@article{lang2012towards,
author = {Lang, Willis and Harizopoulos, Stavros and Patel, Jignesh M. and Shah, Mehul A. and Tsirogiannis, Dimitris},
title = {Towards energy-efficient database cluster design},
year = {2012},
month = {August},
abstract = {Energy is a growing component of the operational cost for many "big data" deployments, and hence has become increasingly important for practitioners of large-scale data analysis who require scale-out clusters or parallel DBMS appliances. Although a number of recent studies have investigated the energy efficiency of DBMSs, none of these studies have looked at the architectural design space of energy-efficient parallel DBMS clusters. There are many challenges to increasing the energy efficiency of a DBMS cluster, including dealing with the inherent scaling inefficiency of parallel data processing, and choosing the appropriate energy-efficient hardware. In this paper, we experimentally examine and analyze a number of key parameters related to these challenges for designing energy-efficient database clusters. We explore the cluster design space using empirical results and propose a model that considers the key bottlenecks to energy efficiency in a parallel DBMS. This paper represents a key first step in designing energy-efficient database clusters, which is increasingly important given the trend toward parallel database appliances.},
url = {http://approjects.co.za/?big=en-us/research/publication/towards-energy-efficient-database-cluster-design/},
pages = {1684-1695},
journal = {2012 Very Large Data Bases},
volume = {5},
number = {11},
}