SLA-constrained service selection for minimizing costs of providing composite cloud services under stochastic runtime performance.

Kuo-Chan Huang,Mu-Jung Tsai,Sin-Ji Lu,Chun-Hao Hung

doi:10.1186/s40064-016-1938-6

Kuo-Chan Huang, Mu-Jung Tsai + Show 2 more

Open Access

https://doi.org/10.1186/s40064-016-1938-6

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Journal: SpringerPlus	Publication Date: Mar 8, 2016
Citations: 9	License type: CC BY 4.0

Affiliation: National Taichung University of Education

Abstract

Composite cloud services based on the methodologies of Software as a Service and Service-Oriented Architecture are transforming how people develop and use software. Cloud service providers are confronting the service selection problem when composing composite cloud services. This paper deals with an important type of service selection problem, minimizing the total cost of providing a composite cloud service with respect to the constraints of service level agreement (SLA). Two types of SLA are considered in the study: per-request-based SLA and ratio-based SLA. We present three service selection approaches for dynamic cloud environments where services’ performance might vary with time. The first two are iterative compound approaches for per-request-based SLA and the third approach is a one-step method for ratio-based SLA based on the Chebyshev’s theorem and nonlinear programming. Experimental results show that our approaches outperform the previous method significantly in terms of total cost reduction.

Highlights

Cloud has become the most promising next-generation computing platform recently, and is usually divided into three layers of services (Buyya et al 2008; Rai et al 2015): Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS)
We focus on one important Quality of Service (QoS) aspect, the response time of the entire composite cloud service, and develop service selection approaches to minimizing the total costs for service providers under the regulation of service level agreement (SLA)
We focus on the issue of service selection which deals with the challenge regarding optimally selecting a service for each task in a composite cloud service from several functionally equivalent ones with an optimization objective for the entire composite cloud service under some QoS constraints

Summary

Introduction

Cloud has become the most promising next-generation computing platform recently, and is usually divided into three layers of services (Buyya et al 2008; Rai et al 2015): Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). The proposed approaches were evaluated with a series of simulation experiments and compared to the method in (Schuller et al 2012), which tries to reduce SLA violation by choosing services with smaller standard deviation of response time in the adaptation step of the iterative service selection process.

Results

Conclusion