Name
Abstract | ||
|---|---|---|
Energy consumption for datacenter has grown significantly and the trend is still growing due to the increasing popularity of cloud computing. Datacenter networks (DCNs), however, are starting to consume a greater portion of overall energy in comparison to servers used in datacenters due to advanced virtualization techniques. On the other hand, devices in a DCN often remain under-utilized. There are various DCN architectures. This paper proposes an approach called Green Spine Switch Management System (GSSMS) for Spine-Leaf topology based DCNs. The objective of the approach is to reduce energy consumption used by the network for a Spine-Leaf topology-based datacenter. The primary idea of GSSMS is to monitor the dynamic workload and only keep Spine switches that are necessary for handling the current network traffic. We have developed an adaptive management system to control the number of Spine switches in a Spine-Leaf DCN for efficient energy consumption. Further, we have performed extensive simulation using CloudSim for a number of scenarios. The simulation results demonstrate that our proposed GSSMS can effectively save energy by as much as 63 % of the energy consumed by a datacenter comprising a fixed static set of Spine switches. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1186/s13677-016-0058-8 | J. Cloud Computing |
Keywords | Field | DocType |
Datacenters, Datacenter Networks, Spine-Leaf Topology, Resource Management, Energy Efficiency | Virtualization,Resource management,Computer science,Efficient energy use,Server,Real-time computing,Management system,Energy consumption,CloudSim,Distributed computing,Cloud computing | Journal |
Volume | Issue | ISSN |
5 | 1 | 2192-113X |
Citations | PageRank | References |
2 | 0.41 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiao-Lin Li | 1 | 89 | 16.69 |
| Chung-Horng Lung | 2 | 687 | 80.56 |
| Shikharesh Majumdar | 3 | 435 | 75.95 |