@inproceedings{2f860c725b5c4dfa974372d719b69834,
title = "Energy efficiency evaluation of distributed systems",
abstract = "Rapid growth in Big Data and Cloud technologies has fueled rising energy demands in large server systems such as data centers, leading to a need for effective power management. In this paper, we investigate the energy consumption characteristics of data-intensive distributed applications in terms of the CPU and memory subsystem. To this end, we develop PowerSave as a lightweight software framework that enables dynamic reconfiguration of power limits. PowerSave uses Running Average Power Limit (RAPL) to impose power limits. Our evaluation study, conducted on three different real systems, demonstrates that for workloads typical of servers used in data centers, higher power caps correlate with higher overall CPU energy use.",
keywords = "Big Data, Cloud, Energy monitoring, Power management, RAPL, Virtualization",
author = "James Phung and Lee, {Young Choon} and Zomaya, {Albert Y.}",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-22750-0_75",
language = "English",
isbn = "9783030227494",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-VDI-Verlag GmbH & Co. KG",
pages = "756--763",
editor = "Rodrigues, {Jo{\~a}o M. F.} and Cardoso, {Pedro J. S.} and J{\^a}nio Monteiro and Roberto Lam and Krzhizhanovskaya, {Valeria V.} and Lees, {Michael H.} and Dongarra, {Jack J.} and Sloot, {Peter M. A.}",
booktitle = "Computational Science - ICCS 2019",
address = "Germany",
note = "19th International Conference on Computational Science, ICCS 2019 ; Conference date: 12-06-2019 Through 14-06-2019",
}