Name
Abstract | ||
|---|---|---|
ording to the important methodology of convex optimization theory, the energy-efficient and scalability problems of modern data centers are studied. Then a novel virtual machine (VM) placement scheme is proposed for solving these problems in large scale. Firstly, by referring the definition of VM placement fairness and utility function, the basic algorithm of VM placement which fulfills server constraints of physical machines is discussed. Then, we abstract the VM placement as an optimization problem which considers the inherent dependencies and traffic between VMs. By given the structural differences of recently proposed data center architectures, we further investigate a comparative analysis on the impact of the network architectures, server constraints and application dependencies on the potential performance gain of optimization-based VM placement. Comparing with the existing schemes, the performance improvements are illustrated from multiple perspectives, such as reducing the number of physical machines deployment, decreasing communication cost between VMs, improving energy-efficient and scalability of data centers. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s10766-013-0274-5 | International Journal of Parallel Programming |
Keywords | Field | DocType |
data center,optimization theory,virtual machine placement,virtualization | Virtualization,Software deployment,Virtual machine,Computer science,Parallel computing,Network architecture,Data center,Optimization problem,Convex optimization,Distributed computing,Scalability | Journal |
Volume | Issue | ISSN |
42 | 5 | 1573-7640 |
Citations | PageRank | References |
22 | 0.92 | 20 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fei Song | 1 | 167 | 19.86 |
| Daochao Huang | 2 | 69 | 6.47 |
| Huachun Zhou | 3 | 370 | 54.39 |
| Hongke Zhang | 4 | 1637 | 142.17 |
| Ilsun You | 5 | 979 | 123.32 |