In the era of digitalization, one of the most challenging research topic regards the energy consumption reduction of ICT equipment to contrast the global climate change. The ICT world is very sensitive to the problem of Greenhouse Gas emissions (GHG) and for several years has begun to implement some countermeasures to reduce consumption waste and increase efficiency of infrastructure: the total embodied emissions of end-use devices have significantly decreased, networks have become more energy efficient, and trends such as virtualization and dematerialization will continue to make equipment more efficient. One of the main contributor to GHG emissions is data centers industry, which provision end users with the necessary computing and communication resources to access the vast majority of services online and on a pay-as-you-go basis. Data centers require a tremendous amount of energy to operate, since the efficiency of cooling systems is increasing, more research efforts should be put in making green the IT system, which is becoming the major contributor to energy consumption. Being the network one of the non-negligible contributors to energy consumption in data centers, several architectures have been designed with the goal of improving energy-efficient of data centers. These architectures are called Data Center Networks (DCNs) and provide interconnections among the computing servers and between the servers and the Internet, according to specific layouts.In my PhD I have extensively investigated on energy efficiency of data center, working on different projects which try to tackle the problems from different views. The research can be divided into two main parts with the Energy Proportionality as connection argument. The main focus of the work is about the trade-off between size and energy efficiency of data centers, with the aim to find a relationship between scalability and energy proportionality of data centers. In this regard, the energy consumption of different data center architectures have been analyzed, varying the dimension in terms of number of server and switches. Extensive simulation experiments, performed in small and large scale scenarios, unveil the ability of network-aware allocation policies in loading the the data center in a energy-proportional manner and the robustness of classical two- and three-tier design under network-oblivious allocation strategies. The concept of energy proportionality, applied to the whole DCN and used as efficiency metric, is one of the main contributions of the work. Energy proportionality is a property defining the degree of proportionality between load and the energy spent to support such load, thus devices are energy proportional when any increase of the load corresponds to a proportional increase of energy consumption. A peculiar feature of our analysis is in the consideration of the whole data center, i.e., both computing and communication devices are taken into account. Our methodology consists of an asymptotic analysis of data center consumption, whenever its size (in terms of servers) become very large. In our analysis, we investigate the impact of three different allocation policies on the energy proportionality of computing and networking equipment for different DCNs, including 2-Tier, 3-Tier and Jupiter topologies. For evaluation, the size of the DCNs varies to accommodate up to several thousands of computing servers. Validation of the analysis is conducted through simulations. We propose new metrics with the objective to characterize in a holistic manner the energy proportionality in data centers. The experiments unveil that, when consolidation policies are in place and regardless of the type of architecture, the size of the DCN plays a key role, i.e., larger DCNs containing thousands of servers are more energy proportional than small DCNs.

Energy Management in Large Data Center Networks / Ruiu, Pietro. - (2018 Apr 23).

Energy Management in Large Data Center Networks

RUIU, PIETRO
2018-04-23

Abstract

In the era of digitalization, one of the most challenging research topic regards the energy consumption reduction of ICT equipment to contrast the global climate change. The ICT world is very sensitive to the problem of Greenhouse Gas emissions (GHG) and for several years has begun to implement some countermeasures to reduce consumption waste and increase efficiency of infrastructure: the total embodied emissions of end-use devices have significantly decreased, networks have become more energy efficient, and trends such as virtualization and dematerialization will continue to make equipment more efficient. One of the main contributor to GHG emissions is data centers industry, which provision end users with the necessary computing and communication resources to access the vast majority of services online and on a pay-as-you-go basis. Data centers require a tremendous amount of energy to operate, since the efficiency of cooling systems is increasing, more research efforts should be put in making green the IT system, which is becoming the major contributor to energy consumption. Being the network one of the non-negligible contributors to energy consumption in data centers, several architectures have been designed with the goal of improving energy-efficient of data centers. These architectures are called Data Center Networks (DCNs) and provide interconnections among the computing servers and between the servers and the Internet, according to specific layouts.In my PhD I have extensively investigated on energy efficiency of data center, working on different projects which try to tackle the problems from different views. The research can be divided into two main parts with the Energy Proportionality as connection argument. The main focus of the work is about the trade-off between size and energy efficiency of data centers, with the aim to find a relationship between scalability and energy proportionality of data centers. In this regard, the energy consumption of different data center architectures have been analyzed, varying the dimension in terms of number of server and switches. Extensive simulation experiments, performed in small and large scale scenarios, unveil the ability of network-aware allocation policies in loading the the data center in a energy-proportional manner and the robustness of classical two- and three-tier design under network-oblivious allocation strategies. The concept of energy proportionality, applied to the whole DCN and used as efficiency metric, is one of the main contributions of the work. Energy proportionality is a property defining the degree of proportionality between load and the energy spent to support such load, thus devices are energy proportional when any increase of the load corresponds to a proportional increase of energy consumption. A peculiar feature of our analysis is in the consideration of the whole data center, i.e., both computing and communication devices are taken into account. Our methodology consists of an asymptotic analysis of data center consumption, whenever its size (in terms of servers) become very large. In our analysis, we investigate the impact of three different allocation policies on the energy proportionality of computing and networking equipment for different DCNs, including 2-Tier, 3-Tier and Jupiter topologies. For evaluation, the size of the DCNs varies to accommodate up to several thousands of computing servers. Validation of the analysis is conducted through simulations. We propose new metrics with the objective to characterize in a holistic manner the energy proportionality in data centers. The experiments unveil that, when consolidation policies are in place and regardless of the type of architecture, the size of the DCN plays a key role, i.e., larger DCNs containing thousands of servers are more energy proportional than small DCNs.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2706336
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo