Security supportive energy-aware scheduling and energy policies for cloud environments
Authors:
- Damián Fernández-Cerero,
- Agnieszka Jakóbik,
- Daniel Grzonka,
- Joanna Kołodziej,
- Alejandro Fernández-Montes
Abstract
Cloud computing (CC) systems are the most popular computational environments for providing elastic and scalable services on a massive scale. The nature of such systems often results in energy-related problems that have to be solved for sustainability, cost reduction, and environment protection. In this paper we defined and developed a set of performance and energy-aware strategies for resource allocation, task scheduling, and for the hibernation of virtual machines. The idea behind this model is to combine energy and performance-aware scheduling policies in order to hibernate those virtual machines that operate in idle state. The efficiency achieved by applying the proposed models has been tested using a realistic large-scale CC system simulator. Obtained results show that a balance between low energy consumption and short makespan can be achieved. Several security constraints may be considered in this model. Each security constraint is characterized by: (a) Security Demands (SD) of tasks; and (b) Trust Levels (TL) provided by virtual machines. SD and TL are computed during the scheduling process in order to provide proper security services. Experimental results show that the proposed solution reduces up to 45% of the energy consumption of the CC system. Such significant improvement was achieved by the combination of an energy-aware scheduler with energy-efficiency policies focused on the hibernation of VMs.
- Record ID
- CUTb9fb89fa76b14fe2883d2964f8c5c2c2
- Publication categories
- ;
- Author
- Journal series
- Journal of Parallel and Distributed Computing, ISSN 0743-7315, e-ISSN 1096-0848
- Issue year
- 2018
- Vol
- 119
- Pages
- 191-202
- Other elements of collation
- rys.; tab.; wykr.; Bibliografia (na s.) - 200-201; Bibliografia (liczba pozycji) - 70; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 119
- Keywords in English
- cloud computing, energy efficiency, independent task scheduling, genetic algorithms, VM hibernating, cloud security
- DOI
- DOI:10.1016/j.jpdc.2018.04.015 Opening in a new tab
- URL
- https://www.sciencedirect.com/science/article/pii/S0743731518302843 Opening in a new tab
- Language
- eng (en) English
- Score (nominal)
- 30
- Publication indicators
- = 38
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUTb9fb89fa76b14fe2883d2964f8c5c2c2/
- URN
urn:pkr-prod:CUTb9fb89fa76b14fe2883d2964f8c5c2c2
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.