Advances in Lossy Data Compression Techniques
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 September 2024 | Viewed by 1005
Special Issue Editors
Interests: high-performance computing; data compression; scientific data management and visualization; large-scale machine learning; I/O systems
Interests: high-performance computing; parallel and distributed systems; scientific data management; large-scale data analytics; distributed machine learning
Special Issue Information
Dear Colleagues,
Today's modern applications generate large volumes of data, making data reduction a crucial technique in various domains. Lossy compression offers the capability to significantly reduce data size, saving memory and storage space, alleviating I/O burden, reducing communication time, and improving energy efficiency in parallel and distributed environments such as high-performance computing (HPC), cloud computing, edge computing, and the Internet of Things (IoT). For example, in HPC systems, where computational capabilities are extensive, scientific applications can generate vast amounts of data for post-analysis, posing challenges due to limited storage space and bottlenecks in runtime memory and communication.
Addressing the challenges in lossy compression requires expertise from computer science, mathematics, and application domains. It involves studying the problem holistically, developing solutions, and creating robust software tools for production applications. The community needs to understand the intricate relationship between application design, data analysis and reduction methods, programming models, system software, hardware, and other elements of large-scale computing infrastructure. Considerations of applicability, fidelity, performance portability, and energy efficiency are essential. The continuous exploration and development of new lossy compression techniques are also necessary to meet the needs of emerging applications and diverse use cases.
Within this context, there are three significant research topics that the community is addressing: (1) the possibility of achieving several orders of magnitude of lossy compression for extreme-scale sciences, (2) understanding the trade-off between performance and accuracy in lossy compression, and (3) developing effective solutions for reducing data size while preserving the information within large datasets.
The goal of this Special Issue is to provide a dedicated platform for researchers from all related communities to present their research findings, exchange ideas, identify new research directions, and foster collaborations within the lossy compression community.
Dr. Dingwen Tao
Dr. Xin Liang
Dr. Kai Zhao
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- lossy compression
- big data
- data reduction
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue polices can be found here.
