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ADAPTIVE AND INTELLIGENT REQUEST DISTRIBUTION FOR CONTENT DELIVERY NETWORKS

机译:内容交付网络的自适应和智能请求分配

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Today's knowledge and content Web-based technologies call for adaptive and intelligent algorithms for accessing the resources, especially to respond to Semantic Web, as well to performance challenges. This work presents the application of two machine learning techniques in an adaptive decision making framework, namely a fuzzy logic and neural networks, to deploy the adaptive and intelligent dispatching algorithm for resource requesting within a geographically distributed fully replicated Web sites. Our approach and algorithm can be used in content distribution and delivery networks where due to content replication each Web server can respond to the client request. Intelligent redirection mechanism redirects the request from the originating site's server to the "best" content source to deliver the content in the fastest manner. First, we introduce a broker-based system architecture. Next, we develop a new
机译:当今基于Web的知识和内容技术要求自适应和智能算法来访问资源,尤其是对语义Web以及性能挑战的响应。这项工作介绍了两种机器学习技术在自适应决策框架(即模糊逻辑和神经网络)中的应用,以在地理分布完全复制的网站内为资源请求部署自适应和智能调度算法。我们的方法和算法可用于内容分发和交付网络中,由于内容复制,每个Web服务器都可以响应客户端请求。智能重定向机制将请求从始发站点的服务器重定向到“最佳”内容源,以最快的方式传递内容。首先,我们介绍一个基于代理的系统架构。接下来,我们开发一个新的

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