Earticle

초록

영어

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

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

키워드

저자

• Monireh Fallah [ Department of Computer Engineering, Islamic Azad University of Mahallat, Mahallat, Iran ]
• Mostafa Ghobaei Arani [ Department of Computer Engineering, Islamic Azad University of Parand, Tehran, Iran ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605