scholarly journals A Cuckoo-based Workflow Scheduling Algorithm to Reduce Cost and Increase Load Balance in the Cloud Environment

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Shahin Ghasemi ◽  
Ali Hanani
Keyword(s):  
Load Balance ◽  
Scheduling Algorithm ◽  
Optimal Scheduling ◽  
Workflow Scheduling ◽  
Optimal Solutions ◽  
Cloud Environment ◽  
Swarm Optimization ◽  
Cuckoo Optimization Algorithm ◽  
Processing Resources ◽  
Np Problem

Workflow scheduling is one of the important issues in implementing workflows in the cloud environment. Workflow scheduling means how to allocate workflow resources to tasks based on requirements and features of the tasks. The problem of workflow scheduling in cloud computing is a very important issue and is an NP problem. The relevant scheduling algorithms try to find optimal scheduling of tasks on the available processing resources in such a way some qualitative criteria when executing the entire workflow are satisfied. In this paper, we proposed a new scheduling algorithm for workflows in the cloud environment using Cuckoo Optimization Algorithm (COA). The aims of the proposed algorithm are reducing the processing and transmission costs as well as maintaining a desirable load balance among the processing resources. The proposed algorithm is implemented in MATLAB and its performance is compared with Cat Swarm Optimization (CSO). The results of the comparisons showed that the proposed algorithm is superior to CSO in discovering optimal solutions.

Workflow scheduling algorithm based on load balance in grid

2011 ◽  
Vol 30 (12) ◽  
pp. 3184-3186
Author(s):  
Ming-quan WANG ◽  
Jiong YU ◽  
Yuan TIAN ◽  
Yun HAN
Keyword(s):  
Load Balance ◽  
Scheduling Algorithm ◽  
Workflow Scheduling

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

The Scheduling Algorithm of Grid Task Based on PSO and Cloud Model

2010 ◽  
Vol 439-440 ◽  
pp. 1487-1492 ◽  
Author(s):  
Shao Bo Zhong ◽  
Zhong Shi He
Keyword(s):  
Particle Swarm Optimization ◽  
Task Scheduling ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Cloud Model ◽  
Excess Entropy ◽  
Scheduling Algorithm ◽  
Particle Swarm ◽  
Optimal Solutions ◽  
Swarm Optimization

Grid task scheduling (GTS) is a NP-hard problem. This paper proposes an optimized GTS algorithm which combines with the advantages of cloud model based on the particle swarm optimization algorithm. This algorithm iterates tasks utilizing the advantages of particle swarm optimization algorithm and then gets a set of candidate solutions quickly. In addition, this algorithm modifies the value of entropy and excess entropy using the characteristics of cloud model and implements the transformation between qualitative variables and quantity of uncertain events. And this algorithm makes particles fly to the global optimal solutions by exact searching in local areas. Theoretical analysis and simulation results show that this algorithm makes load balance of resource efficiently. It also avoids the problems of genetic algorithm and basic particle swarm optimization algorithm, which would easily fall into local optimal solutions and premature convergence caused by too much selected pressure. This algorithm has the advantages of high precision and faster convergence and can be applied in task scheduling on computing grid.

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