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MR-CloudSim: Designing and implementing MapReduce computing model on CloudSim

机译:MR-CloudSim:在Cloudsim上设计和实现MapReduce计算模型

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Nowadays, we can hear the word “cloud” everywhere. Cloud web storage, cloud-based web applications, and cloud networks, they all indicate that cloud has become more important than it has ever been. Internet service providers (ISP) and internet contents providers (ICP) are providing more and more services with cloud computing, and also in mobile computing environments, a cloud service is drawing much attention from the community. The biggest advantage of cloud computing is clear. As far as the user is connected to the cloud, (s)he can have all the extra computing power and storage no matter what his device is. However, empirical validation of various research projects on a cloud system seems to be ineffective in both cost and time since it requires involving to a huge amount of computing facilities and resources. Even with its importance as commerce and inconvenience of researching, there are not many simulators that can provide a simulation environment for cloud computing and datacenters. Thus, we propose a simulation tool that supports the MapReduce model, the most widely used programming model for big data processing, implemented on CloudSim, an open source simulator for cloud computing and datacenters.
机译:如今,我们可以听到这个词“ cloud”到处。云Web存储,基于云的Web应用程序和云网络,它们都表明云变得比以往更重要。互联网服务提供商(ISP)和Internet内容提供商(ICP)正在提供云计算的越来越多的服务,也在移动计算环境中提供云服务,这是一个云服务从社区借鉴了很多关注。云计算的最大优势很清楚。据用户连接到云,但是,无论他的设备是什么,他都可以拥有所有额外的计算能力和存储。然而,在云系统上的各种研究项目的实证验证似乎在成本和时间方面无效,因为它需要涉及大量的计算设施和资源。即使是作为商业的重要性和对研究的不便,也没有许多模拟器可以为云计算和数据中心提供仿真环境。因此,我们提出了一种支持MapReduce模型的模拟工具,在CloudSim上实现了MapReduce模型,是大数据处理的最广泛的编程模型,是云计算和数据中心的开源模拟器。

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