earticle

논문검색

A Cost-AWARE Approach Based ON Learning Automata FOR Resource Auto-Scaling IN Cloud Computing Environment

초록

영어

In recent years, applications of cloud services have been increasingly expanded. Cloud services, are distributed infrastructures which develop the communication and services. Auto scaling is one of the most important features of cloud services which dedicates and retakes the allocated dynamic resource in proportion to the volume of requests. The Scaling tries to utilize maximum power of the available resources also to use idle resources, in order to maximize the efficiency or shutdown unnecessary resources to reduce the cost of running requests. In this paper, we have suggested an approach based on learning automata for resource auto-scaling, in order to manage and optimize factor cost. Results of simulation show that proposed approach has been able to optimize cost compared to the other approaches.

목차

Abstract
 1. Introduction
 2. Related Works
 3. The Proposed Approach
  3.1 Learning Automata
  3.2 The Proposed Algorithm
 4. Performance Evaluation
  4.1 Evaluation Results
 5. Conclusion and Further Work
 References

저자정보

  • Khosro Mogoui 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

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.