GreenDCN: a General Framework for Achieving Energy Efficiency in Data Center Networks

TL;DR

GreenDCN introduces a comprehensive framework combining VM placement and traffic engineering to significantly reduce energy consumption in data center networks, achieving up to 50% savings.

Contribution

The paper presents a novel, NP-hard framework that integrates VM assignment with traffic engineering for energy efficiency in data centers.

Findings

Up to 50% energy savings achieved.

Framework effectively balances traffic and reduces active switches.

Scalability and practicality discussed in detail.

Abstract

The popularization of cloud computing has raised concerns over the energy consumption that takes place in data centers. In addition to the energy consumed by servers, the energy consumed by large numbers of network devices emerges as a significant problem. Existing work on energy-efficient data center networking primarily focuses on traffic engineering, which is usually adapted from traditional networks. We propose a new framework to embrace the new opportunities brought by combining some special features of data centers with traffic engineering. Based on this framework, we characterize the problem of achieving energy efficiency with a time-aware model, and we prove its NP-hardness with a solution that has two steps. First, we solve the problem of assigning virtual machines (VM) to servers to reduce the amount of traffic and to generate favorable conditions for traffic engineering. The solution reached for this problem is based on three essential principles that we propose. Second, we reduce the number of active switches and balance traffic flows, depending on the relation between power consumption and routing, to achieve energy conservation. Experimental results confirm that, by using this framework, we can achieve up to 50 percent energy savings. We also provide a comprehensive discussion on the scalability and practicability of the framework.