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DTSTAMP:20230124T171526Z
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DTSTART;TZID=America/Chicago:20221117T083000
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UID:submissions.supercomputing.org_SC22_sess226_spostu109@linklings.com
SUMMARY:Practical Evaluation of Remote Adaptive Lossy Compression with Fee
 dback
DESCRIPTION:ACM Student Research Competition: Graduate Poster, ACM Student
  Research Competition: Undergraduate Poster, Posters\n\nPractical Evaluati
 on of Remote Adaptive Lossy Compression with Feedback\n\nEnnis\n\nWhen tra
 nsmitting image data from a deployed edge device, a high-bandwidth connect
 ion to a cloud system cannot be guaranteed. An early-warning system for an
  intersection crosswalk, for instance, would have to be able to compress a
 nd transmit data with enough quality to ensure prompt detection of danger 
 through remote image processing. Adaptive lossy compression provides a pot
 ential solution for this, although it is yet to be evaluated on actual edg
 e hardware. By separating the compression and detection pipelines between 
 client and server processes, improving compression ratios by up to 4.95% v
 ia a unified lossless stage, demonstrating compression performance on an A
 rm-powered edge device, and benchmarking network performance under a range
  of realistic bandwidth conditions, we attempt to evaluate the viability o
 f this method under realistic conditions. This poster discusses our revise
 d architecture and its performance, along with the relevance of our result
 s towards method refinement.\n\nRegistration Category: Tech Program Reg Pa
 ss
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