Browsing by Author "Song, Jaeseung"
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- EiF: Toward an Elastic IoT Fog Framework for AI Services
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2019-05-01) An, Jonggwan; Li, Wenbin; Gall, Franck Le; Kovac, Ernoe; Kim, Jaeho; Taleb, Tarik; Song, JaeseungThe first generation of IoT was developed and deployed all over the world by connecting devices with common functionalities that were not sufficiently efficient or reliable for use in dynamic situations that require adaptive solutions. However, these fundamental IoT functions and services mainly targeted stable environments; there is consequently a strong need for the next generation of IoT services to be smarter, faster, and more reliable. We believe that the hyper-connected IoT ecosystem on fog platforms with contextual AI technologies is a promising solution. In this work, we introduce the EiF, a flexible fog computing framework that runs on IoT gateways with adaptive AI services fostered on the cloud. Our approach can be viewed as an integration of three emerging technologies, namely IoT, fog, and AI. Generally, EiF virtualizes an IoT service layer platform for fog nodes, and provides functions to manage and orchestrate various fog nodes; upon service virtualization and orchestration, AI services are fostered within both the federated cloud and distributed edge side and are deployed on fog nodes. We demonstrate the feasibility of EiF via the example of intelligent traffic flow monitoring and management. - Roads Infrastructure Digital Twin: A Step Toward Smarter Cities Realization
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2021-03) Marai, Oussama El; Taleb, Tarik; Song, JaeseungDigital Twin is a new concept that consists of creating an up-to-date virtual asset in cyberspace which mimics the original physical asset in most of its aspects, ultimately to monitor, analyze, test, and optimize the physical asset. In this article, we investigate and discuss the use of the digital twin concept of the roads as a step toward realizing the dream of smart cities. To this end, we propose the deployment of a Digital Twin Box to the roads that is composed of a 360° camera and a set of IoT devices connected to a Single Onboard Computer. The Digital Twin Box creates a digital twin of the physical road asset by constantly sending real-time data to the edge/cloud, including the 360° live stream, GPS location, and measurements of the temperature and humidity. This data will be used for realtime monitoring and other purposes by displaying the live stream via head-mounted devices or using a 360° web-based player. Additionally, we perform an object detection process to extract all possible objects from the captured stream. For some specific objects (person and vehicle), an identification module and a tracking module are employed to identify the corresponding objects and keep track of all video frames where these objects appeared. The outcome of the latter step would be of utmost importance to many other services and domains such as national security. To show the viability of the proposed solution, we have implemented and conducted real-world experiments where we focus more on the detection and recognition processes. The achieved results show the effectiveness of the proposed solution in creating a digital twin of the roads, a step forward to enable self-driving vehicles as a crucial component of smart mobility, using the Digital Twin Box. - A Software-Defined Queuing Framework for QoS Provisioning in 5G and beyond Mobile Systems
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2021-03) Abbou, Aiman Nait; Taleb, Tarik; Song, JaeseungThere is an ever-increasing demand for network technologies supporting Ultra-Reliable Low Latency Communications (URLLC) services and their co-existence with best-effort traffic. By way of example, reference can be made to the emerging 5G mobile networks. In this vein, this article investigates the Software-Defined Networking (SDN) technology capabilities for providing Quality of Service (QoS) guarantees. Specifically, we present a testbed, under development, dubbed Soft-ware-Defined Queueing (SDQ). This framework leverages QoS provision functionalities of SDN. SDQ can be regarded as a framework for testing traffic engineering solutions in networks with deterministic QoS support. By using SDQ, we develop and test a specific solution that chooses the optimal queue and path for each incoming flow in order to reduce the workload imbalances in the network. For the experimental setup, we consider a generic SDN network whose bridges include three priority queues at every output port. Furthermore, we compare the aforementioned solution with a best-effort network and an SDN-enabled network with QoS support configured by default. The obtained results show that the envisioned solution outperforms the baseline one of SDN and the best-effort solution in terms of the average latency recorded.