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Designing a Resilient SDN Framework with IoT Integration for Enhanced Network Reliability
The ever-expanding Internet of Things (IoT) landscape poses significant challenges for network reliability and resilience. This research investigates the design and implementation of a resilient Software-Defined Networking (SDN) framework with Internet of Things (IoT) integration, aiming to enhance...
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Main Authors: | , , , , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | The ever-expanding Internet of Things (IoT) landscape poses significant challenges for network reliability and resilience. This research investigates the design and implementation of a resilient Software-Defined Networking (SDN) framework with Internet of Things (IoT) integration, aiming to enhance network reliability. The proposed model, referred to as HybridSDN-IoT Resilience (HyRes), introduces a hybrid SDN approach by amalgamating traditional and distributed SDN strategies. This hybridization seeks to balance the advantages of centralized control and distributed resilience within the network architecture. To estimate the efficacy of the HyRes model implementation, comprehensive simulation analyses are conducted, comparing its performance against established algorithms in the SDN domain. Metrics such as network latency, packet loss, and throughput are employed to assess the reliability of the network under varying conditions. The simulation results offer significant performance results for the resilience and adaptability of HyRes in comparison to existing algorithms, showcasing its potential to mitigate network failures and enhance overall reliability. The proposed HyRes model not only establishes a foundation for resilient SDN architectures but also discourses the precise challenges in the integration of diverse IoT devices. By emphasizing adaptability and responsiveness, the research advances the discourse on the practical realization of reliable SDN frameworks in the context of emerging IoT technologies. |
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ISSN: | 2767-7788 |
DOI: | 10.1109/ICICT60155.2024.10544640 |