Earticle

초록

영어

A major challenge facing cloud computing is virtual resource allocation with dynamic characteristics. Evaluation of a resource allocation strategy using a single aspect can no longer meet the real world demands. We resolve this issue from the perspectives of users and resource providers using a particle swarm algorithm for resource allocation. With this algorithm, we establish an allocation model using the shortest task completion time and the lowest cost as the constraints. The fast convergence rate of the particle swarm algorithm is then used to find the optimal solution for resource allocation. The velocity weight of each particle is self-adaptively adjusted based on the fitness value of each particle, resulting in an improvement in the global optimization and convergence capabilities. Finally, a simulation with the CloudSim platform shows that this algorithm can take into account the completion time and cost, which ensures the minimum cost in the shortest possible time to complete the task to improve resource utilization.

목차

Abstract
 1. Introduction
 2. The Cloud Computing Resource Scheduling Model
  2.1. The DAG Scheduling Model
  2.2. The Resource Scheduling Model in the Cloud Computing Environment
 3. Virtual Resource Scheduling Based on the Improved Particle Swarm Algorithm
  3.1. Improved Particle Swarm Optimisation (Ipso)
  3.2. Ipso-Based Virtual Resource Scheduling
 3. Simulation Results and Analysis
 4. Conclusion
 References

키워드

저자

• Youwei Shao [ School of Applied Electronics，Chongqing College of Electronic Engineering, Chongqing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605