Performance analysis of content discovery for ad-hoc tactile networks

Tactile Internet evolves communications to encompass sensory information such as smell and haptic sensations combining ultra-low latency with extremely high availability, reliability, and security. Tactile Internet is realized through underpinning technologies such as Multi-access Edge and Fog computing which facilitate decentralized infrastructures and machine to machine (M2M) communications. Mobile ad hoc networks (MANETs) form the foundation layer of such infrastructures, enabling direct communication between autonomous and decentralized devices such as sensors and vehicles. Among other applications, autonomous ad hoc vehicular networks (VANETs) and vehicle to vehicle (V2V) communications require efficient content discovery and quality of data transfer. The mobility patterns of vehicles within this communication model could effect the quality of data exchanged between devices in a tactile network. Several mobility models exist describing mobility patterns of mobile users in MANETs. In this paper, we present a first performance study to evaluate the impact of different mobility models on content discovery techniques for tactile Internet comprising of fast-moving vehicles and devices. This study combines direct and derived mobility metrics evaluating impact on content discovery and content dissemination using NS-3. Our simulation results indicate that unstructured techniques may not scale well within a tactile network of fast moving vehicles while maintaining low latency and could suffer from performance degradation in a saturated environment. Furthermore, simulation results also demonstrate the resilience of the unstructured content discovery protocol in mobility scenarios with proactive routing and diverse behavior.