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A multi-tenant hierarchical modeling for cloud computing workload
An C.1; Zhou J.1; Liu S.1; Geihs K.2
2016-10-01
Source PublicationIntelligent Automation and Soft Computing
ISSN1079-8587
Volume22Issue:4Pages:579-586
Abstract

Diverse realistic workloads are urgently needed by SaaS providers and researchers to study the cloud environment. Workload model is an important way to specify and produce workloads. However, existing workload models are usually simplified. They cannot comprehensively describe the variations of the behaviors in user-level, application-level and service level in real environment. Moreover, existing workload models are aimed to only specific applications. They fail to support multi-users, multi-applications and multi-service-units in one workload model. To solve the problem, a hierarchical workload modeling approach is proposed in this paper. The approach constructs a cloud workload model on three layers: User, application, service-units. At each layer two key time-varying variations are captured; amount and composition. Then the workload model is the superposition of the three layers. The approach provides a unified model for different applications and various user behaviors. The experiments give the hierarchical workload models of three examples, which applications are Bag-of-Tasks, MapReduce and self-contained service-units. The experimental results show the flexibility of the novel workload modeling. Finally, architecture of a workload generator based on the model is given.

KeywordCloud Computing Hierarchical Workload Model Workload Generator
DOI10.1080/10798587.2016.1152774
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systemscomputer Science, Artificial Intelligence
WOS IDWOS:000393797100007
Scopus ID2-s2.0-84966703635
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Citation statistics
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorZhou J.
Affiliation1.College of Computer Science, Inner Mongolia University, Hohhot, China
2.EECS Department, Kassel University, Kassel, Germany
Recommended Citation
GB/T 7714
An C.,Zhou J.,Liu S.,et al. A multi-tenant hierarchical modeling for cloud computing workload[J]. Intelligent Automation and Soft Computing, 2016, 22(4), 579-586.
APA An C.., Zhou J.., Liu S.., & Geihs K. (2016). A multi-tenant hierarchical modeling for cloud computing workload. Intelligent Automation and Soft Computing, 22(4), 579-586.
MLA An C.,et al."A multi-tenant hierarchical modeling for cloud computing workload".Intelligent Automation and Soft Computing 22.4(2016):579-586.
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