End-to-End SDN/NFV Orchestration of Video Analytics Using Edge and Cloud Computing over Programmable Optical Networks

Vilalta, Ricard; Popescu, Iulian; Mayoral, Arturo; Cao, Xiaoyuan; Casellas, Ramon; Yoshikane, Noboru; Tsuritani, Takehiro; Morita, Itsuro; Muñoz, Raül

doi:10.1364/ofc.2017.w3i.1

Cited by 10 publications

(11 citation statements)

References 3 publications

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“…The IoTAP is responsible for selecting what IoT analytics services will be distributed to the edge, based on the characteristics of the IoT applications. We have developed an IoT application in [6] which is responsible for processing in the edge DC the camera image fed by detecting movement (using Gaussian blur filters, differential image and contour detection), and requesting connectivity towards the core DC and storing the suspicious videos.…”

Section: Iot-aware Cloud and Network Orchestration Architecturementioning

confidence: 99%

Orchestration of Optical Networks and Cloud/Edge Computing for IoT Services

Muñoz

Vilalta

Casellas

et al. 2019

2019 24th OptoElectronics and Communications Conference (OECC) and 2019 International Conference on Photonics in Switching and

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We present an IoT-aware cloud and network orchestration architecture for multi-domain transport SDN networks and cloud/edge computing that deploys an IoT-traffic control and congestion avoidance mechanism for dynamic distribution of IoT analytics to the edge. Keywords: Fog/edge computing infrastructure and applications, Internet of Things aware systems and applications, Software defined networking (SDN) for computing and big data control.

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Section: Iot-aware Cloud and Network Orchestration Architecturementioning

confidence: 99%

Orchestration of Optical Networks and Cloud/Edge Computing for IoT Services

Muñoz

Vilalta

Casellas

et al. 2019

2019 24th OptoElectronics and Communications Conference (OECC) and 2019 International Conference on Photonics in Switching and

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“…The authors have previously proposed in [16] the usage of a service orchestrator for IoT applications. Under this context, the SDN orchestrator must carry out the following three key functions: i) facilitate the transport of the huge amount of data generated at the terminals, sensors, machines, nodes, etc., to any distributed computing node, edge, or core data center; ii) allocate computing and storage resources in distributed fog nodes and data centers; and iii) process the collected data to make proper decisions, leading to the concept of cognition.…”

Section: Fog Computing and The Connected Carmentioning

confidence: 99%

Fifth-Generation Technologies for the Connected Car: Capable Systems for Vehicle-to-Anything Communications

Fallgren

Dillinger

Alonso-Zarat

et al. 2018

IEEE Veh. Technol. Mag.

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Abstract-This paper discusses the role of 5G technologies for the connected car. 5G technologies will enable cars and vehicles to be connected to the networks and also to be able to talk to each other ensuring ultra high reliability and very low latency. Enabling such kind of connectivity will leverage disruptive new applications that will allow to improve driving efficiency and boost road safety. First preliminary results from the EC-funded 5GPPP 5GCAR project are presented with regard to certain technologies that will enable the connected car, including channel measurement and modeling, advanced V2X communications, and fog computing. Also, a business perspective is provided, where the transformation of the automotive sector due to 5G is discussed.

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“…These three techniques (fog computing, SDN, NFV) are intertwined: in future communication networks, services will be deployed over a cloud computing infrastructure, where the necessary connectivity is provided by an SDN controller. The authors have previously proposed in [6], the usage of a service orchestrator for IoT applications.…”

Section: Introductionmentioning

confidence: 99%

Control and Management of a Connected Car Using SDN/NFV, Fog Computing and YANG data models

Vilalta

Via

Mira

et al. 2018

2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft)

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There are several use cases that claim the need for a connected car. Among them there is the need for connectivity between vehicles and information sources, or V2V and V2X exchanges for accident prevention. In order to cope with the need for novel applications running on top of an interconnected network, the concept of fog computing appears as a realistic solution for both intra-car and inter-car data processing and decision making. This paper describes the proposed architecture and experimental evaluation of an innovative proof-of-concept (PoC) for a connected car, modeled with YANG, which can be remotely controlled using SDN/NFV and fog computing technologies. As an example, the remote control of the car might be based on a service application running on a fog node, which can be located close to a road side unit (RSU). We also propose a fog architecture in order to enable cooperative perception between connected cars. Finally, the performance evaluation uses a RESTCONF server installed in a Raspberry Pi aboard of a small car. This server is responsible for the sensors and actuators of the car and allows for its remote control from a user terminal (e.g., a smartphone, tablet, or laptop) and through the fog node, running a control application as a service.

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End-to-End SDN/NFV Orchestration of Video Analytics Using Edge and Cloud Computing over Programmable Optical Networks

Abstract: This paper proposes the introduction of SDN-enabled containers to support the deployment of SDN/NFV applications located at the network edge, which are able to trigger ondemand connectivity services. A video analytics use case is demonstrated.

Cited by 10 publications

References 3 publications

Orchestration of Optical Networks and Cloud/Edge Computing for IoT Services

Orchestration of Optical Networks and Cloud/Edge Computing for IoT Services

Fifth-Generation Technologies for the Connected Car: Capable Systems for Vehicle-to-Anything Communications

Control and Management of a Connected Car Using SDN/NFV, Fog Computing and YANG data models

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