用于普适计算的服务发现和组合的亲和力驱动集群方法

J. Gaber, M. Bakhouya
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引用次数: 16

摘要

普适计算是一种新的范式,其目标是随时随地提供计算和通信服务。本文提出了普适计算应用实现的服务涌现模型。在此模型中,特别服务或组合服务由一个组织或一组自治代理表示。代理基于亲和力建立关系。亲和性对应于两个服务可以绑定以创建组合服务或指出类似服务的充分性。随着用户对所提供服务的满意度和动态网络条件的变化,这些亲和力会被调整或加强。并利用NS2对该服务涌现模型进行了仿真
本文章由计算机程序翻译,如有差异,请以英文原文为准。
an affinity-driven clustering approach for service discovery and composition for pervasive computing
Pervasive computing is a new paradigm with a goal to provide computing and communication services all the time and everywhere. In this paper, a service emergence model for the implementation of pervasive computing applications is presented. In this model, ad hoc or composite services are represented by an organization or group of autonomous agents. Agents establish relationships based on affinities. Affinity corresponds to the adequacy with which two services could bind to create a composed service or to point out a similar service. These affinities are adjusted or reinforced by user satisfaction regarding the provided service and dynamic network condition changes. Simulations of this proposed service emergence model with NS2 are also presented
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