Paper Info
Title
Sosw: Scalable And Optimal Nearsighted Location Selection For Fog Node Deployment And Routing In Sdn-Based Wireless Networks For Iot Systems
Abstract
In a fog computing (FC) architecture, cloud services migrate towards the network edge and operate via edge devices such as access points (AP), routers, and switches. These devices become part of a virtualization infrastructure and are referred to as "fog nodes." Recently, software-defined networking (SDN) has been used in FC to improve its control and manageability. The current SDN-based FC literature has overlooked two issues: (a) fog nodes' deployment at optimal locations and (b) SDN best path computation for data flows based on constraints (i.e., end-to-end delay and link utilization). To solve these optimization problems, this paper suggests a novel approach, called scalable and optimal near-sighted location selection for fog node deployment and routing in SDN-based wireless networks for IoT systems (SOSW). First, the SOSW model uses singular-value decomposition (SVD) and QR factorization with column pivoting linear algebra methods on the traffic matrix of the network to compute the optimal locations for fog nodes, and second, it introduces a new heuristic-based traffic engineering algorithm, called the constraint-based shortest path algorithm (CSPA), which uses ant colony optimization (ACO) to optimize the path computation process for task offloading. The results show that our proposed approach significantly reduces average latency and energy consumption in comparison with existing approaches.
Year
DOI
Venue
2021
10.1007/s12243-021-00845-z
ANNALS OF TELECOMMUNICATIONS
Keywords
DocType
Volume
Wireless network, IoT, Fog computing, SDN, Optimization
Journal
76
Issue
ISSN
Citations 
5-6
0003-4347
2
PageRank 
References 
Authors
0.37
0
6
Name
Order
Citations
PageRank
Muhammad Ibrar1112.65
Lei Wang2434.83
Gabriel-Miro Muntean330.71
Nadir Shah420.37
Aamir Akbar5144.03
Khalid Ibrahim Qureshi620.70