Concepedia

TLDR

Data center networks are typically kept continuously powered, but energy savings can be achieved by dynamically scaling network elements to match fluctuating traffic demands. The study introduces ElasticTree, a power manager that dynamically adjusts active network elements to meet changing traffic loads and compares strategies for selecting minimum‑power subsets. ElasticTree is implemented on a prototype testbed using production OpenFlow switches from three vendors, and its energy, performance, and robustness trade‑offs are evaluated with real e‑commerce traffic traces. Results show ElasticTree can save up to 50% of network energy while handling traffic surges, scales to thousands of nodes via a fast heuristic, and offers administrators a configuration framework to balance performance, fault tolerance, and power cost.

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 power1 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 between energy efficiency, performance and robustness, with real traces from a production e-commerce website. Our results demonstrate that for data center workloads, ElasticTree can save up to 50% of network energy, while maintaining the ability to handle traffic surges. Our fast heuristic for computing network subsets enables ElasticTree to scale to data centers containing thousands of nodes. We finish by showing how a network admin might configure ElasticTree to satisfy their needs for performance and fault tolerance, while minimizing their network power bill.

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