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SLA-constrained service selection for minimizing costs of providing composite cloud services under stochastic runtime
Kuo-Chan Huang1, Mu-Jung Tsai1, Sin-Ji Lu1
1Department of Computer Science, National Taichung University of Education, No. 140, Min-Shen Road, Taichung, Taiwan.
Springerplus
|April 12, 2016
Summary
This study introduces new methods to solve the service selection problem in composite cloud services, significantly reducing costs. These approaches optimize service composition under service level agreement (SLA) constraints for dynamic cloud environments.
Area of Science:
- Computer Science
- Cloud Computing
- Software Engineering
Background:
- Composite cloud services, built on Software as a Service (SaaS) and Service-Oriented Architecture (SOA), are revolutionizing software development and usage.
- Cloud service providers face challenges in selecting the optimal services for composing composite cloud services.
Purpose of the Study:
- To address the service selection problem in composite cloud services, focusing on minimizing total cost.
- To develop efficient approaches for service selection under per-request-based and ratio-based Service Level Agreement (SLA) constraints.
Main Methods:
- Developed three novel service selection approaches for dynamic cloud environments.
- Two iterative compound approaches were designed for per-request-based SLA.
- A one-step nonlinear programming method, utilizing Chebyshev's theorem, was created for ratio-based SLA.
Main Results:
- The proposed approaches significantly outperform existing methods in reducing the total cost of composite cloud services.
- Demonstrated effectiveness in dynamic cloud environments where service performance fluctuates.
Conclusions:
- The presented service selection strategies offer substantial cost savings for composite cloud services.
- These methods provide effective solutions for optimizing service composition under various SLA constraints in evolving cloud landscapes.
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