<abstract xmlns="http://www.w3.org/1999/xhtml"><p> In order to solve the problems of security threats on workflow scheduling in cloud computing environments, the security of tasks and virtual machine resources are quantified using a cloud model, and the users’ satisfaction degree with the security of tasks assigned to the virtual resources is measured through the similarity of the security cloud. On this basis, combined with security, completion time and cost constraints, an optimized cloud workflow scheduling algorithm is proposed using a discrete particle swarm. The particle in the particle swarm indicates a different cloud workflow scheduling scheme. The particle changes its velocity and position using the evolution equation of the standard particle swarm algorithm, which ensures that it is a feasible solution through the feasible solution adjustment strategies. The simulation experiment results show that the algorithm has better comprehensive performance with respect to the security utility, completion time, cost and load balance compared to other similar algorithms.</p></abstract>

In order to solve the problems of security threats on workflow scheduling in cloud computing environments, the security of tasks and virtual machine resources are quantified using a cloud model, and the users’ satisfaction degree with the security of tasks assigned to the virtual resources is measured through the similarity of the security cloud. On this basis, combined with security, completion time and cost constraints, an optimized cloud workflow scheduling algorithm is proposed using a discrete particle swarm. The particle in the particle swarm indicates a different cloud workflow scheduling scheme. The particle changes its velocity and position using the evolution equation of the standard particle swarm algorithm, which ensures that it is a feasible solution through the feasible solution adjustment strategies. The simulation experiment results show that the algorithm has better comprehensive performance with respect to the security utility, completion time, cost and load balance compared to other similar algorithms.

An optimized scheduling algorithm on a cloud workflow using a discrete particle swarm

Department of Computer Science & Technology, Xinzhou Teachers’ University, Xinzhou City, CO 034000 China

College of Computer & Software, Taiyuan University of Technology, Taiyuan City, CO 030024 China

Cybernetics and Information Technologies

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

In order to solve the problems of security threats on workflow scheduling in cloud computing environments, the security of tasks and virtual machine resources...

An optimized scheduling algorithm on a cloud workflow using a discrete particle swarm

Data publikacji: 09 kwi 2014

Zakres stron: 25 - 39

DOI: https://doi.org/10.2478/cait-2014-0003

Słowa kluczowe
Scheduling algorithm, cloud workflow, discrete particle swarm, evolution equation

© by Cao Jianfang

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

An optimized scheduling algorithm on a cloud workflow using a discrete particle swarm

Data publikacji: 09 kwi 2014

Zakres stron: 25 - 39

DOI: https://doi.org/10.2478/cait-2014-0003

Słowa kluczoweScheduling algorithm, cloud workflow, discrete particle swarm, evolution equation

© by Cao Jianfang

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Słowa kluczowe
Scheduling algorithm, cloud workflow, discrete particle swarm, evolution equation