Abstract
Data stored in the cloud can be simultaneously served to large swarms of nodes that stream bandwidth-intensive content. A direct transfer-and-store paradigm, as practiced today, can be inefficient in terms of bandwidth and memory. This disclosure describes techniques that leverage location proximity cues to selectively compress data that is transmitted over networks. Two nodes of a network processing similar video or audio divide and merge the compression stack such that reconstruction is performed with lower storage and bandwidth requirements, and at little to no loss of fidelity. For example, co-located cameras with partially overlapping fields-of-view encode their data to leverage the multi-view information in the overlapping section to achieve high-fidelity reconstruction with high compression. Bidirectional communication between nodes and a remote server is utilized to transmit location, pose, and other information that can be used to detect proximate nodes and enable cross-node compression.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Shin, D, "Using Location Cues for Efficient Data Compression and Transmission to Remote Server", Technical Disclosure Commons, (March 08, 2023)
https://www.tdcommons.org/dpubs_series/5726