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Strategies and systems towards grids and clouds integration: A DBMS-based solution

机译:网格和云集成的策略和系统:基于DBMS的解​​决方案

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Cloud and Grid computing share some essential driving ideas although the computing and economic models are very different. In this paper, we propose different strategies for the Batch-oriented and Service-oriented computing models interoperability. In particular, we describe an innovative approach to connect together Computational Grids and IaaS providers. This is achieved via introducing a simple and powerful DBMS-based system of deploying VM images from a Cloud environment in order to fulfill particular requests of task execution coming from a Grid environment. From a user point of view, resource authorization and access are kept unchanged, thus preserving the user experience related to the Grid. From the accounting point of view, in order to inform the Grid sites that a certain resource is available on a given Cloud-enabled Grid site, the information is published on the Grid information system. In this so-delineated scenario, we are able of using the powerful capability of distributing jobs of the Grid in order to allocate resources not only belonging to Grid clusters, but also with different architectures like GPUs, FPGAs and other systems. The target DBMS-based system has been designed for orchestrate a set of computing systems able to provide physical and virtual resources, creating a unified system, in which the various users-submitted computing tasks are managed and optimized. The goodness of the proposed system is demonstrated by a series of experiments highlighting the benefits of our approach.
机译:尽管计算和经济模型非常不同,但是云计算和网格计算共享一些基本的驱动思想。在本文中,我们针对面向批处理和面向服务的计算模型互操作性提出了不同的策略。特别是,我们描述了一种将计算网格与IaaS提供商连接在一起的创新方法。这是通过引入一个简单而强大的基于DBMS的系统来实现的,该系统从Cloud环境中部署VM映像,以便满足来自Grid环境的任务执行的特定请求。从用户的角度来看,资源授权和访问保持不变,从而保留了与网格相关的用户体验。从记账的角度来看,为了通知Grid站点在给定的支持Cloud的Grid站点上有某些资源可用,该信息会在Grid信息系统上发布。在这种情况下,我们能够利用强大的网格作业分配功能来分配资源,这些资源不仅属于网格集群,而且还具有不同的架构,例如GPU,FPGA和其他系统。基于目标DBMS的系统已设计用于协调一组能够提供物理和虚拟资源的计算系统,从而创建一个统一的系统,在该系统中管理和优化了各种用户提交的计算任务。一系列实验强调了我们方法的好处,证明了所提出系统的优越性。

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