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A new agent-based method for QoS-aware cloud service composition using particle swarm optimization algorithm

机译:一种新的基于粒子群优化算法的基于代理的QoS感知云服务组合方法

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摘要

Cloud computing as a new computing paradigm has a great capacity for storing and accessing the remote data and services. Presently, many organizations decide to reduce the burden of local resources and support them by outsourcing the resources to the cloud. Typically, scalable resources are provided as services over the Internet. The way of choosing appropriate services in the cloud computing is done by determining the different Quality of Service (QoS) parameters to perform optimized resource allocation. Therefore, service composition as a developing approach combines the existing services to increase the number of cloud applications. Independent services can be integrated into complex composited services through service composition. In this paper, a new hybrid method is proposed for efficient service composition in the cloud computing. The agent-based method is also used to compose services by identifying the QoS parameters and the particle swarm optimization (PSO) algorithm is employed for selecting the best services based on fitness function. The simulation results have shown the performance of the method in terms of reducing the combined resources and waiting time.
机译:云计算作为一种新的计算范例,具有存储和访问远程数据和服务的强大功能。当前,许多组织决定减少本地资源的负担,并通过将资源外包到云来支持本地资源。通常,可伸缩资源作为Internet上的服务提供。通过确定不同的服务质量(QoS)参数以执行优化的资源分配,可以在云计算中选择合适的服务。因此,服务组合作为一种发展中的方法结合了现有服务以增加云应用程序的数量。可以通过服务组合将独立服务集成到复杂的组合服务中。本文提出了一种新的混合方法,用于在云计算中有效地进行服务组合。基于代理的方法还用于通过识别QoS参数来组合服务,并且采用粒子群优化(PSO)算法基于适应度函数选择最佳服务。仿真结果表明了该方法在减少组合资源和等待时间方面的性能。

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