Network-Aware Adaptive Sampling for Low Bitrate Telehaptic Communication

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F18%3A43898679" target="_blank" >RIV/60076658:12310/18:43898679 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-319-93399-3_56" target="_blank" >http://dx.doi.org/10.1007/978-3-319-93399-3_56</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-93399-3_56" target="_blank" >10.1007/978-3-319-93399-3_56</a>

Result language

angličtina

Original language name

Network-Aware Adaptive Sampling for Low Bitrate Telehaptic Communication

Original language description

While the adaptive sampling technique for kinesthetic signal transmission offers a phenomenal reduction in the time-average data rate, it does not guarantee a meaningful upper bound on the instantaneous rate, which can occasionally be comparable to the peak rate. This implies that for Quality of Service (QoS) compliance, a network bandwidth equal to the peak rate must be reserved apriori for the telehaptic stream at all times. On a shared network with unknown and time-varying cross-traffic, this is not always feasible. In order to address the intermittently high bandwidth demand as well as the network-obliviousness of adaptive sampling, we propose NaPAS: Network-aware Packetization for Adaptive Sampling. The idea is to intelligently merge multiple haptic samples generated by adaptive sampling in a packet, depending on the changing network conditions. This results in an elastic telehaptic traffic that can adapt to the available network bandwidth. Through qualitative and quantitative measures, we evaluate the performance of NaPAS and demonstrate that it outperforms standard adaptive sampling (SAS) in terms of maintaining the haptic perceptual quality and QoS compliance, while also being friendlier to the exogenous network cross-traffic.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISBN

978-3-319-93398-6

ISSN

—

e-ISSN

1611-3349

Number of pages

13

Pages from-to

660-672

Publisher name

Springer Verlag

Place of publication

Pisa, Italy

Event location

Pisa; Italy

Event date

Jun 13, 2018

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

000458561800056