Next Generation Internet of Things

Vermesan, Ovidiu; Bacquet, Joël

doi:10.13052/rp-9788770220071

Cited by 22 publications

(2 citation statements)

References 35 publications

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“…The IoRT is based on technologies derived from the IoT/IIoT paradigms that were developed during the last years. The IoT/IIoT technologies and applications are described in several published survey papers that cover different aspects of the IoT technologies and applications (Al-Fuqaha et al, 2015 ; Vermesan and Friess, 2015 , 2016 ; Vermesan and Bacquet, 2017 , 2018 ; Colaković and Hadzialic, 2018 ; Perrone et al, 2019 ; Sabry et al, 2019 ; Ud Din et al, 2019 ). The new enabling technologies for IoRT extend the existing IoT/IIoT and bring new requirements for the emerging IoT/IIoT technologies as emphasized in the next subsections.…”

Section: Enabling Technologiesmentioning

confidence: 99%

Internet of Robotic Things Intelligent Connectivity and Platforms

et al. 2020

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The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and "things" have evolved significantly. "Things" now range from simple Radio Frequency Identification (RFID) devices to smart wireless sensors, intelligent wireless sensors and actuators, robotic things, and autonomous vehicles operating in consumer, business, and industrial environments. The emergence of "intelligent things" (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration of applications across different business and industrial domains. These new applications accelerate the development of autonomous system design paradigms and the proliferation of the Internet of Robotic Things (IoRT). In IoRT, collaborative robotic things can communicate with other things, learn autonomously, interact safely with the environment, humans and other things, and gain qualities like self-maintenance, self-awareness, self-healing, and fail-operational behavior. IoRT applications can make use of the individual, collaborative, and collective intelligence of robotic things, as well as information from the infrastructure and operating context to plan, implement and accomplish tasks under different environmental conditions and uncertainties. The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms important components of new-generation IoRT applications. This paper reviews the taxonomy of the IoRT, emphasizing the IoRT intelligent connectivity, architectures, interoperability, and trustworthiness framework, and surveys the technologies that enable the application of the IoRT across different domains to perform missions more efficiently, productively, and completely. The aim is to provide a novel perspective on the IoRT that involves communication among robotic things and humans and highlights the convergence of several technologies and interactions between different taxonomies used in the literature.

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Section: Enabling Technologiesmentioning

confidence: 99%

Internet of Robotic Things Intelligent Connectivity and Platforms

et al. 2020

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“…The flow generated by these applications is sensitive to delays. However, compared to VoIP or video, they impose stricter restriction on the time of delivery, which is about 10 ms. For some applications (e.g., remote surgical operations), it is necessary to provide shorter delivery time to a maximum of 1 ms. A concept of a network interaction, involving a transfer of data with ultra-short delays, is called the Tactile IoT [54,55].…”

Section: Launching Nb-iot Controller For Management Of Iot Traffic With E2e Qos Over Lte-based 4g/5g Networkmentioning

confidence: 99%

End-to-End QoS “Smart Queue” Management Algorithms and Traffic Prioritization Mechanisms for Narrow-Band Internet of Things Services in 4G/5G Networks

Beshley

Kryvinska

Seliuchenko

et al. 2020

Sensors

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This paper proposes a modified architecture of the Long-Term Evolution (LTE) mobile network to provide services for the Internet of Things (IoT). This is achieved by allocating a narrow bandwidth and transferring the scheduling functions from the eNodeB base station to an NB-IoT controller. A method for allocating uplink and downlink resources of the LTE/NB-IoT hybrid technology is applied to ensure the Quality of Service (QoS) from end-to-end. This method considers scheduling traffic/resources on the NB-IoT controller, which allows eNodeB planning to remain unchanged. This paper also proposes a prioritization approach within the IoT traffic to provide End-to-End (E2E) QoS in the integrated LTE/NB-IoT network. Further, we develop “smart queue” management algorithms for the IoT traffic prioritization. To demonstrate the feasibility of our approach, we performed a number of experiments using simulations. We concluded that our proposed approach ensures high end-to-end QoS of the real-time traffic by reducing the average end-to-end transmission delay.

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