ElasticTree: saving energy in data center networks
Palo Alto University · Stanford University · +2 more institutions
Abstract
Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network’s ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power manager, which dynamically adjusts the set of active network elements — links and switches — to satisfy changing data center traffic loads. We first compare multiple strategies for finding minimum-power network subsets across a range of traffic patterns. We implement and analyze ElasticTree on a prototype testbed built with production OpenFlow switches from three network vendors. Further, we examine the trade-offs…
Citation impact
- FWCI
- 148.56
- Percentile
- 100%
- References
- 25
Authors
7Topics & keywords
- Testbed
- Data center
- Computer science
- OpenFlow
- Computer network
- Robustness (evolution)
- Distributed computing
- Networking hardware
- Affordable and clean energy