Title :
DENS: Data Center Energy-Efficient Network-Aware Scheduling
Author :
Kliazovich, Dzmitry ; Bouvry, Pascal ; Khan, Samee Ullah
Author_Institution :
Univ. of Luxembourg, Luxembourg, Luxembourg
Abstract :
In modern data centers, energy consumption accounts for a considerably large slice of operational expenses. The state of the art in data center energy optimization is focusing only on job distribution between computing servers based on workload or thermal profiles. This paper underlines the role of communication fabric in data center energy consumption and presents a scheduling approach that combines energy efficiency and network awareness, termed DENS. The DENS methodology balances the energy consumption of a data center, individual job performance, and traffic demands. The proposed approach optimizes the tradeoff between job consolidation (to minimize the amount of computing servers) and distribution of traffic patterns (to avoid hotspots in the data center network).
Keywords :
computer centres; power aware computing; processor scheduling; DENS methodology; communication fabric; computing servers; data center energy consumption; data center energy efficient network aware scheduling; job consolidation; job distribution; job performance; traffic pattern; Bandwidth; Computer architecture; Energy consumption; Energy efficiency; Measurement; Processor scheduling; Servers; cloud computing; congestion; data center; energy-efficient; network-aware scheduling;
Conference_Titel :
Green Computing and Communications (GreenCom), 2010 IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom)
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-9779-9
Electronic_ISBN :
978-0-7695-4331-4
DOI :
10.1109/GreenCom-CPSCom.2010.31