2,087 research outputs found
Congestion Control for Network-Aware Telehaptic Communication
Telehaptic applications involve delay-sensitive multimedia communication
between remote locations with distinct Quality of Service (QoS) requirements
for different media components. These QoS constraints pose a variety of
challenges, especially when the communication occurs over a shared network,
with unknown and time-varying cross-traffic. In this work, we propose a
transport layer congestion control protocol for telehaptic applications
operating over shared networks, termed as dynamic packetization module (DPM).
DPM is a lossless, network-aware protocol which tunes the telehaptic
packetization rate based on the level of congestion in the network. To monitor
the network congestion, we devise a novel network feedback module, which
communicates the end-to-end delays encountered by the telehaptic packets to the
respective transmitters with negligible overhead. Via extensive simulations, we
show that DPM meets the QoS requirements of telehaptic applications over a wide
range of network cross-traffic conditions. We also report qualitative results
of a real-time telepottery experiment with several human subjects, which reveal
that DPM preserves the quality of telehaptic activity even under heavily
congested network scenarios. Finally, we compare the performance of DPM with
several previously proposed telehaptic communication protocols and demonstrate
that DPM outperforms these protocols.Comment: 25 pages, 19 figure
3D oceanographic data compression using 3D-ODETLAP
This paper describes a 3D environmental data compression technique for oceanographic datasets. With proper point selection, our method approximates uncompressed marine data using an over-determined system of linear equations based on, but essentially different from, the Laplacian partial differential equation. Then this approximation is refined via an error metric. These two steps work alternatively until a predefined satisfying approximation is found. Using several different datasets and metrics, we demonstrate that our method has an excellent compression ratio. To further evaluate our method, we compare it with 3D-SPIHT. 3D-ODETLAP averages 20% better compression than 3D-SPIHT on our eight test datasets, from World Ocean Atlas 2005. Our method provides up to approximately six times better compression on datasets with relatively small variance. Meanwhile, with the same approximate mean error, we demonstrate a significantly smaller maximum error compared to 3D-SPIHT and provide a feature to keep the maximum error under a user-defined limit
Mulsemedia Communication Research Challenges for Metaverse in 6G Wireless Systems
Although humans have five basic senses, sight, hearing, touch, smell, and
taste, most multimedia systems in current systems only capture two of them,
namely, sight and hearing. With the development of the metaverse and related
technologies, there is a growing need for a more immersive media format that
leverages all human senses. Multisensory media(Mulsemedia) that can stimulate
multiple senses will play a critical role in the near future. This paper
provides an overview of the history, background, use cases, existing research,
devices, and standards of mulsemedia. Emerging mulsemedia technologies such as
Extended Reality (XR) and Holographic-Type Communication (HTC) are introduced.
Additionally, the challenges in mulsemedia research from the perspective of
wireless communication and networking are discussed. The potential of 6G
wireless systems to address these challenges is highlighted, and several
research directions that can advance mulsemedia communications are identified
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