ASTAW : Auto-Scaling Threshold-based Approach for Web Application in Cloud Computing Environment

다국어 초록 (Multilingual Abstract)

In recent years, the number of users and service providers are increasing in using cloud services so the accessibility and the effective management of the required resources, irrespective of the time and place, seem to be of great importance for both sides. Improving the performance and utilization of the cloud systems are gained by the auto-scaling of the applications; this is because of the fact that, some approaches have been proposed for auto scaling. This paper seeks to checking some value, based on the learning automata, for the scalability of the web applications, which combines virtual machine clusters and the learning automata in order to provide the best possible way for the scaling up and scaling down of the virtual machines. The results of this study indicate how an increased capacity of virtual machine which have been done by the value of thresholds could effect on SLA and overhead of responding.

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. Related Works
• 3. The Proposed Approach
• 3.1 Scalability Framework
• 3.2 Learning Automata
• 3.3 The Proposed Algorithm (ASTAW)
• 4. Performance Evaluation
• 5. Conclusion and Further Work
• References