Adaptive Delta Causality Control With Prediction

2299 Words Oct 12th, 2014 10 Pages
Adaptive Delta-Causality Control with Prediction in Networked Real-Time Game Using Haptic Media

Haptic – “relating to the sense of touch, in particular relating to the perception and manipulation of objects using the senses of touch and proprioception.”

MU - “The game is based on a peer-to-peer (P2P) model. Each terminal refreshes a screen at 60 Hz and sends media units (MUs), each of which includes information about the position, velocity, and time-stamp, to the other terminal. We have two types of MUs: One has the position information of the mallet, and the other has that of the puck.”

Networked Air Hockey using Haptic media
Improve interactivity of the air hockey game through applying prediction logic to adaptive delta-causality control.
The value of ∆ is dynamically changed according to the network delay for MUs of the mallet, and is shared among terminals
Then, each terminal sends a changed value of ∆ to the other terminals. The terminal selects the largest value from among the changed values as a new value of ∆.
The adaptive delta causality control scheme with prediction outputs each Media Unit by predicting the future position later than the output time of the received MU by the prediction time Tpredict ( ≥ 0) ms to keep the interactivity high.
Measured through Quality of Experience assessment.
Conclusion
In this paper, we proposed the adaptive ∆-causality control scheme with prediction and investigated the effect of the proposed scheme by QoE assessment in a…
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