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Minimizing Data Access Latencies for Virtual Machine Assignment in Cloud Systems

机译:最小化云系统中虚拟机分配的数据访问延迟

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摘要

Cloud systems empower the big data management by providing virtual machines (VMs) to process data nodes (DNs) in a faster, cheaper and more effective way. The efficiency of a VM allocation is an important concern that is influenced by the communication latencies. In the literature, it has been proved that the VM assignment minimizing communication latency in the presence of the triangle inequality is 2-approximation. However, a 2-approximation solution is not efficient enough as data center networks are not limited to the triangle inequality. In this paper, we define the quadrilateral inequality property for latencies such that the time complexity of the VM assignment problem minimizing communication latency in the presence of the quadrilateral inequality is in P (polynomial) class. Indeed, we propose an algorithm for the problem of assigning VMs to DNs to minimize the maximum latency among allocated VMs in addition to DNs with their assigned VMs. This algorithm is latency optimal and 2-approximation for networks with the quadrilateral inequality and the triangle inequality, respectively. Besides, the extension of the proposed method can be applied to the cloud elasticity. The simulation results illustrate the good performance and scalability of our method in various known data center networks.
机译:云系统通过提供虚拟机(VM)来处理数据节点(DNS)更快,更便宜,更有效的方式来赋予大数据管理。 VM分配的效率是受通信延迟影响的重要关注。在文献中,已经证明,VM分配在三角形不等式存在下最小化通信延迟是2近似。然而,随着数据中心网络不限于三角不等式,2近似解决方案不足。在本文中,我们为延迟定义了四边形不等式属性,使得VM分配问题的时间复杂性最小化在四边形不等式存在下最小化通信延迟是p(多项式)类。实际上,我们提出了一种算法,用于将VMS分配给DNS的问题,以便除了具有分配的VM的DNS之外,还可以最小化分配的VM之间的最大延迟。该算法是具有四边形不等式和三角不等式的网络的延迟最佳和2近似。此外,所提出的方法的延伸可以应用于云弹性。仿真结果说明了我们在各种已知数据中心网络中的方法的良好性能和可扩展性。

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