VAP3 – Techniques for IoVs, Wearables and Industry

Thursday, 9 June 2022, 16:00-17:30, Room C240

Session Chair: Konstantin Mikhaylov (University of Oulu, FI)

SAC-Based Resource Allocation for Computation Offloading in IoV Networks

Bishmita Hazarika (National Sun Yat-Sen University, Taiwan); Keshav Singh (National Sun Yat-sen University, Kaohsiung, Taiwan); Sudip Biswas (Indian Institute of Information Technology, Guwahati, India); Shahid Mumtaz (Instituto de Telecomunicações, Portugal); Chih-Peng Li (National Sun Yat-sen University, Taiwan)
Due to the dynamic nature of a vehicular fog computing environment, efficient real-time resource allocation in an internet of vehicles (IoV) network without affecting the quality of service of any of the on-board vehicles can be challenging. This paper proposes a priority-sensitive task offloading and resource allocation scheme in an IoV network, where vehicles periodically exchange beacon messages to inquire about available services and other important information necessary for making the offloading decisions. In the proposed methodology, the vehicles are stimulated to share their idle computation resources with the task vehicles, whereby a deep reinforcement learning algorithm based on soft actor-critic (SAC) is designed to classify the tasks based on priority and computation size of each task for optimally allocating the power. In particular, the SAC algorithm works towards achieving the optimal policy for task offloading by maximizing the mean utility of the considered network. Extensive numerical results along with a comparison with other baseline algorithms, namely greedy and deep deterministic policy gradient algorithms are presented to validate the feasibility of the proposed algorithm.

Regional Multi-RAT Dual Connectivity Management for Reliable 5G V2X Communications

David Garcia-Roger (Universitat Politècnica de València, Spain); Edgar E. González (Universidad Tecnológica Israel, Ecuador); Jose F Monserrat (Universitat Politècnica de València, Spain)
Release 16 of the Third Generation Partnership Project (3GPP) standards contains the first set of Fifth Generation (5G) Vehicle-to-Anything (V2X) specifications based on the New Radio (NR) interface. The coexistence of NR and Long Term Evolution (LTE) V2X rollouts paves the way for communications involving multiple Radio Access Technologies (multi-RAT). From 5G-CARMEN project viewpoint, non-standalone multi-RAT Dual Connectivity (MR-DC) architectures enable support of cross-border Cooperative, Connected and Automated Mobility use cases with stringent requirements. However, the joint coordination of multi-RAT, cross-RAT, and sidelink interfaces is still a complex issue. This paper presents an MR-DC aware, regional multi-RAT management (MRM) entity, particularizing such approach for improving the reliability of 5G V2X through the use of redundant transmissions. A comparative study is carried out in MATLAB targeting a proof-of-concept scenario on the 5G-CARMEN project corridor. Simulation results show better Packet Reception Ratio (PRR) performance when the MRM entity is enabled.

Addressing Coverage Concerns for Direct-To-Cloud Wearables

Ewout Brandsma, Henk Huijgen, Paul Gruijters and Jesus Gonzalez Tejeria (Philips, The Netherlands)
Small wearable devices measuring vital-signs and connecting Direct-to-Cloud through the cellular network are a game changer for healthcare, enabling better outcomes for patients, better patient experience, better staff experience, and lower cost of care. These devices leverage mMTC technologies such as LTE-M and NB-IoT to provide hassle-free, out-of-the-box, and ubiquitous connectivity. However, a lack of cellular coverage may inhibit the uptake of this new class of devices. The current paper presents these coverage concerns – including field test results in hospitals – and then addresses two potential solutions: NB-IoT as an alternative RAT to LTE-M and signal repeaters as a cost-effective alternative to DAS and small cells.

Enabling URLLC in 5G NR IIoT Networks: A Full-Stack End-To-End Analysis

Giampaolo Cuozzo (Università di Bologna, Italy); Sara Cavallero (University of Bologna, Italy); Francesco Pase and Marco Giordani (University of Padova, Italy); Joseph Eichinger (Huawei Technologies Duesseldorf GmbH, European Research Center (ERC), Germany); Chiara Buratti and Roberto Verdone (University of Bologna, Italy); Michele Zorzi (University of Padova, Italy)
This paper addresses the problem of enabling inter-machine ultra-reliable low-latency communication (URLLC) in 5th generation (5G) NR Industrial Internet of Things (IIoT) networks. In particular, we consider a common Standalone Non-Public Network (SNPN) architecture proposed by the 5G Alliance for Connected Industries and Automation (5G-ACIA), and formalize a full-stack end-to-end (E2E) latency analysis where semi-persistent uplink scheduling is considered in detail and compared with a baseline grant-based approach. Through simulations, we demonstrate that semi-persistent scheduling outperforms the baseline scheme and provides an E2E latency below 1 ms, thereby representing a desirable solution to allocate resources for URLLC. Notably, we provide numerical guidelines for dimensioning 3GPP-compliant IIoT networks for both periodic and aperiodic traffic applications, and as a function of the number of machines in the factory and the offered traffic.

Enabling Cooperative Awareness for UAVs: ETSI CAM Protocol Extension

Sandaruwan Gayantha Jayaweera, Konstantin Mikhaylov and Matti Hämäläinen (University of Oulu, Finland)
The use cases involving single or multiple Unmanned Aerial Vehicles (UAVs) controlled by a pilot or operating autonomously are becoming more and more common these days. To support UAVs’ safe and efficient operation, the enablement of cooperative awareness (CA) is crucial. In this paper, we approach this challenge by proposing a modification of the Cooperative Awareness Message (CAM) protocol developed by the European Telecommunication Standards Institute (ETSI) for enabling CA for Intelligent Transportation Systems (ITSs) to support UAVs. Initially, we identify the information required to provide UAV CA. Then, we introduce a messaging architecture with data fields specifically designed to support 3D mobility. We follow the rules of the existing CAM specification so that this messaging structure can be added as an extension to the existing CAM structure. Finally, we present the performance of our messaging scheme using analytical models. The results show that the proposed messaging structure can be effectively used and provide some insights into the scalability of the proposed approach.

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