Software Defined IoT Systems: Properties, State of the Art, and Future Research

Mishra, Pritish; Puthal, Deepak; Tiwary, Mayank; Mohanty, Saraju P.

doi:10.1109/mwc.001.1900083

Cited by 34 publications

(14 citation statements)

References 14 publications

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“…5 This congestion arises as a result of varying computational capabilities of different devices, functioning on an IoT platform. Hence, appropriate protocol stack structures 6 have been experimented in the literature to avoid congestion in the delivery of services. Other issues related to 5G IoT networks include the green energy-based concepts 7 to reduce the CO 2 emissions, and intrusions in the cognitive networks 8 etc.…”

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confidence: 99%

Retracted: A hybrid‐supervised learning model for compressive spectrum sensing in fifth generation(5G) cognitive Radio enabled internet of things (IoT) networks

Jothiraj¹,

Sridevi²,

Rangaraj

2021

Int J Communication

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Summary 5G Internet of Things (IoT) networks are characterized by wideband radio frequency spectrum utility and are therefore of primary importance for efficient means of sensing the wideband spectrum characterized by high bandwidth. A cognitive radio network (CRN) intelligently does the sensing of authorized users ideal spectrum and allocates the same to the demanded unauthorized user. Conventional energy detection and k‐means schemes associated with CRN perform well for narrowband applications, whereas they are not quite suitable for wideband applications. Hence, a compressive collaborative sensing scheme together with deep neural network learning model (CCS‐DLNN) has been proposed to sense the information from the compressed and reconstructed information signal. Based on the extracted features, decision on presence or absence of primary user (PU) in the received signal has been observed. This paper proposes a deep learning neural network model for learning the dynamic change in the input spectra. Accordingly, this paper also updates the weights associated with the neurons to converge upon the target objective. The performance of the proposed sensing scheme has been evaluated pertaining to probability of detection, sensing error, and accuracy of detection of idle channels. The proposed work will be very useful for the upcoming generation departing to be implemented with 5G IoT networks.

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confidence: 99%

Retracted: A hybrid‐supervised learning model for compressive spectrum sensing in fifth generation(5G) cognitive Radio enabled internet of things (IoT) networks

Jothiraj¹,

Sridevi²,

Rangaraj

2021

Int J Communication

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“…Taking MAC address learning as an example, a conventional service switch determines whether to learn the source MAC address of a packet based on the switch configuration. On a service switch with control and forwarding separated, a packet is received through the device ingress and transferred to the controller, and then the controller determines whether to learn the MAC address of the packet and notifies the device [10].…”

Section: Implementation Pilotmentioning

confidence: 99%

Software Defined Network, The Design, Technique, and Internet of Things Defined in Campus Network

Tongkaw¹

2019

Int. j. technol. eng. stud.

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In the current research, Software Defined Network (SDN) is implemented and tested on campus networks to build a framework for easier and manageable, more extensive networks. SKRU deployed ONC software from Ruijie for network administration. The current study also defines the Internet of Things (IoT) devices among faculty, including IoT for Smart farm from agriculture faculty. In an SDN architecture, the ability to configure, manage, secure, and optimize network resources via software affords many benefits to enterprises. This article is contextualized from the concept of the IoT, its security, the interoperability of VLANs, and software-defined networks. By taking into account existing architectures and technologies, intelligent infrastructure is proposed to support all processes. Based on the implementation and evaluation of SDN, valuable insights and research directions are discussed.

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“…The above interrelated challenges can be answered by applying the software-defined networking (SDN) approach [5,6]. The core idea of SDN is the separation of data payloads from the controlling data that, in turns, determines the messages path.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Control Architecture Based on Software Defined Networking for the Internet of Things

et al. 2021

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Software Defined Networking (SDN) provides a new perspective for the Internet of Things (IoT), since, with the separation of the control from the data planes, it is viable to optimise the traditional networks operation management. In particular, the SDN Controller has a global vision of the network of sensors/actuators domain, allowing real-time network nodes and data flows reconfiguration. As a consequence, devices, usually facing limited communications and computing resources, are relieved of the route selection task in a distributed and, thus, suboptimal way. This paper proposes a SDN-IoT architecture, specifically focusing on the Controller design, which dynamically optimises in real time the end-to-end flows delivery. In particular, the dynamic routing policy adaptation is based on the real-time estimation of the network status and it allows jointly minimising the end-to-end latency and energy consumption and, consequently, to improve the network life time. The performance of the proposed approach is analysed in terms of the average latency, energy consumption and overhead, pointing out a better behaviour in comparison with the existing distributed approaches.

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Software Defined IoT Systems: Properties, State of the Art, and Future Research

Cited by 34 publications

References 14 publications

Retracted: A hybrid‐supervised learning model for compressive spectrum sensing in fifth generation(5G) cognitive Radio enabled internet of things (IoT) networks

Retracted: A hybrid‐supervised learning model for compressive spectrum sensing in fifth generation(5G) cognitive Radio enabled internet of things (IoT) networks

Software Defined Network, The Design, Technique, and Internet of Things Defined in Campus Network

Dynamic Control Architecture Based on Software Defined Networking for the Internet of Things

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