Title
A tenant-based resource allocation model for scaling Software-as-a-Service applications over cloud computing infrastructures
Abstract
Cloud computing provides on-demand access to computational resources which together with pay-per-use business models, enable application providers seamlessly scaling their services. Cloud computing infrastructures allow creating a variable number of virtual machine instances depending on the application demands. An attractive capability for Software-as-a-Service (SaaS) providers is having the potential to scale up or down application resources to only consume and pay for the resources that are really required at some point in time; if done correctly, it will be less expensive than running on regular hardware by traditional hosting. However, even when large-scale applications are deployed over pay-per-use cloud high-performance infrastructures, cost-effective scalability is not achieved because idle processes and resources (CPU, memory) are unused but charged to application providers. Over and under provisioning of cloud resources are still unsolved issues. Even if peak loads can be successfully predicted, without an effective elasticity model, costly resources are wasted during nonpeak times (underutilization) or revenues from potential customers are lost after experiencing poor service (saturation). This work attempts to establish formal measurements for under and over provisioning of virtualized resources in cloud infrastructures, specifically for SaaS platform deployments and proposes a resource allocation model to deploy SaaS applications over cloud computing platforms by taking into account their multi-tenancy, thus creating a cost-effective scalable environment.
Year
DOI
Venue
2013
10.1016/j.future.2011.10.013
Future Generation Comp. Syst.
Keywords
Field
DocType
software-as-a-service application,tenant-based resource allocation model,cloud computing platform,saas application,application provider,cloud computing infrastructure,cloud computing,cloud resource,pay-per-use cloud,cloud infrastructure,application resource,application demand,multi tenancy,software as a service,resource allocation
Virtual machine,Computer science,Multitenancy,Software as a service,Provisioning,Real-time computing,Resource allocation,Utility computing,Cloud computing,Scalability,Distributed computing
Journal
Volume
Issue
ISSN
29
1
0167-739X
Citations 
PageRank 
References 
49
1.62
41
Authors
6
Name
Order
Citations
PageRank
Javier Espadas11076.18
Arturo Molina264269.86
Guillermo Jiménez3542.70
Martín Molina413414.28
RaúL RamíRez5491.62
David Concha6794.62