IoT Device Virtualization for Efficient Resource Utilization in Smart City IoT Platform

Ogawa, Kazuhiko; Kanai, Kazuaki; Nakamura, Kenichi; Kanemitsu, Hidehiro; Katto, Jiro; Nakazato, Hidenori

doi:10.1109/percomw.2019.8730806

Cited by 24 publications

(17 citation statements)

References 7 publications

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“…A smart city application is an application in which diverse IoT systems are interoperated. The FED4IoT project, which we join, aims to develop a similar smart-city application [12], [13]. A schematic of the FED4IoT project is shown in Figure 5.…”

Section: Summary Of the Smart City Applicationmentioning

confidence: 99%

Concept and Development of Next Phase Gateway Applied to Internet of Things

2021

Proceedings of 2021 the 11th International Workshop on Computer Science and Engineering

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Gateway was developed as a home adapter to be used in home security and controlling household appliances. However, its requirements changed with improvements in network technologies, and they can be divided into four phases. With increasing development of Internet of Things (IoT), internet services have become more diverse in recent years. Therefore, requirements of gateways, for their application to IoT, have also changed. The requirements of a phase 5 Gateway are open connectivity and capability to cooperate with multiple cloud services. In this study, a wildlife monitoring system, which is a use case in the FED4IoT project, was chosen in the development of the Phase 5 Gateway. A data model was created to make the gateway learn the type of data obtained at the gateway. Finally, a phase 5 Gateway to be applied to the wildlife monitoring system was developed.

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Section: Summary Of the Smart City Applicationmentioning

confidence: 99%

Concept and Development of Next Phase Gateway Applied to Internet of Things

2021

Proceedings of 2021 the 11th International Workshop on Computer Science and Engineering

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“…Fed4IoT is a research and innovation project that is jointly funded by the European Commission and Japan's Ministry of Internal Affairs and Communications. This project aims to develop a smart-city application by using novel IoT virtualization technologies [11], [12]. As shown in Figure 3, this project has 4 locations (Murucia in Spain, Grasse in France, Hakusan and Kumamoto in Japan) and IoT services are provided at each location.…”

Section: Summary Of the Fed4iot Projectmentioning

confidence: 99%

Wildlife Monitoring to Contribute Sustainable Development Goals - Concept, Requirement, and Implementation

Yoshida¹,

Yokotani²,

Ishibashi³

et al. 2020

IJCDS

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With the increasing use of the Internet of things (IoT), heterogeneous IoT services are being offered to satisfy various needs. The Fed4IoT project aims to develop an IoT virtualization technology that could realize the possibility of a smart-city application that federates heterogeneous IoT services. In this project, wildlife monitoring was chosen as an example of this application. Wildlife damage is not only a problem in agriculture but also a problem for people who live in rural areas as it disturbs their daily lives. It is a universal problem that has existed for a significant amount of time. In this case, an IoT platform with end devices that consist of a cage, camera, target counter, etc. is employed, and local offices and residents are informed about the approach of an animal, the condition of the cage, etc. through an information-centric network. The obtained data is subsequently used in other Fed4IoT services. In this study, the IoT platform and its application to wildlife monitoring are discussed after its implementation, which would help achieve the United Nations Sustainable Development Goals© (17 goals and 169 targets to eradicate poverty and realize a sustainable world).

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“…Hence, some researchers, e.g., Dolberg et al ( 2016 ), Meng et al ( 2017 ), Chen et al ( 2018 ), Lee et al ( 2018 ), Bevi et al ( 2019 ), Bistritz and Bambos ( 2019 ), Chang et al ( 2019 ), and Li et al ( 2019 ), focus on designing edge computing architecture to achieve a high level of scalability and fast response rate, comparing with the widely deployed centralized cloud-based(IoT) solutions. Some others, e.g., Kovatsch et al ( 2012 ), Morabito and Beijar ( 2016 ), Morabito et al ( 2016 , 2017 ), Morabito ( 2017 ), Rufino et al ( 2017 ), Cheng et al ( 2018 ), Dolui and Király ( 2018 ), Mendki ( 2018 ), and Ogawa et al ( 2019 ), also works on the virtualization of edge-side gateways to enhance the flexibility of above edge computing architecture. All these works either improve the communication and computation efficacy at infrastructure level or design an edge-cloud cooperation training mechanism in which training task runs on cloud side while detection and recognition tasks are executed on the edge.…”

Section: Introductionmentioning

confidence: 99%

Rinegan: A Scalable Image Processing Architecture for Large Scale Surveillance Applications

et al. 2021

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Image processing is widely used in intelligent robots, significantly improving the surveillance capabilities of smart buildings, industrial parks, and border ports. However, relying on the camera installed in a single robot is not enough since it only provides a narrow field of view as well as limited processing performance. Specially, a target person such as the suspect may appear anywhere and tracking the suspect in such a large-scale scene requires cooperation between fixed cameras and patrol robots. This induces a significant surge in demand for data, computing resources, as well as networking infrastructures. In this work, we develop a scalable architecture to optimize image processing efficacy and response rate for visual ability. In this architecture, the lightweight pre-process and object detection functions are deployed on the gateway-side to minimize the bandwidth consumption. Cloud-side servers receive solely the recognized data rather than entire image or video streams to identify specific suspect. Then the cloud-side sends the information to the robot, and the robot completes the corresponding tracking task. All these functions are implemented and orchestrated based on micro-service architecture to improve the flexibility. We implement a prototype system, called Rinegan, and evaluate it in an in-lab testing environment. The result shows that Rinegan is able to improve the effectiveness and efficacy of image processing.

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IoT Device Virtualization for Efficient Resource Utilization in Smart City IoT Platform

Cited by 24 publications

References 7 publications

Concept and Development of Next Phase Gateway Applied to Internet of Things

Concept and Development of Next Phase Gateway Applied to Internet of Things

Wildlife Monitoring to Contribute Sustainable Development Goals - Concept, Requirement, and Implementation

Rinegan: A Scalable Image Processing Architecture for Large Scale Surveillance Applications

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