A Distributed SDN Controller for Distributed IoT

Firouzi, Ramin; Rahmani, Rahim

doi:10.1109/access.2022.3168299

Cited by 11 publications

(2 citation statements)

References 20 publications

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“…Edge intelligence: SDUAV networks must embrace the concept of utilizing capabilities for intelligent analysis and edge computing [102]. UAVs will function as edge nodes at the network's edge, processing localized information, analyzing data, and doing AI-driven work.…”

Section: A Visionsmentioning

confidence: 99%

Software-Defined UAV Networks for 6G Systems: Requirements, Opportunities, Emerging Techniques, Challenges, and Research Directions

Siddiki Abir,

Chowdhury,

Jang

2023

IEEE Open J. Commun. Soc.

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The ever-increasing demand for wireless communication has driven the development of innovative technologies to address the issues that conventional communication networks meet. To support autonomous devices in the sixth-generation (6G) and provide seamless wireless connectivity in inaccessible and hard-to-reach areas, the combination of software-defined networking (SDN) with unmanned aerial vehicles (UAVs) has already shown promises. As the traditional UAV-based cellular network encompasses challenges such as lack of centralized supervision, robust decision-making ability, and dynamic network management, the SDN platform could be an excellent alternative to offer aerial networking for future 6G ecosystem. However, the SDN-assisted UAV paradigm faces a set of challenges and critical issues. For instance, the network management and orchestration, resource allocation and optimization, handover mechanism, spectrum management, energy efficiency, integration of heterogeneous networks, and reliability, thus causing the decrease of quality of services of the SDN-enables UAV networks. To effectively address all these issues and identify the trends of software-defined UAV (SDUAV) networks, more research activities are needed. Unfortunately, there are not any specific guidelines in the literature that address each of these requirements, enabling technologies, emerging techniques, and future research directions in the context of SDN-based UAV networks to enable next-generation 6G systems. Therefore, motivated by this fact, this paper offers a comprehensive evaluation of the state of the SDUAV network and architecture, highlighting its various requirements and different prospects and applications in 6G systems. Besides, this paper also addresses why the combination of SDN and UAV-enabled networks is becoming essential in the 6G networking context and how it can offer more flexibility, scalability, reliability, and efficient connectivity than the conventional approaches to provide features like intelligence, automation, programmability, and centralized controllability. This paper furthermore outlines the difficulties of implementing SDUAV networks, such as security, adaptability, interference management, interoperability, and lack of standardization. Finally, to accomplish the goals, this article provides a roadmap for future trends and research directions in SDUAV networks to support the 6G systems.INDEX TERMS 6G, aerial base station, SDN, SDUAV, UAV-based cellular network. I. INTRODUCTIONThe growing trend of emerging technologies, such as artificial intelligence (AI), augmented reality (AR), virtual reality (VR), extended reality (XR), automated vehicles, electronic health (e-health), cloud computing, Internet of Things (IoT), and Industry 4.0, is culminating a massive amount of data every day [1]. Recently, the International Telecommunication Union (ITU) estimates that traffic volume will be 5016 EB/month, with traffic volume per person reaching 257.1 GB/month [2]. As a result, there will be 97 billion machine-to-machine (M...

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Section: A Visionsmentioning

confidence: 99%

Software-Defined UAV Networks for 6G Systems: Requirements, Opportunities, Emerging Techniques, Challenges, and Research Directions

Siddiki Abir,

Chowdhury,

Jang

2023

IEEE Open J. Commun. Soc.

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“…The system utilizes the available connectivity interfaces in the Edge Devices and Fog Open vSwitches to provide redundant paths for edge devices and Fog nodes. In light of SDN deployment for FL-enabled ITS, Qureshi et al [187] study a distributed SDN approach in a smart grid scenario. Each distributed controller is responsible for a specific domain, obtains a partial view of the network, and finally updates the global state.…”

Section: High Information Sensitivitymentioning

confidence: 99%

Enhanced Federated Learning for Edge Data Security in Intelligent Transportation Systems

Zhu

Yin

et al. 2023

IEEE Trans. Intell. Transport. Syst.

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AI‐driven network softwarization scheme for efficient message exchange in IoT environment beyond 5G

Jadav

Nair

Gupta

et al. 2022

Int J Communication

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SummaryInternet of things (IoT) has massively adopted the market due to the current era demanding fully intelligent and autonomous services. However, efficient network management and message exchange are challenging in a dynamic and energy‐constrained IoT environment. Hence, for efficient message passing in IoT applications, softwarization of the IoT network is essential, wherein the logical control plane is decoupled from the data plane consisting of hardware devices such as routers and switches. Using softwarization, a centralized software‐defined networking (SDN) controller is responsible for routing data packets from source to destination in a dynamic environment. However, to reduce the computational overhead of filtering malicious and nonmalicious packets, artificial intelligence (AI) classifiers prove beneficial. Moreover, such challenges have trade‐offs with network requirements such as ultralow latency, high reliability, and higher data rates. Motivated by this, we propose an AI‐enabled network softwarization scheme for efficient message exchange under the 6G network. Lastly, the performance of the proposed scheme is evaluated with different performance metrics, such as accuracy, precision, f1‐score, packet drop ratio, and latency. The empirical result revealed that the proposed scheme outperforms in terms of accuracy and controller efficiency, that is, 81.64% and 82.2%, respectively.

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A Distributed SDN Controller for Distributed IoT

Abstract: Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.

Cited by 11 publications

References 20 publications

Software-Defined UAV Networks for 6G Systems: Requirements, Opportunities, Emerging Techniques, Challenges, and Research Directions

Software-Defined UAV Networks for 6G Systems: Requirements, Opportunities, Emerging Techniques, Challenges, and Research Directions

Enhanced Federated Learning for Edge Data Security in Intelligent Transportation Systems

AI‐driven network softwarization scheme for efficient message exchange in IoT environment beyond 5G

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