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Algorithms
Special Issues
Big Data Solutions
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Big Data Solutions

A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Databases and Data Structures".

Deadline for manuscript submissions: closed (30 September 2020) | Viewed by 5165

Special Issue Editor

Dr. Zbigniew Marszalek

E-Mail Website
Guest Editor
Institute of Mathematics, Silesian University of Technology, 44-100 Gliwice, Poland
Interests: computational complexity of algorithms—parallel programming; databases; artificial intelligence

Special Issue Information

Dear Colleagues,

Big data is an important topic in the modern world. Huge amounts of data need to be processed, searched, and analyzed very quickly. Unfortunately, this is not an easy task due to the time/computational complexity, hence it is important to model and refine various techniques to help and improve big data analysis.

This Special Issue is devoted to the analysis and presentation of new algorithms in the area of big data. Papers should contain both theoretical and experimental data in order to show newer solutions in this topic.

Dr. Zbigniew Marszalek
Guest Editor

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. Algorithms is an international peer-reviewed open access monthly 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 1600 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

  • big data analysis
  • big data solutions
  • machine learning in big data
  • big data in the internet of things
  • signal and data processing

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Published Papers (1 paper)

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Research

12 pages, 606 KiB  
Article
A New Way to Store Simple Text Files
by Marcin Lawnik, Artur Pełka and Adrian Kapczyński
Algorithms 2020, 13(4), 101; https://doi.org/10.3390/a13040101 - 22 Apr 2020
Cited by 4 | Viewed by 4767
Abstract
In the era of ubiquitous digitization, the Internet of Things (IoT), information plays a vital role. All types of data are collected, and some of this data are stored as text files. An important aspect—regardless of the type of data—is related to file [...] Read more.
In the era of ubiquitous digitization, the Internet of Things (IoT), information plays a vital role. All types of data are collected, and some of this data are stored as text files. An important aspect—regardless of the type of data—is related to file storage, especially the amount of disk space that is required. The less space is used on storing data sets, the lower is the cost of this service. Another important aspect of storing data warehouses in the form of files is the cost of data transmission needed for file transfer and its processing. Moreover, the data that are stored should be minimally protected against access and reading by other entities. The aspects mentioned above are particularly important for large data sets like Big Data. Considering the above criteria, i.e., minimizing storage space, data transfer, ensuring minimum security, the main goal of the article was to show the new way of storing text files. This article presents a method that converts data from text files like txt, json, html, py to images (image files) in png format. Taking into account such criteria as the output size of the file, the results obtained for the test files confirm that presented method enables to reduce the need for disk space, as well as to hide data in an image file. The described method can be used for texts saved in extended ASCII and UTF-8 coding. Full article
(This article belongs to the Special Issue Big Data Solutions)
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