Holistic Resource Management for Sustainable and Reliable Cloud Computing : An Innovative Solution to Global Challenge

Gill, Sukhpal Singh and Garraghan, Peter and Stankovski, Vlado and Casale, Giuliano and Thulasiram, Ruppa K. and Ghosh, Soumya K. and Ramamohanarao, Kotagiri and Buyya, Rajkumar (2019) Holistic Resource Management for Sustainable and Reliable Cloud Computing : An Innovative Solution to Global Challenge. Journal of Systems and Software, 155. pp. 104-129. ISSN 0164-1212

[thumbnail of Holistic Resource Management for Sustainable and Reliable Cloud Computing]
PDF (Holistic Resource Management for Sustainable and Reliable Cloud Computing)
Holistic_Resource_Management_for_Sustainable_and_Reliable_Cloud_Computing.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.

Download (2MB)


Minimizing the energy consumption of servers within cloud computing systems is of upmost importance to cloud providers towards reducing operational costs and enhancing service sustainability by consolidating services onto fewer active servers. Moreover, providers must also provision high levels of availability and reliability, hence cloud services are frequently replicated across servers that subsequently increases server energy consumption and resource overhead. These two objectives can present a potential conflict within cloud resource management decision making that must balance between service consolidation and replication to minimize energy consumption whilst maximizing server availability and reliability, respectively. In this paper, we propose a cuckoo optimization-based energy-reliability aware resource scheduling technique (CRUZE) for holistic management of cloud computing resources including servers, networks, storage, and cooling systems. CRUZE clusters and executes heterogeneous workloads on provisioned cloud resources and enhances the energy-efficiency and reduces the carbon footprint in datacenters without adversely affecting cloud service reliability. We evaluate the effectiveness of CRUZE against existing state-of-the-art solutions using the CloudSim toolkit. Results indicate that our proposed technique is capable of reducing energy consumption by 20.1% whilst improving reliability and CPU utilization by 17.1% and 15.7% respectively without affecting other Quality of Service parameters.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Systems and Software
Additional Information:
This is the author’s version of a work that was accepted for publication in Journal of Systems and Software. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Systems and Software, 155, 2019 DOI: 10.1016/j.jss.2019.05.025
Uncontrolled Keywords:
?? cloud computingenergy consumptionsustainabilityreliabilityholistic managementcloud datacentershardware and architecturesoftwareinformation systems ??
ID Code:
Deposited By:
Deposited On:
22 Jun 2019 09:12
Last Modified:
15 Jul 2024 19:24