Title

A Predictive Framework for Haptic Enabled VR-based Remote Phobia Treatment in Cloud/Fog Environment

Document Type

Conference Proceeding

Source of Publication

2021 24th Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)

Publication Date

1-1-2021

Abstract

The emerging Tactile Internet aims to transmit the modality of touch in addition to the conventional audiovisual signals, thus converting the content delivery networks into skill-set delivery networks. An interesting example of immersive, low-latency Tactile Internet applications is haptic-enabled virtual reality (VR), where an extremely low latency of less than 50 ms is required. In this paper, we consider a recently proposed fog-based haptic-enabled VR system for remote treatment of animal phobia. Specifically, we address the problem of excessive packet latency as well as packet loss, which may result in quality-of-experience (QoE) degradation. Toward this end, we aim to use machine learning to decouple the impact of excessive latency and extreme packet loss from the user experience by utilizing our proposed edge tactile learner (ETL), which is responsible for predicting the zones touched by the therapist and then delivering it to the patient fog domain immediately, if needed. The simulation results indicate that our proposed predictive method outperforms two benchmark algorithms in terms of accuracy and prediction time.

ISSN

2472-8144

Publisher

IEEE

First Page

20

Last Page

27

Disciplines

Computer Sciences

Keywords

Tactile Internet, Cloud computing, Machine learning algorithms, Simulation, Packet loss, Virtual reality, Prediction algorithms

Scopus ID

85104190190

Indexed in Scopus

yes

Open Access

no

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