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.
Metadata
Item Type:
Article (Published)
Refereed:
Yes
Uncontrolled Keywords:
Wireless Networks; IoT; Fog Computing; SDN; Optimization
This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:
The National Natural Science Foundation of China grant no. 619020, National Key Research and Development Plan grant no. 2017YFC08210, Science and Technology Major Industrial Project of Liaoning Province grant no. 2020JH1/10100, Dalian Science and Technology Innovation Fund” grants no. 2019J11CY004 and 2020JJ26G, Science Foundation Ireland Research Centres Programme grants no.16/SP/3804 (ENA, Science Foundation Ireland Research Centres Programme grants no. 12/RC/2289 P2 (Insight), Fundamental Research Funds for the Central Universities grants no. DUT20ZD210 and DUT20T
ID Code:
26040
Deposited On:
29 Jun 2021 10:56 by
Gabriel Muntean
. Last Modified 05 Oct 2021 12:53