Title
Makespan-Cost-Reliability-Optimized Workflow Scheduling Using Evolutionary Techniques in Clouds.
Abstract
Most popular scientific workflow systems can now support the deployment of tasks to the cloud. The execution of workflow on cloud has become a multi-objective scheduling in order to meet the needs of users in many aspects. Cost and makespan are considered to be the two most important objects. In addition to these, there are some other Quality-of-Service (QoS) parameters including system reliability, energy consumption and so on. Here, we focus on three objectives: cost, makespan and system reliability. In this paper, we propose a Multi-objective Evolutionary Algorithm on the Cloud (MEAC). In the algorithm, we design some novel schemes including problem-specific encoding and also evolutionary operations, such as crossover and mutation. Simulations on real-world and random workflows are conducted and the results show that MEAC can get on average about 5% higher hypervolume value than some other workflow scheduling algorithms.
Year
DOI
Venue
2020
10.1142/S0218126620501674
JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS
Keywords
DocType
Volume
Workflow scheduling,cloud computing,multi-objective optimization,evolutionary algorithm
Journal
29
Issue
ISSN
Citations 
10.0
0218-1266
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Xiumin Zhou1222.71
Gongxuan Zhang29419.89
Wang Tian31715.16
Mingyue Zhang400.34
Xiji Wang500.34
Zhang Wei639253.03