A Network-Aware Virtual Machine Allocation in Cloud Datacenter

In a cloud computing environment, virtual machine allocation is an important task for providing infrastructure services. Generally, the datacenters, on which a cloud computing platform runs, are distributed over a wide area network. Therefore, communication cost should be taken into consideration when allocating VMs across servers of multiple datacenters. A network-aware VM allocation algorithm for cloud is developed. It tries to minimize the communication cost and latency between servers, with the number of VMs, VM configurations and communication bandwidths are satisfied to users. Specifically, a two-dimensional knapsack algorithm is applied to solve this problem. The algorithm is evaluated and compared with other ones through experiments, which shows satisfying results.

[1]  Antonio Corradi,et al.  A Stable Network-Aware VM Placement for Cloud Systems , 2012, 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012).

[2]  Rajkumar Buyya,et al.  Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing , 2012, Future Gener. Comput. Syst..

[3]  Bo Wang,et al.  An Intelligent Capacity Planning Model for Cloud Market , 2011, J. Internet Serv. Inf. Secur..

[4]  Randy H. Katz,et al.  A view of cloud computing , 2010, CACM.

[5]  Vasileios Pappas,et al.  Improving the Scalability of Data Center Networks with Traffic-aware Virtual Machine Placement , 2010, 2010 Proceedings IEEE INFOCOM.

[6]  A. Kivity,et al.  kvm : the Linux Virtual Machine Monitor , 2007 .

[7]  Minglu Li,et al.  Energy Efficient Allocation of Virtual Machines in Cloud Computing Environments Based on Demand Forecast , 2012, GPC.

[8]  Rajkumar Buyya,et al.  Energy Efficient Resource Management in Virtualized Cloud Data Centers , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.

[9]  Liang Liu,et al.  GreenCloud: a new architecture for green data center , 2009, ICAC-INDST '09.

[10]  Meng Wang,et al.  Consolidating virtual machines with dynamic bandwidth demand in data centers , 2011, 2011 Proceedings IEEE INFOCOM.

[11]  Fumio Machida,et al.  Redundant virtual machine placement for fault-tolerant consolidated server clusters , 2010, 2010 IEEE Network Operations and Management Symposium - NOMS 2010.

[12]  Andrew Warfield,et al.  Xen and the art of virtualization , 2003, SOSP '03.

[13]  Shuang Wu,et al.  Virtual Machine Based Energy-Efficient Data Center Architecture for Cloud Computing: A Performance Perspective , 2010, 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing.

[14]  Rajkumar Buyya,et al.  Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges , 2010, PDPTA.

[15]  Laurence T. Yang,et al.  Advances in Grid and Pervasive Computing, Third International Conference, GPC 2008, Kunming, China, May 25-28, 2008. Proceedings , 2008, GPC.

[16]  Carl A. Waldspurger,et al.  Memory resource management in VMware ESX server , 2002, OSDI '02.

[17]  T. V. Lakshman,et al.  Network aware resource allocation in distributed clouds , 2012, 2012 Proceedings IEEE INFOCOM.

[18]  Cao Jian,et al.  Energy Efficient Allocation of Virtual Machines in Cloud Computing Environments Based on Demand Forecast , 2013 .