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SELDAC: Software-Defined Storage based Efficient Load Distribution and Auto Scaling in Cloud Data Centers

机译：SELDAC：云数据中心中基于软件定义的有效负载分配和自动扩展的存储

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摘要

Cloud computing allows the users to access the shared pool of configurable resources such as compute, network and storage on-demand basis from the cloud Data Centers. Cloud storage provides the storage resources to the cloud users over the network. The massive growth of cloud data due to the applications such as video streaming, big data processing, social networking, banking and scientific applications fueled the storage demand. An increase in storage demand resulted in the expansion of the cloud storage with additional storage nodes. The expansion of the cloud storage necessitates the migration of data across the storage nodes to keep them balanced. Efficient management and migration of tera bytes or peta bytes of such cloud data depends not only on the storage availability but also on the networking cost which is proportional to the distance and the bandwidth requirement. In this scenario, software defined environment opens up the new opportunities to orchestrate the network and storage resources control strategies to provide an effective solution. In this paper, we present the software-defined orchestration framework for efficient load distribution and auto scaling mechanism and shows that it improves the overall efficiency in terms of latency and retrieval cost. We demonstrate the effectiveness and the efficiency of the proposed mechanism using simulations.
机译：云计算使用户可以从云数据中心按需访问共享的可配置资源池，例如计算，网络和存储。云存储通过网络为云用户提供存储资源。视频流，大数据处理，社交网络，银行和科学应用等应用程序带来的云数据的大量增长推动了存储需求。存储需求的增加导致云存储扩展了额外的存储节点。云存储的扩展需要跨存储节点进行数据迁移，以使其保持平衡。这种云数据的兆字节或PB字节的有效管理和迁移不仅取决于存储可用性，还取决于与距离和带宽要求成比例的网络成本。在这种情况下，软件定义的环境将为编排网络和存储资源控制策略提供新的机会，从而提供有效的解决方案。在本文中，我们提出了一种软件定义的编排框架，以实现有效的负载分配和自动缩放机制，并表明它在延迟和检索成本方面提高了整体效率。我们通过仿真证明了所提出机制的有效性和效率。

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