Classical and quantum compression for edge computing: the ubiquitous data dimensionality reduction

Maryam Bagherian; Sarah Chehade; Ben Whitney; Ali Passian

doi:10.1007/s00607-023-01154-0

Classical and quantum compression for edge computing: the ubiquitous data dimensionality reduction

Maryam Bagherian, Sarah Chehade, Ben Whitney, Ali Passian

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Edge computing aims to address the challenges associated with communicating and transferring large amounts of data generated remotely to a data center in a timely and efficient manner. A central pillar of edge computing is local (i.e., at- or near-source) data processing capability so that data transfer to a data center for processing can be minimized. Data compression at the edge is therefore a natural component of edge workflows. We present a survey of data compression algorithms with a focus on edge computing. Not all compression algorithms can accommodate the data type heterogeneity, tight processing and communication time constraints, or energy efficiency requirement characteristics of edge computing. We discuss specific examples of compression algorithms that are being explored in the context of edge computing. We end our review with a brief survey of emerging quantum compression techniques that are of importance in quantum information processing, including the proposed concept of quantum edge computing.

Original language	English
Pages (from-to)	1419-1465
Number of pages	47
Journal	Computing
Volume	105
Issue number	7
DOIs	https://doi.org/10.1007/s00607-023-01154-0
State	Published - Jul 2023

Funding

The authors are indebted to Dr. Richard Archibald of the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) for reviewing the manuscript. This work was in part supported by the United States Department of Defense (DoD) and used resources of the Computational Research and Development Programs at ORNL. ORNL is managed by UT-Battelle, LLC, for the US DOE under contract DE-AC05-00OR22725. S.C. acknowledges DOE ASCR funding under the Quantum Computing Application Teams program, FWP No. ERKJ347.

Funders	Funder number
U.S. Department of Defense
U.S. Department of Energy	DE-AC05-00OR22725
Advanced Scientific Computing Research	ERKJ347
Oak Ridge National Laboratory

Keywords

Classical compression
Dimensionality reduction
Edge computing
Quantum compression

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10.1007/s00607-023-01154-0

Cite this

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Classical and quantum compression for edge computing: the ubiquitous data dimensionality reduction

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Keywords

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