Paper Info
Title
Task Placement Across Multiple Public Clouds With Deadline Constraints for Smart Factory.
Abstract
The smart factory of Industry 4.0 has been regarded as a solution for handling the increasing production complexity caused by growing global economy and demand for customized products. Besides, it will make the interactions between humans, machines, and products become a highly competitive area for market capitalization in the near feature. Nowadays, cloud computing with the high performance of computing and self-service access plays an important role in realizing smart factor. To minimize the overall cost of company in a heterogeneous cloud environment, including multiple public clouds, while ensuring a proper level of quality-of-service, task placement across multiple public clouds is a critical problem, where task deadlines and long-haul data transmission costs between smart factory and different clouds must be considered. We formulate this task placement problem as an integer linear program (ILP) to minimize company cost under the task deadline constraint. With extensive simulations, we evaluate the performance of our proposed ILP model in heterogeneous public clouds with finite and infinite resources.
Year
DOI
Venue
2018
10.1109/ACCESS.2017.2779462
IEEE ACCESS
Keywords
Field
DocType
Cloud computing,heterogeneous cloud,integral linear programming (ILP),task placement
Numerical models,Data transmission,Computer science,Market capitalization,Linear programming,Smart factory,Distributed computing,Cloud computing
Journal
Volume
ISSN
Citations 
6
2169-3536
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Boyu Li101.69
Zhipeng Zhao200.34
Yan Guan300.34
Ning Ai400.34
Xiaowen Dong524922.07
Bin Wu627138.89