Ocelot: An Interactive, Efficient Distributed Compression-As-a-Service Platform With Optimized Data Compression Techniques

Large volumes of data generated by scientific simulations, genome sequencing, and other applications need to be moved among clusters for data collection/analysis. Data compression techniques have effectively reduced data storage and transfer costs. However, users' requirements on interactively controlling both data quality and compression ratios are non-trivial to fulfill. We propose a novel Compression-as-a-Service (CaaS) platform called Ocelot with four important contributions: (1) It offers real-time visualization, interactive compression, and transfer of scientific datasets. (2) It incorporates new strategies for compressing diverse types of datasets more effectively than traditional methods. (3) It provides an effective method for estimating the compression ratio and execution time of compression tasks. (4) Experiments on multiple real-world datasets on geographically distributed computers show that Ocelot can significantly improve data transfer efficiency with a performance gain of more than 10x in computing clusters with relatively slow networks.

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Publication Details

Journal
IEEE Transactions on Parallel and Distributed Systems
Published
2025-05-20
DOI
https://doi.org/10.1109/tpds.2025.3568221
Citations
1
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
1.49
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article

Ocelot: An Interactive, Efficient Distributed Compression-As-a-Service Platform With Optimized Data Compression Techniques

Ian Foster, Kyle Chard, Sheng Di, Jiajun Huang et al.
1 citations
IEEE Transactions on Parallel and Distributed Systems
Distributed and Parallel Computing Systems
1.49
article

Ocelot: An Interactive, Efficient Distributed Compression-As-a-Service Platform With Optimized Data Compression Techniques

Ian Foster, Kyle Chard, Sheng Di, Jiajun Huang, Yuanjian Liu, Zhaorui Zhang
article en
1 citations

Abstract

Large volumes of data generated by scientific simulations, genome sequencing, and other applications need to be moved among clusters for data collection/analysis. Data compression techniques have effectively reduced data storage and transfer costs. However, users' requirements on interactively controlling both data quality and compression ratios are non-trivial to fulfill. We propose a novel Compression-as-a-Service (CaaS) platform called Ocelot with four important contributions: (1) It offers real-time visualization, interactive compression, and transfer of scientific datasets. (2) It incorporates new strategies for compressing diverse types of datasets more effectively than traditional methods. (3) It provides an effective method for estimating the compression ratio and execution time of compression tasks. (4) Experiments on multiple real-world datasets on geographically distributed computers show that Ocelot can significantly improve data transfer efficiency with a performance gain of more than 10x in computing clusters with relatively slow networks.

IEEE Transactions on Parallel and Distributed SystemsVol. 36(12)
University of California, Riverside (US), Argonne National Laboratory (US), Hong Kong Polytechnic University (HK), University of Chicago (US)
Affordable and clean energy
Openalex Percentile: Top 17%
Distributed and Parallel Computing Systems
1.49
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Ocelot: An Interactive, Efficient Distributed Compression-As-a-Service Platform With Optimized Data Compression Techniques — Ian Foster, Kyle Chard, et al. · IEEE Transactions on Parallel and Distributed Systems (2025) | TGRS Research Map | TGRS