scholarly journals A particle swarm optimization and min–max-based workflow scheduling algorithm with QoS satisfaction for service-oriented grids

2016 ◽  
Vol 73 (5) ◽  
pp. 2018-2051 ◽  
Author(s):  
Faruku Umar Ambursa ◽  
Rohaya Latip ◽  
Azizol Abdullah ◽  
Shamala Subramaniam
Keyword(s):  
Particle Swarm Optimization ◽  
Scheduling Algorithm ◽  
Particle Swarm ◽  
Workflow Scheduling ◽  
Swarm Optimization ◽  
Service Oriented

A particle swarm optimization-based workflow scheduling algorithm in the cloud computing enveronment

2015 ◽  
Vol 60 (4) ◽  
pp. 47-55
Author(s):  
Phan Thanh Toàn ◽  
Nguyễn Thế Lộc ◽  
Nguyễn Doãn Cường ◽  
Đỗ Như Long
Keyword(s):  
Cloud Computing ◽  
Particle Swarm Optimization ◽  
Scheduling Algorithm ◽  
Particle Swarm ◽  
Workflow Scheduling ◽  
Swarm Optimization

Job Scheduling Algorithm for Cloud Computing Based on Particle Swarm Optimization

2013 ◽  
Vol 662 ◽  
pp. 957-960 ◽  
Author(s):  
Jing Liu ◽  
Xing Guo Luo ◽  
Xing Ming Zhang ◽  
Fan Zhang
Keyword(s):  
Cloud Computing ◽  
Particle Swarm Optimization ◽  
High Performance ◽  
Large Scale ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Autonomous Systems ◽  
Particle Swarm ◽  
Cost Benefit ◽  
Swarm Optimization

Cloud computing is an emerging high performance computing environment with a large scale, heterogeneous collection of autonomous systems and flexible computational architecture. The performance of the scheduling system influences the cost benefit of this computing paradigm. To reduce the energy consumption and improve the profit, a job scheduling model based on the particle swarm optimization(PSO) algorithm is established for cloud computing. Based on open source cloud computing simulation platform CloudSim, compared to GA and random scheduling algorithms, the results show that the proposed algorithm can obtain a better solution concerning the energy cost and profit.

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