行了LASEC的广泛模拟以及现有的分散式和基于拉式的集中式算法。结果表明,LASEC的通信成本和编写时间相对较低。此外,我们通过原型实现展示了我们方法的可行性。

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