Abstract
The integration of software-defined networking (SDN) into legacy networks causes both operational and deployment issues. In this context, this article proposes a novel approach, called An Intelligent Solution for Improved Performance of Reliable and Time-sensitive Flows in hybrid SDN-based fog computing IoT systems (IHSF). The proposed IHSF approach has three solutions: 1) a novel algorithm to deploy SDN switches between legacy switches to improve network observability; 2) a {K}-nearest neighbor regression algorithm to predict in real time the reliability of legacy links at the SDN controller based on historic data; this enables the SDN controller to make timely decisions, improving system performance; and 3) a reliable and time-sensitive deep deterministic policy gradient algorithm (RT-DDPG), which optimally computes forwarding paths in hybrid SDN-F for time-critical traffic flows generated by IoT applications. The simulation results show that our proposed IHSF solution has a better performance than the existing approach in terms of network observability time, number of disturbed flows, end-to-end delay, and packet delivery ratio.
Original language | English |
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Article number | 9199898 |
Pages (from-to) | 3130-3142 |
Number of pages | 13 |
Journal | IEEE Internet of Things Journal |
Volume | 8 |
Issue number | 5 |
DOIs | |
State | Published - 01 03 2021 |
Bibliographical note
Publisher Copyright:© 2014 IEEE.
Keywords
- Fog computing (FC)
- IoT
- hybrid software-defined networking (SDN)
- link failure
- machine learning