Paper Info
Title
Efficient and dynamic scaling of fog nodes for IoT devices.
Abstract
It is predicted by the year 2020, more than 50 billion devices will be connected to the Internet. Traditionally, cloud computing has been used as the preferred platform for aggregating, processing, and analyzing IoT traffic. However, the cloud may not be the preferred platform for IoT devices in terms of responsiveness and immediate processing and analysis of IoT data and requests. For this reason, fog or edge computing has emerged to overcome such problems, whereby fog nodes are placed in close proximity to IoT devices. Fog nodes are primarily responsible of the local aggregation, processing, and analysis of IoT workload, thereby resulting in significant notable performance and responsiveness. One of the open issues and challenges in the area of fog computing is efficient scalability in which a minimal number of fog nodes are allocated based on the IoT workload and such that the SLA and QoS parameters are satisfied. To address this problem, we present a queuing mathematical and analytical model to study and analyze the performance of fog computing system. Our mathematical model determines under any offered IoT workload the number of fog nodes needed so that the QoS parameters are satisfied. From the model, we derived formulas for key performance metrics which include system response time, system loss rate, system throughput, CPU utilization, and the mean number of messages request. Our analytical model is cross-validated using discrete event simulator simulations.
Year
DOI
Venue
2017
https://doi.org/10.1007/s11227-017-2083-x
The Journal of Supercomputing
Keywords
Field
DocType
Internet of things,Fog computing,Edge computing,Cloud computing,Queuing theory,Performance modeling and analysis
Edge computing,Computer science,CPU time,Workload,Quality of service,Computer network,Queueing theory,Throughput,Distributed computing,Cloud computing,Scalability
Journal
Volume
Issue
ISSN
73
12
0920-8542
Citations 
PageRank 
References 
2
0.36
21
Authors
2
Name
Order
Citations
PageRank
Said El Kafhali1146.43
Khaled Salah253569.86