NDLI: Improving Resource Utilisation in the Cloud Environment Using Multivariate Probabilistic Models

Content Provider	IEEE Xplore Digital Library
Author	Sijin He Li Guo Ghanem, M. Yike Guo
Copyright Year	2012
Abstract	Resource provisioning based on virtual machine (VM) has been widely accepted and adopted in cloud computing environments. A key problem resulting from using static scheduling approaches for allocating VMs on different physical machines (PMs) is that resources tend to be not fully utilised. Although some existing cloud reconfiguration algorithms have been developed to address the problem, they normally result in high migration costs and low resource utilisation due to ignoring the multi-dimensional characteristics of VMs and PMs. In this paper we present and evaluate a new algorithm for improving resource utilisation for cloud providers. By using a multivariate probabilistic model, our algorithm selects suitable PMs for VM re-allocation which are then used to generate a reconfiguration plan. We also describe two heuristics metrics which can be used in the algorithm to capture the multi-dimensional characteristics of VMs and PMs. By combining these two heuristics metrics in our experiments, we observed that our approach improves the resource utilisation level by around 8% for cloud providers, such as IC Cloud, which accept user-defined VM configurations and 14% for providers, such as Amazon EC2, which only provide limited types of VM configurations.
Starting Page	574
Ending Page	581
File Size	697618
Page Count	8
File Format	PDF
ISBN	9781467328920
ISSN	21596190
DOI	10.1109/CLOUD.2012.66
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Cloud computing Algorithms Cloud Computing Heuristic algorithms Resource Allocation Heuristics Gaussian distribution Vectors Resource management Mathematical model Resource Management
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Research on dynamic resource allocation with cooperation strategy in cloud computing

Dynamic resource allocation in cloud using bin-packing technique

System resource allocation algorithm for multi-tenant SaaS application

Modified Elite Chaotic Immune Clonal Selection Algorithm for sever resource allocation in cloud computing systems

A universal fairness evaluation framework for resource allocation in cloud computing

Cloud-Computing-Based Resource Allocation Research on the Perspective of Improved Ant Colony Algorithm

Minimum Cost Maximum Flow Algorithm for Dynamic Resource Allocation in Clouds

Scheduling algorithm research for spatial information service under cloud environment

Study on cloud resource allocation strategy based on particle swarm ant colony optimization algorithm

Improving Resource Utilisation in the Cloud Environment Using Multivariate Probabilistic Models

Similar Documents

Research on dynamic resource allocation with cooperation strategy in cloud computing

Dynamic resource allocation in cloud using bin-packing technique

System resource allocation algorithm for multi-tenant SaaS application

Modified Elite Chaotic Immune Clonal Selection Algorithm for sever resource allocation in cloud computing systems

A universal fairness evaluation framework for resource allocation in cloud computing

Cloud-Computing-Based Resource Allocation Research on the Perspective of Improved Ant Colony Algorithm

Minimum Cost Maximum Flow Algorithm for Dynamic Resource Allocation in Clouds

Scheduling algorithm research for spatial information service under cloud environment

Study on cloud resource allocation strategy based on particle swarm ant colony optimization algorithm

Improving Resource Utilisation in the Cloud Environment Using Multivariate Probabilistic Models