Cloud Scalability Measurement and Testing

Author:

Bai Xiaoying1,Gao Jerry2,Tsai Wei-Tek3

Affiliation:

1. Tsinghua University, China

2. San Jose State University, USA

3. Tsinghua University, China & Arizona State University, USA

Abstract

Cloud computing introduces a new paradigm for software deployment, hosting, and service renting. Based on the XaaS architecture, a large number of users may share computing resources, platform services, and application software in a multi-tenancy approach. To ensure service availability, the system needs to support an advanced level of massive scalability so that it can provide necessary resources on demand following the pay-per-use pricing model. This chapter analyzes the unique requirements of cloud performance and scalability, compared with traditional distributed systems. Measurements are proposed with performance indicators, meters, and metrics identified from different perspectives. To support scalability testing in a dynamic environment, an agent-based testing framework is proposed to facilitate adaptive load generation and simulation using a two-layer control architecture.

Publisher

IGI Global

Reference39 articles.

1. Amazon. (n.d.). Amazon web service. Retrieved from http://aws.amazon.com/

2. Bai, X., Chen, B., Ma, B., & Gong, Y. (2011). Design of intelligent agent for collaborative testing of service-based systems. International Workshop on Automation of Software Test (pp. 22-28).

3. Bai, X., Dai, G., Xu, D., & Tsai, W.-T. (2006). A multi-agent based framework for collaborative testing on web services. International Workshop on Collaborative Computing, Integration, and Assurance (pp. 205-210).

4. Bai, X., Li, M., Chen, B., Gao, J., & Tsai, W. T. (2011). A survey of cloud testing tools. International Symposium on Service Oriented System Engineering (pp. 1-12).

5. Bai, X., Wang, Y., Dai, G., Tsai, W.-T., & Chen, Y. (2007). A framework for contract-based collaborative verification and validation of web services. International Conference on Component-Based Software Engineering (pp. 258-273).

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