Abstract
Next-generation offshore wind farms are increasingly adopting vendor-agnostic software-defined networking (SDN) to oversee their Industrial Internet of Things Edge(IIoT-Edge) networks. The SDN-enabled IIoT-Edge networks present a promising solution for high availability and consistent performance-demanding environments such as offshore wind farm critical infrastructure monitoring, operation, and maintenance. Inevitably, these networks encounter stochastic failures such as random component malfunctions, software malfunctions, CPU overconsumption, and memory leakages. These stochastic failures result in intermittent network service interruptions, disrupting the real-time exchange of critical, latency-sensitive data essential for offshore wind farm operations. Given the criticality of data transfer in offshore wind farms, this paper investigates the dependability of the SDN-enabled IIoT-Edge networks amid the highlighted stochastic failures using a two-pronged approach to: (i) observe the transient behavior using a proof-of-concept simulation testbed and (ii) quantitatively assess the steady-state behavior using a probabilistic Homogeneous Continuous Time Markov Model (HCTMM) under varying failure and repair conditions. The study finds that network throughput decreases during failures in the transient behavior analysis. After quantitatively analyzing 15 case scenarios with varying failure and repair combinations, steady-state availability ranged from 93% to 98%, nearing the industry-standard SLA of 99.999%, guaranteeing up to 3 years of uninterrupted network service.
Original language | English |
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Pages (from-to) | 6126-6139 |
Number of pages | 14 |
Journal | IEEE Transactions on Network and Service Management |
Volume | 21 |
Issue number | 6 |
DOIs | |
Publication status | Published - 11 Sept 2024 |
Bibliographical note
Publisher Copyright:© 2004-2012 IEEE.
Funding
This research has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Innovative Tools for Cyber-Physical Energy Systems (InnoCyPES) project and the Marie Skłodowska-Curie grant agreement No 956433.
Funders | Funder number |
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Marie Sklodowska-Curie Innovative Training Network (EU) | 956433 |
Keywords
- Dependability
- Homogeneous Continuous time markov chain
- IEC61850
- IEEE802.1 Time Sensitive Networking
- Industrial Internet of Things
- Offshore wind
- Software defined networking
- edge computing