MDTW Metric: A Signal Matching Yardstick for Accurately Evaluating the Quality of Tactile Internet

Abstract

Tactile Internet (TI) aims to construct a novel skill delivery network that delivers human operating experience to robots. The quality of different TI applications can be measured and compared, only when highly accurate TI metric schemes are established. However, existing TI metric schemes utilize only the signal deviation but ignore the signal range constrained by kinematic characteristics of hardware devices, which results in unrealistic signal matching. To this end, this paper set a signal matching yardstick by proposing a modified dynamic time warping (MDTW) metric algorithm. Particularly, typical kinematic characteristics such as time-varying joint angular trajectory and displacement range are first explored. Further, not only for one-dimensional joint data, but also for multi-dimensional position data, the corresponding signal matching constraints are established by utilizing the system state criterions, which specify the feasible signal range. To verify the accuracy and practicality of the proposed MDTW metric, extensive simulations are conducted and a TI-enabled telemedicine testbed is implemented. Both simulation and experimental results verify that the proposed MDTW metric effectively improves the accuracy of signal matching in various scenarios.