Green Resource Management in Distributed Cloud Infrastructures

Computing has evolved over time according to different paradigms, along with an increasing need for computational power. Modern computing paradigms basically share the same underlying concept of Utility Computing, that is a service provisioning model through which a shared pool of computing resources is used by a customer when needed. The objective of Utility Computing is to maximize the resource utilization and bring down the relative costs. Nearly a decade ago, the concept of Cloud Computing emerged as a virtualization technique where services were executed remotely in a ubiquitous way, providing scalable and virtualized resources. The spread of Cloud Computing has been also encouraged by the success of the virtualization, which is one of the most promising and efficient techniques to consolidate system's utilization on one side, and to lower power, electricity charges and space costs in data centers on the other. In the last few years, there has been a remarkable growth in the number of data centers, which represent one of the leading sources of increased business data traffic on the Internet. An effect of the growing scale and the wide use of data centers is the dramatic increase of power consumption, with significant consequences both in terms of environmental and operational costs. In addition to power consumption, also carbon footprint of the Cloud infrastructures is becoming a serious concern, since a lot of power is generated from non-renewable sources. Hence, energy awareness has become one of the major design constraints for Cloud infrastructures. In order to face these challenges, a new generation of energy-efficient and eco-sustainable network infrastructures is needed. In this thesis, a novel energy-aware resource orchestration framework for distributed Cloud infrastructures is discussed. The aim is to explain how both network and IT resources can be managed while, at the same time, the overall power consumption and carbon footprint are being minimized. To this end, an energy-aware routing algorithm and an extension of the OSPF-TE protocol to distribute energy-related information have been implemented