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Research Article

Intelligent SDN Architecture With Fuzzy Neural Network and Blockchain for Monitoring Critical Events

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Article: 2145634 | Received 18 Apr 2022, Accepted 04 Nov 2022, Published online: 21 Nov 2022

Figures & data

Figure 1. SDN architecture of a transport IoT environment.

Figure 1. SDN architecture of a transport IoT environment.

Figure 2. Subsystem for analysis and detection of atypical data packets.

Figure 2. Subsystem for analysis and detection of atypical data packets.

Figure 3. Architecture of fuzzy neural network.

Figure 3. Architecture of fuzzy neural network.

Figure 4. Diagrams of the dependence of the delay on the number of sensor nodes and the number of packets.

Figure 4. Diagrams of the dependence of the delay on the number of sensor nodes and the number of packets.

Figure 5. Comparison of the response time of a traditional SDN network and an SDN network with an HNS and an LHS algorithm.

Figure 5. Comparison of the response time of a traditional SDN network and an SDN network with an HNS and an LHS algorithm.

Figure 6. Comparison of throughput in SDN network with traditional architecture and in SDN network with HNS and LHS algorithm.

Figure 6. Comparison of throughput in SDN network with traditional architecture and in SDN network with HNS and LHS algorithm.

Table 1. Atypical packet detection accuracy.