The Journal of Grid Computing explores an emerging technology that enables large-scale resource sharing problem solving within distributed, loosely coordinated groups sometimes termed "virtual organizations". Coverage includes protocols, security, scaling and more.
Although the advantages of this technology for classes of applications have been acknowledged, research in a variety of disciplines is needed to broaden the applicability and scope of the current body of knowledge. This journal fills the need, covering such topics as protocols, middleware, and services, security, discovery, sharing, scaling, and more.
Discussion extends to advanced technologies for collaborative work, information sharing and problem solving.
- Explores emerging technology that enables large-scale resource sharing problem solving within loosely coordinated groups sometimes termed "virtual organizations"
- Coverage includes protocols, security, scaling and more
- Discusses advanced technologies for collaborative work, information sharing and problem solving
- Peter Kacsuk,
- Tamas Kiss
- Publishing model
- Hybrid (Transformative Journal). Learn about publishing Open Access with us
- 3.986 (2020)
- Impact factor
- 3.642 (2020)
- Five year impact factor
- 82 days
- Submission to first decision
- 325 days
- Submission to acceptance
- 25,482 (2020)
This is part of 1 collection:
Authors (first, second and last of 6)This is part of 1 collection:
Authors (first, second and last of 4)This is part of 1 collection:
Authors (first, second and last of 7)
Deep learning and machine learning techniques are at the forefront of Artificial Intelligent (AI) in various fields. One of the important computing methods used to overcome the training difficulty in deep learning and machine learning techniques is Reservoir Computing (RC).
Guest Editors: Dr. Ahmed A. Abd El-Latif (Lead Guest Editor); Dr. Edmond Shu-lim Ho; Dr. Jialiang Peng
Submission Deadline: April 15th 2022
Download full details here: Reservoir Computing: Trends and Future Prospects
Call for Papers: Decision Support Systems and Intelligent Algorithms for Industrial IoT and Big Data (Submission Deadline November 30th 2021)
This topical collection aims to offer a systematic and most up-to-date overview, latest research trends, advanced research and mixed method approaches of this new research field. It aims to provide innovative Decision Support approaches, models, systems and algorithms to effectively support decision making in IIoT environments. It also includes platforms, applications and services for IIoT and Big Data, such as Industry 4.0, supply chain and smart manufacturing. The user and organizational adoption are also amongst our interests. It will provide a leading forum for disseminating the latest results of research, development, and applications in the area of Decision Support Systems and Algorithms (DSS) in IIoT and Big Data Environments. Advanced IIoT and its applications/services in Industry 4.0, integrated systems and smart algorithms are largely welcome. We select some top papers from IoTBDS 2021 http://iotbds.org/, COMPLEXIS 2021 http://www.complexis.org/ and IIoTBDSC 2021 http://iiotbdsc.com/, which require an extensive improvement prior submission. We also welcome a small number of high-quality paper submissions that are not presented at these conferences.
Guest Editors: Prof. Victor Chang (Lead Guest Editor), Prof. Víctor Méndez Muñoz, Prof. Reinhold Behringer
Submission Deadline: November 30th, 2021
Download full details here: Decision Support Systems and Intelligent Algorithms for Industrial IoT and Big Data
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