Special Issue "Cloud Computing for Big Data Analysis"
Deadline for manuscript submissions: 15 October 2020.
Interests: distributed systems; data mining; cloud computing; social media and Big Data analysis; peer-to-peer networks
Interests: cloud computing; social media and Big Data analysis; distributed knowledge discovery; data mining
It is our pleasure to announce the opening of a new Special Issue in Applied Science. The main topic for the Issue is cloud computing for big data analysis.
In the era of the Internet of Things, huge amounts of digital data are generated and collected by several sources, such as sensors, mobile devices, and social media. This huge amount of data, commonly referred as big data, represents a challenge for the current storage, process, and analysis capabilities.
Novel technologies, architectures, and algorithms have been and are being developed to capture and analyze big data. For example, in the scientific and business fields, researchers and data scientists are analyzing big data to extract information and knowledge useful for making new discoveries and supporting decision processes.
In this context, cloud computing is a valid and cost-effective solution for supporting big data storage and executing data analytic applications. Due to elastic resource allocation and high computing power, cloud computing represents a compelling solution for big data analytics, allowing faster data analysis, resulting in more timely results and then greater data value.
From this perspective, this Special Issue aims to contribute to the field, presenting the most relevant advances in this research area.
The following are some of the topics proposed for this Special Issue (but not limited to):
- Programming models and algorithms for distributed computing environments;
- Systems for data processing on cloud platforms;
- Data analysis workflows for distributed environments;
- Scalable data mining algorithms;
- Programming models and scalable algorithms for big data;
- Big data analytics and applications;
- Applications of machine learning in big data;
- Cloud-based data mining applications; and
- Libraries, algorithms, and applications for big social data analysis.
We hope you will contribute your high quality research and we look forward to reading your results.
Dr. Fabrizio Marozzo
Dr. Loris Belcastro
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 papers will be 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. Applied Sciences 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 1800 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.
- Cloud computing
- Big data
- Scalable data mining
- Data analysis workflows
- Social media analysis
- Parallel and distributed algorithms
- High performance computing
- Machine learning applications