Improving the Scalability of Data Center Networks

Improving the Scalability of Data Center Networks -...

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Unformatted text preview: Improving the Scalability of Data Center Networks with Traffic-aware Virtual Machine Placement Xiaoqiao Meng, Vasileios Pappas, Li Zhang IBM T.J. Watson Research Center 19 Skyline Drive, Hawthorne, NY 10532 Email: { xmeng, vpappas, zhangli } Abstract The scalability of modern data centers has become a practical concern and has attracted significant attention in recent years. In contrast to existing solutions that require changes in the network architecture and the routing protocols, this paper proposes using traffic-aware virtual machine (VM) placement to improve the network scalability. By optimizing the placement of VMs on host machines, traffic patterns among VMs can be better aligned with the communication distance between them, e.g. VMs with large mutual bandwidth usage are assigned to host machines in close proximity. We formulate the VM placement as an optimization problem and prove its hardness. We design a two-tier approximate algorithm that efficiently solves the VM placement problem for very large problem sizes. Given the significant difference in the traffic patterns seen in current data centers and the structural differences of the recently proposed data center architectures, we further conduct a comparative analysis on the impact of the traffic patterns and the network architectures on the potential performance gain of traffic-aware VM placement. We use traffic traces collected from production data centers to evaluate our proposed VM placement algorithm, and we show a significant performance improvement compared to existing generic methods that do not take advantage of traffic patterns and data center network characteristics. I. INTRODUCTION Modern virtualization based data centers are becoming the hosting platform for a wide spectrum of composite applica- tions. With an increasing trend towards more communication intensive applications in data centers, the bandwidth usage between virtual machines (VMs) is rapidly growing. This raises a number of concerns with respect to the scalability of the underlying network architecture, an issue that has attracted significant attention recently [1][2][3][4][5][6][7]. Techniques in these proposals include rich connectivity at the edge of the network and dynamic routing protocols to balance traffic load. In this paper, we tackle the scalability issue from a different perspective, by optimizing the placement of VMs on host machines. Normally VM placement is decided by various capacity planning tools such as VMware Capacity Planner [8], IBM WebSphere CloudBurst [9], Novell PlateSpin Recon [10] and Lanamark Suite [11]. These tools seek to consolidate VMs for CPU, physical memory and power consumption savings, yet without considering consumption of network resources. As a result, this can lead to situations in which VM pairs with heavy traffic among them are placed on host machines with large network cost between them. To understand how often this happens in practice, we conducted a measurement study...
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