Title
A Resource Management Model for Distributed Multi-Task Applications in Fog Computing Networks
Abstract
While the effectiveness of fog computing in Internet of Things (IoT) applications has been widely investigated in various studies, there is still a lack of techniques to efficiently utilize the computing resources in a fog platform to maximize Quality of Service (QoS) and Quality of Experience (QoE). This paper presents a resource management model for service placement of distributed multitasking applications in fog computing through mathematical modeling of such a platform. Our main design goal is to reduce communication between the candidate nodes hosting different task modules of an application by selecting a group of nodes near each other and as close to the source of the data as possible. We propose a method based on a greedy principle that demonstrates a highly scalable and near-optimal performance for resource mapping problems for multitasking applications in fog computing networks. Compared with the commercial Gurobi optimizer, our proposed algorithm provides a mapping solution that obtains 93% of the performance, attributed to a higher communication cost, while outperforming the reference method in terms of the computing speed, cutting the mapping execution time to less than 1% of that of the Gurobi optimizer.
Year
DOI
Venue
2021
10.1109/ACCESS.2021.3127355
IEEE ACCESS
Keywords
DocType
Volume
Edge computing, Cloud computing, Task analysis, Resource management, Costs, Computational modeling, Delays, Greedy, fog computing, Internet of Things, modelling, optimization, resource management
Journal
9
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Farhoud Hosseinpour100.34
Ahmad Naebi200.34
Seppo Virtanen300.34
Tapio Pahikkala400.34
Hannu Tenhunen51709190.57
Juha Plosila600.34