Paper Info
Title
A hybrid instance-intensive workflow scheduling method in private cloud environment
Abstract
Aiming to solve the problem of instance-intensive workflow scheduling in private cloud environment, this paper first formulates a scheduling optimization model considering the communication time between tasks. The objective of this model is to minimize the execution time of all workflow instances. Then, a hybrid scheduling method based on the batch strategy and an improved genetic algorithm termed fragmentation based genetic algorithm is proposed according to the characters of instance-intensive cloud workflow, where task priority dispatching rules are also taken into account. Simulations are conducted to compare the proposed method with the canonical genetic algorithm and two heuristic algorithms. Our simulation results demonstrate that the proposed method can considerably enhance the search efficiency of the genetic algorithm and is able to considerably outperform the compared algorithms, in particular when the number of workflow instances is high and the computational resource available for optimization is limited.
Year
DOI
Venue
2019
10.1007/s11047-016-9600-3
Natural Computing
Keywords
DocType
Volume
Cloud computing, Private cloud, Workflow scheduling, Batch strategy, Heuristic algorithm, Genetic algorithm
Journal
18
Issue
ISSN
Citations 
4
1572-9796
2
PageRank 
References 
Authors
0.36
18
6
Name
Order
Citations
PageRank
Xin Ye151.41
Jia Li250.74
Sihao Liu320.36
Jiwei Liang420.36
Yaochu Jin523317.91
Yaochu Jin623317.91