Name
Abstract | ||
|---|---|---|
A significant proportion of the operational cost for datacenters is attributed to their energy consumption. Using advanced virtualization techniques in datacenters is enabling the control of electricity use in servers. However, as servers are becoming more energy-proportional, datacenter networks are starting to consume a greater portion of overall power although networks devices often remain under-utilized. This paper proposes an energy aware management technique for reducing the consumption of energy by the network for a Spine-Leaf topology-based datacenter. The main idea of the system is to keep track of the dynamic workload and enable only switches that are necessary for handling the current network traffic. We have developed an energy aware management system for dynamically controlling the number of Spine switches in Spine-Leaf datacenter networks and performed simulation using CloudSim for a number of scenarios. The simulation results show that the system can work effectively to 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 |
|---|---|---|
2015 | 10.1109/ICC.2015.7248308 | 2015 IEEE International Conference on Communications (ICC) |
Keywords | Field | DocType |
Green Datacenters,Datacenter Networks,Spine-Leaf Topology,Resource Management | Virtualization,Resource management,Electricity,Workload,Computer science,Server,Computer network,Real-time computing,Energy consumption,Management system,CloudSim | Conference |
ISSN | Citations | PageRank |
1550-3607 | 1 | 0.39 |
References | Authors | |
8 | 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 |