The Internet of Things has now become an integral part of the most competitive industries, as it enables optimization of production processes, reduction of operating costs and maintenance time, and improvement of the quality of products and services. More specifically the term Industrial Internet of Things (IIoT) identifies the system which consists of advanced Internet-connected equipment and analytics platforms that process the products in industrial activities. IIoT devices range from small environmental sensors to complex industrial robots. Fifth generation (5G) cellular networks represent an enabling technology for the full development of the IIoT, as they realize the infrastructure on which clusters of smart devices rely to interconnect and manage the exchange of data with the various control processes and databases containing the information necessary for their proper operation. This paper presents the design of a high-level network architecture for managing information flows generated by multiple clusters of sensors and actuators: the proposed architecture is based on a Network Slicing approach and applied to an Industry 4.0 context where wireless subnetworks are interconnected via 5G access points and data routing is managed by an SDN Controller. The proposed system is emulated by means of two distinct real time frameworks, one for 5G network and the other for SDN network simulation. The obtained results demonstrate that the proposed approach that is coherent with 5G characteristics, allows to distribute the available resources more efficiently and afford improved performance in terms of connectivity, energy efficiency, end-to-end latency and throughput. In addition its scalability, modularity and flexibility are assessed, making it a general tool to test novel applications and more complex scenarios.
5G RAN and MEC Slices Management Framework for Networks of Industrial Things / Chiti Francesco; Morosi Simone; Bartoli Claudio.. - ELETTRONICO. - (2024), pp. 316-321. (Intervento presentato al convegno 7th IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd4.0 and IoT 2024 tenutosi a ita nel 2024) [10.1109/MetroInd4.0IoT61288.2024.10584162].
5G RAN and MEC Slices Management Framework for Networks of Industrial Things
Chiti F.
Conceptualization
;Morosi S.Conceptualization
;
2024
Abstract
The Internet of Things has now become an integral part of the most competitive industries, as it enables optimization of production processes, reduction of operating costs and maintenance time, and improvement of the quality of products and services. More specifically the term Industrial Internet of Things (IIoT) identifies the system which consists of advanced Internet-connected equipment and analytics platforms that process the products in industrial activities. IIoT devices range from small environmental sensors to complex industrial robots. Fifth generation (5G) cellular networks represent an enabling technology for the full development of the IIoT, as they realize the infrastructure on which clusters of smart devices rely to interconnect and manage the exchange of data with the various control processes and databases containing the information necessary for their proper operation. This paper presents the design of a high-level network architecture for managing information flows generated by multiple clusters of sensors and actuators: the proposed architecture is based on a Network Slicing approach and applied to an Industry 4.0 context where wireless subnetworks are interconnected via 5G access points and data routing is managed by an SDN Controller. The proposed system is emulated by means of two distinct real time frameworks, one for 5G network and the other for SDN network simulation. The obtained results demonstrate that the proposed approach that is coherent with 5G characteristics, allows to distribute the available resources more efficiently and afford improved performance in terms of connectivity, energy efficiency, end-to-end latency and throughput. In addition its scalability, modularity and flexibility are assessed, making it a general tool to test novel applications and more complex scenarios.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.