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Cloud Scalability Measurement and Testing

Cloud Scalability Measurement and Testing

Xiaoying Bai, Jerry Zeyu Gao, Wei-Tek Tsai
ISBN13: 9781466625365|ISBN10: 1466625368|EISBN13: 9781466625372
DOI: 10.4018/978-1-4666-2536-5.ch017
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MLA

Bai, Xiaoying, et al. "Cloud Scalability Measurement and Testing." Software Testing in the Cloud: Perspectives on an Emerging Discipline, edited by Scott Tilley and Tauhida Parveen, IGI Global, 2013, pp. 356-381. https://doi.org/10.4018/978-1-4666-2536-5.ch017

APA

Bai, X., Gao, J. Z., & Tsai, W. (2013). Cloud Scalability Measurement and Testing. In S. Tilley & T. Parveen (Eds.), Software Testing in the Cloud: Perspectives on an Emerging Discipline (pp. 356-381). IGI Global. https://doi.org/10.4018/978-1-4666-2536-5.ch017

Chicago

Bai, Xiaoying, Jerry Zeyu Gao, and Wei-Tek Tsai. "Cloud Scalability Measurement and Testing." In Software Testing in the Cloud: Perspectives on an Emerging Discipline, edited by Scott Tilley and Tauhida Parveen, 356-381. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2536-5.ch017

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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.

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