Fine-Grained Traffic Differentiation in Tactile Internet Scenarios Using RINA

Abstract

The tactile Internet (TI) has emerged as an advanced communication technology that enables interaction between humans and machines. However, TI use cases demand low latency, high reliability, and high-capacity requirements to achieve high quality of experience (QoE) in their applications. IoT networks provide transmission services to heterogeneous applications, and the inclusion of high-demand Quality of Service (QoS) requirements by TI applications will increase the difficulty of guaranteeing end-to-end QoS. We proposed a fine-grained traffic differentiation in tactile Internet scenarios using the Recursive Inter-Networking Architecture (RINA) QoS cubes and the Quantitative Timeliness Agreement Multiplexor (QTA-Mux) flow prioritization scheme. We designed four RINA QoS cubes to meet the delay and packet loss requirements of TI, Augmented Reality/Virtual Reality (AR/VR), and IoT applications and to provide fine-grained traffic differentiation. Also, we designed the QTA-Mux policy to enable a trade-off between delay and packet loss and adequately scheduling the service data unit (SDU) for delivering. We implemented a RINA network to test the proposed schemes in IoT environments and conducted several experiments to evaluate the delay and packet loss. The results showed that RINA-based prioritization and traffic differentiation proposed guaranteed end-to-end QoS to support TI applications. Thus, the next generation of IoT networks can use RINA to guarantee the QoS requirements of TI applications.