FFMRA: A fully fair multi-resource allocation algorithm in cloud environments
Authors: Hamzeh, H., Meacham, S., Khan, K., Phalp, K. and Stefanidis, A.
Journal: Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019
Pages: 279-286
ISBN: 9781728140346
DOI: 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00091
Abstract:The need for effective and fair resource allocation in cloud computing has been identified in the literature and in industrial contexts for a while. Cloud computing seen as a promising technology, offers usage-based payment, scalable and on-demand computing resources. However, during the past decade, the growing complexity of the IT world has resulted in making Quality of Service (QoS) in the cloud a challenging subject and an NP-hard problem. Specifically, the fair allocation of resources in the cloud becomes particularly interesting when many users submit several tasks which require multiple resources. Research in this area has been increasing since 2012 by introducing the Dominant Resource Fairness (DRF) algorithm as an initial attempt to solve the fair resource allocation problem in the cloud. Although DRF meets a sort of desirable fairness properties, it has been proven to be inefficient in certain conditions. Noticeably, DRF and other works in its extension are not intuitively fair after all. Those implementations have been unable to utilize all the resources in the system, leaving the system in an imbalanced situation with respect to each specific system resource. In order to address those issues, we propose in this paper a novel algorithm namely a Fully Fair Multi-Resource Allocation Algorithm in Cloud Environments (FFMRA) which allocates resources in a fully fair way considering both dominant and non-dominant shares. The results from the experiments conducted in CloudSim show that FFMRA provides approximately 100% recourse utilization, and distributing them fairly among the users while meeting desirable fairness features.
https://eprints.bournemouth.ac.uk/32656/
Source: Scopus
FFMRA: A Fully Fair Multi-Resource Allocation Algorithm in Cloud Environments
Authors: Hamzeh, H., Meacham, S., Khan, K., Phalp, K. and Stefanidis, A.
Journal: 2019 IEEE SMARTWORLD, UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTING, SCALABLE COMPUTING & COMMUNICATIONS, CLOUD & BIG DATA COMPUTING, INTERNET OF PEOPLE AND SMART CITY INNOVATION (SMARTWORLD/SCALCOM/UIC/ATC/CBDCOM/IOP/SCI 2019)
Pages: 279-286
DOI: 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00091
https://eprints.bournemouth.ac.uk/32656/
Source: Web of Science (Lite)
FFMRA: A Fully Fair Multi-Resource Allocation Algorithm in Cloud Environments
Authors: Hamzeh, H., Meacham, S., Khan, K., Phalp, K. and Stefanidis, A.
Conference: The 3rd IEEE Symposium on Software Engineering for Smart Systems (SSESS) 2019
Dates: 19-23 August 2019
Pages: 279-286
Publisher: IEEE
Abstract:The need for effective and fair resource allocation in cloud computing has been identified in the literature and in industrial contexts for some time now. Cloud computing, as a promising technology, offers usage-based payment, ondemand computing resources. However, in the recent decade, the growing complexity of the IT world resulted in making Quality of Service (QoS) in the cloud a challenging subject and an NP-hard problem. Specifically, fair allocation of resources in the cloud is one of the most important aspects of QoS that becomes more interesting especially when many users submit their tasks and requests include multiple resources. Research in this area has been considered since 2012 by introducing Dominant Resource Fairness (DRF) algorithm as an initial attempt to solve the resource fair allocation problem in the cloud. Although DRF has some good features in terms of fairness, it has been proven inefficient in some conditions.
Remarkably, DRF and other works in its extension are not proven intuitively fair after all. These implementations have been unable to utilize all the resources in the system and more specifically, they leave the system in an imbalanced situation with respect to each specific resource. To tackle those problems, in this paper we propose a novel algorithm namely FFMRA inspired by DRF which allocate resources in a fully fair way considering both dominant and non-dominant shares.
The results from the experiments show that our proposed method provides approximately 100% utilization of resources and distributes them fairly among the users and meets good fairness properties.
https://eprints.bournemouth.ac.uk/32656/
Source: Manual
FFMRA: A Fully Fair Multi-Resource Allocation Algorithm in Cloud Environments.
Authors: Hamzeh, H., Meacham, S., Khan, K., Phalp, K. and Stefanidis, A.
Journal: SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI
Pages: 279-286
Publisher: IEEE
ISBN: 978-1-7281-4034-6
https://eprints.bournemouth.ac.uk/32656/
https://ieeexplore.ieee.org/xpl/conhome/9036713/proceeding
Source: DBLP
FFMRA: A Fully Fair Multi-Resource Allocation Algorithm in Cloud Environments
Authors: Hamzeh, H., Meacham, S., Khan, K., Phalp, K.T. and Stefanidis, A.
Conference: The 3rd IEEE Symposium on Software Engineering for Smart Systems (SSESS) 2019
Publisher: IEEE
Abstract:The need for effective and fair resource allocation in cloud computing has been identified in the literature and in industrial contexts for some time now. Cloud computing, as a promising technology, offers usage-based payment, ondemand computing resources. However, in the recent decade, the growing complexity of the IT world resulted in making Quality of Service (QoS) in the cloud a challenging subject and an NP-hard problem. Specifically, fair allocation of resources in the cloud is one of the most important aspects of QoS that becomes more interesting especially when many users submit their tasks and requests include multiple resources. Research in this area has been considered since 2012 by introducing Dominant Resource Fairness (DRF) algorithm as an initial attempt to solve the resource fair allocation problem in the cloud. Although DRF has some good features in terms of fairness, it has been proven inefficient in some conditions. Remarkably, DRF and other works in its extension are not proven intuitively fair after all. These implementations have been unable to utilize all the resources in the system and more specifically, they leave the system in an imbalanced situation with respect to each specific resource. To tackle those problems, in this paper we propose a novel algorithm namely FFMRA inspired by DRF which allocate resources in a fully fair way considering both dominant and non-dominant shares. The results from the experiments show that our proposed method provides approximately 100% utilization of resources and distributes them fairly among the users and meets good fairness properties.
https://eprints.bournemouth.ac.uk/32656/
Source: BURO EPrints