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QUALITY OF SERVICE-BASED RESOURCE ALLOCATION FOR WEB CONTENT DELIVERY ON CLOUD COMPUTING INFRASTRUCTURE

机译:基于云计算基础架构的Web内容交付的基于服务的资源分配质量

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Demand for web content continues to increase at exponential rates and this has intensified the challenges of satisfying customer?s Quality of Service. Several techniques for Web content delivery vis-?-vis resource allocation have been proposed, one of which is the use of Content Distribution Networks. However, in recent times, cloud computing has become a driving force in Information Technology where Service Providers? limited resources are shared among numerous users with different QoS requirements. In this work, focus is on developing a model for allocation of resources on cloud computing Infrastructure in order to improve delivery of Web content and optimize service cost. An analytical approach was adopted and expressed as an optimization problem subject to QoS metrics: delay, throughput, and bandwidth. The optimization problem was formulated as an Integer Linear Programming problem in which the decision variable takes the value of 0 or 1. A single Infrastructure-as-a-Service cloud with Virtual Machine (VM) instances running in Physical Machines (PM) was assumed. The model was considered for different values of delay, throughput, and bandwidth for each VM to obtain minimum cost of delivering Web content to users. An algorithm was developed and sample data were collected from Amazon Elastic Cloud Compute/storage pricing model to obtain optimal results. The implementation of the algorithm was done using ?A Mathematical Programming Language/Modular In-core Nonlinear Optimization Systems? (AMPL/MINOS).
机译:对Web内容的需求持续以指数级的速度增长,这加剧了满足客户服务质量的挑战。已经提出了几种用于Web内容传递相对于资源分配的技术,其中一种是使用内容分发网络。但是,近来,云计算已成为信息技术的驱动力,服务提供商在哪里?在具有不同QoS要求的众多用户之间共享有限的资源。在这项工作中,重点是开发用于在云计算基础结构上分配资源的模型,以改善Web内容的交付并优化服务成本。采用了一种分析方法,并将其表示为受QoS指标约束的优化问题:延迟,吞吐量和带宽。该优化问题被表述为整数线性规划问题,其中决策变量取值为0或1。假定单个虚拟机(VM)实例在物理机(PM)中运行的基础架构即服务云。考虑该模型为每个VM设置不同的延迟,吞吐量和带宽值,以将向用户交付Web内容的成本降至最低。开发了一种算法,并从Amazon Elastic Cloud计算/存储定价模型中收集了样本数据以获得最佳结果。该算法的实现是使用“数学编程语言/模块化核内非线性优化系统”完成的。 (AMPL / MINOS)。

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