The next frontier in communications isteleoperation– manipulation and control of remote environments with haptic feedback. Compared to conventional networked applications, teleoperation poses widely different requirements, ultra-low latency (ULL) is primary. Realizing ULL communication demands significant redesign of conventional networking techniques, and the network infrastructure envisioned for achieving this is termed asTactile Internet(TI). The design of meaningful performance metrics is crucial for seamless TI communication. However, existing performance metrics fall severely short of comprehensively characterizing TI performance due to their inability to capture how well sensed signals are reproduced. We take Dynamic Time Warping(DTW) as the basis of our work and identify necessary changes for characterizing TI performance. Through substantial refinements to DTW, we designEffective Time- and Value-Offset (ETVO)– a new method for measuring the fine-grained performance of TI systems. Through an in-depth objective analysis, we demonstrate the improvements of ETVO over DTW. Through subjective experiments, we demonstrate that existing QoS and QoE methods fall short of estimating the TI session performance accurately. Using subjective experiments, we demonstrate the behavior of the proposed metrics, their ability to match theoretically derived performance, and finally, their ability to reflect user satisfaction in a practical setting.

The next frontier in communications is teleoperation – manipulation and control of remote environments. Compared to conventional networked applications, teleoperation poses widely different requirements, ultra-low latency (ULL) being the primary one. Teleoperation, along with a host of other applications requiring ULL communication, is termed as Tactile Internet (TI). A significant redesign of conventional networking techniques is necessary to realize TI applications. Further, these advancements can be evaluated only when meaningful performance metrics are available. However, existing TI performance metrics fall severely short of comprehensively characterizing TI performance. In this paper, we take the first step towards bridging this gap. To this end, we propose a method that captures the fine-grained performance of TI in terms of delay and precision. We take Dynamic Time Warping (DTW) as the basis of our work and identify whether it is sufficient in characterizing TI systems. We refine DTW by developing a framework called Effective Time- and Value-Offset (ETVO) that extracts fine-grained time and value offsets between input and output signals of TI. Using ETVO, we present two quantitative metrics for TI – Effective Delay-Derivative (EDD) and Effective Root Mean Square Error. Through rigorous experiments conducted on a realistic TI setup, we demonstrate the potential of the proposed metrics to precisely characterize TI interactions.