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Computing

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

  • 22-01-2023
  • Regular Paper
Published in:
Authors
Maryam Bagherian
Sarah Chehade
Ben Whitney
Ali Passian
Published in
Computing | Issue 7/2023

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Abstract

The article delves into the pressing need for efficient data compression in edge computing, driven by the exponential growth of data volumes. It discusses the unique characteristics of edge data, such as heterogeneity, processing time sensitivities, and resource constraints, and explores various compression algorithms tailored for these environments. The paper reviews both classical and quantum compression techniques, highlighting their suitability for edge applications. It also discusses the emerging field of quantum edge computing, which promises to revolutionize data processing at the edge. The article provides a detailed overview of compression strategies, their implementation challenges, and future directions, making it a valuable resource for professionals in the field.
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Title
Classical and quantum compression for edge computing: the ubiquitous data dimensionality reduction
Authors
Maryam Bagherian
Sarah Chehade
Ben Whitney
Ali Passian
Publication date
22-01-2023
Publisher
Springer Vienna
Published in
Computing / Issue 7/2023
Print ISSN: 0010-485X
Electronic ISSN: 1436-5057
DOI
https://doi.org/10.1007/s00607-023-01154-0
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