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A framework of scaling for inter-tenant collaborative systems

机译:租户间协作系统的扩展框架

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To deliver scalability for business processes running in multi-tenant cloud environment has become a critical goal for enterprise business service providers. Many such software systems are composed of data intensive operations, offered via the Internet as services, and they often perform collaborative analysis of data. Collaborative analysis of data imposes new requirements of scalability on the underneath platform. We need to approach a supporting platform for multiple systems in a multi-tenant cloud environment to achieve better performance. We present our solution of scaling-out for inter-tenant data flows between collaborative data-intensive cloud systems deployed with different VMs. In this paper, we define an abstraction of “shared data flows” to capture data co-analysis and dependency among services of such systems. We describe a model based on the abstraction that is designed with elements to address the challenges in supporting multi-tenant environment to achieve an improved scalability. Our objective is to provide optimization opportunities on bandwidth and throughput of the collaborative service systems of various tenants.
机译:为在多租户云环境中运行的业务流程提供可伸缩性已成为企业业务服务提供商的关键目标。许多这样的软件系统由数据密集型操作组成,通过Internet作为服务提供,它们经常执行数据的协作分析。数据的协同分析对底层平台提出了新的可伸缩性要求。我们需要为多租户云环境中的多个系统提供一个支持平台,以实现更好的性能。我们提供了针对部署有不同VM的协作数据密集型云系统之间的租户间数据流进行横向扩展的解决方案。在本文中,我们定义了“共享数据流”的抽象,以捕获此类系统的服务之间的数据协同分析和依赖性。我们描述了一个基于抽象的模型,该模型设计有一些元素,以解决在支持多租户环境以实现改进的可伸缩性方面的挑战。我们的目标是为各种租户的协作服务系统的带宽和吞吐量提供优化机会。

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