Mininet-WiFi as Software-Defined Wireless Network Testing Platform

Kaur, Kirandeep; Kaur, Sukhveer; Kumar, Krishan; Aggarwal, Naveen; Mangat, Veenu

doi:10.1201/9781003185543-8

Cited by 22 publications

(23 citation statements)

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“…In this subsection, we present and discuss the experimental results of our adaptive SDN-based QoS framework. Our adaptive QoS framework was evaluated using Mininet software [ 29 ]. Mininet is an open-source network emulator that permits users to build virtual software-defined networks composed of an OpenFlow controller, a network of multiple OpenFlow-based Ethernet switches, and multiple hosts connected to those switches.…”

Section: Results and Discussionmentioning

confidence: 99%

Integrating Deep Learning-Based IoT and Fog Computing with Software-Defined Networking for Detecting Weapons in Video Surveillance Systems

Fathy

Saleh

2022

Sensors

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Due to the widespread proliferation of multimedia traffic resulting from Internet of Things (IoT) applications and the increased use of remote multimedia-based applications, as a consequence of COVID-19, there is an urgent need to develop intelligent adaptive techniques that improve the Quality of Service (QoS) perceived by end-users. In this work, we investigate the integration of deep learning techniques with Software-Defined Network (SDN) architecture to support delay-sensitive applications in IoT environments. Weapon detection in real-time video surveillance applications is deployed as our case study upon which multiple deep learning-based models are trained and evaluated for detection using precision, recall, and mean absolute precision. The deep learning model with the highest performance is then deployed within a proposed artificial intelligence model at the edge to extract the first detected video frames containing weapons for quick transmission to authorities, thus helping in the early detection and prevention of different kinds of crimes, and at the same time decreasing the bandwidth requirements by offloading the communication network from massive traffic transmission. Performance improvement is achieved in terms of delay, throughput, and bandwidth requirements by dynamically programming the network to provide different QoS based on the type of offered traffic and current traffic load, and based on the destination of the traffic. Performance evaluation of the proposed model was carried out using the mininet emulator, which revealed improvement of up to 75.0% in terms of average throughput, up to 14.7% in terms of mean jitter, and up to 32.5% in terms of packet loss.

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Section: Results and Discussionmentioning

confidence: 99%

Integrating Deep Learning-Based IoT and Fog Computing with Software-Defined Networking for Detecting Weapons in Video Surveillance Systems

Fathy

Saleh

2022

Sensors

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“…We have deployed 6 OpenMotes-CC2538 nodes [20] running Open-WSN REL-1.24.0 to build the 6TiSCH network. For the wired network, we have emulated 7 OpenFlow-enabled switches through Mininet [21]. In order to orchestrate both networks we use ONOS 2.1.0 which includes the Whisper module 1 .…”

Section: Resultsmentioning

confidence: 99%

Leveraging Distributed Protocols for full End-to-End Softwarization in IoT Networks

Municio

Balemans

Latré

et al. 2020

2020 IEEE 17th Annual Consumer Communications &Amp; Networking Conference (CCNC)

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Current Software Defined Networking (SDN) techniques allow improving network control and flexibility. However its use in IoT is not trivial because IoT networks are unreliable and highly resource-constrained. Among some of the existing solutions proposed in the literature, Whisper enables SDN-like control over the packet forwarding and cell allocation of IoT devices by injecting in the network artificial, but still standard compliant messages that alter the default protocol behavior. Since Whisper uses carefully computed routing and scheduling messages that are compatible with the distributed protocols run in the network, it reduces the overhead in the network and operates without modifying the IoT devices' firmware. However, as other SDN-on-IoT technologies, Whisper is currently limited to the IoT network scope and remains as yet another independent network management silo. In this paper we propose a new higherlevel architecture that allows to fully integrate the IoT SDN network management into a network operating system, such as ONOS, by using Whisper in order to provide an integral endto-end softwarization. We also describe the interaction between the Whisper platform and the orchestrator and test our solution with real 6TiSCH-compatible hardware in the ONOS platform. Finally, we discuss the requirements and technical challenges to fully leverage Whisper to provide an efficient and programmable end-to-end control over an heterogeneous network domain.

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“…Fogbed [34] allows resource provisioning emulation in Fog environments. It combines Containernet [112] and Maxinet [154] (both are extensions of the Mininet [69] network emulator) to allow the use of virtual instances for resource provisioning emulation.…”

Section: Emulation Systemsmentioning

confidence: 99%

Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review

Rosendo

Costan

Valduriez

et al. 2022

Journal of Parallel and Distributed Computing

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Mininet-WiFi as Software-Defined Wireless Network Testing Platform

Cited by 22 publications

References 0 publications

Integrating Deep Learning-Based IoT and Fog Computing with Software-Defined Networking for Detecting Weapons in Video Surveillance Systems

Integrating Deep Learning-Based IoT and Fog Computing with Software-Defined Networking for Detecting Weapons in Video Surveillance Systems

Leveraging Distributed Protocols for full End-to-End Softwarization in IoT Networks

Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review

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