Paper Info
Title
Improved Particle Swarm Optimization Based Workflow Scheduling in Cloud-Fog Environment.
Abstract
Mobile edge devices with high requirements typically need to obtain faster response on local network services. Fog computing is an emerging computing paradigm motivated by this need, which currently is viewed as an extension of cloud computing. This computing paradigm is presented to provide low commutation latency service for workflow applications. However, how to schedule workflow applications for seeking the tradeoff between makespan and cost in cloud-fog environment is facing huge challenge. To address this issue, in current paper, we propose a workflow scheduling algorithm based on improved particle swarm optimization (IPSO), where a nonlinear decreasing function of inertia weight in PSO is designed for promoting PSO to gain the optimal solution. Finally, comprehensive simulation experiment results show that our proposed scheduling algorithm is more cost-effective and can obtain better performance than baseline approach.
Year
DOI
Venue
2018
10.1007/978-3-030-11641-5_27
Business Process Management Workshops
Field
DocType
Citations 
Particle swarm optimization,Job shop scheduling,Systems engineering,Computer science,Latency (engineering),Scheduling (computing),Edge device,Local area network,Workflow,Distributed computing,Cloud computing
Conference
1
PageRank 
References 
Authors
0.35
12
7
Name
Order
Citations
PageRank
Rongbin Xu13710.01
Yeguo Wang210.35
Yongliang Cheng3101.83
Yuanwei Zhu410.35
Ying Xie54714.48
Abubakar Sadiq Sani610.35
Dong Yuan776848.06