Autonomic resource management for power, performance, and security in cloud environment

Farah Fargo, Olivier Franza, Cihan Tunc, Salim Hariri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

High performance computing is widely used for large-scale simulations, designs and analysis of critical problems especially through the use of cloud computing systems nowadays because cloud computing provides ubiquitous, on-demand computing capabilities with large variety of hardware configurations including GPUs and FPGAs that are highly used for high performance computing. However, it is well known that inefficient management of such systems results in excessive power consumption affecting the budget, cooling challenges, as well as reducing reliability due to the overheating and hotspots. Furthermore, considering the latest trends in the attack scenarios and crypto-currency based intrusions, security has become a major problem for high performance computing. Therefore, to address both challenges, in this paper we present an autonomic management methodology for both security and power/performance. Our proposed approach first builds knowledge of the environment in terms of power consumption and the security tools' deployment. Next, it provisions virtual resources so that the power consumption can be reduced while maintaining the required performance and deploy the security tools based on the system behavior. Using this approach, we can utilize a wide range of secure resources efficiently in HPC system, cloud computing systems, servers, embedded systems, etc.

Original languageEnglish (US)
Title of host publication16th ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2019
PublisherIEEE Computer Society
ISBN (Electronic)9781728150529
DOIs
StatePublished - Nov 2019
Event16th ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2019 - Abu Dhabi, United Arab Emirates
Duration: Nov 3 2019Nov 7 2019

Publication series

NameProceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA
Volume2019-November
ISSN (Print)2161-5322
ISSN (Electronic)2161-5330

Conference

Conference16th ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2019
CountryUnited Arab Emirates
CityAbu Dhabi
Period11/3/1911/7/19

Keywords

  • Big Data Analytics
  • Cloud computing
  • High Performance Computing
  • Machine learning
  • Power and Performance Management
  • Security

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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