Journal of Grid Computing

Aims & Scope

Grid computing is an emerging technology that enables large-scale resource sharing and coordinated problem solving within distributed, often loosely coordinated groups-what are sometimes termed "virtual organizations.

By providing scalable, secure, high-performance mechanisms for discovering and negotiating access to remote resources, Grid technologies promise to make it possible for scientific collaborations to share resources on an unprecedented scale, and for geographically distributed groups to work together in ways that were previously impossible.

Similar technologies are being adopted within industry, where they serve as important building blocks for emerging service provider infrastructures.

Even though the advantages of this technology for classes of applications have been acknowledged, research in a variety of disciplines, including not only multiple domains of computer science (networking, middleware, programming, algorithms) but also application disciplines themselves, as well as such areas as sociology and economics, is needed to broaden the applicability and scope of the current body of knowledge.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2.9

Journal Rank

Year	Value
2024	7629

Journal Citation Indicator

Year	Value
2024	801

SJR (SCImago Journal Rank)

Year	Value
2024	0.734

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	63

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments

  Citation: 500

  Authors: Tania, Jose, Jose A.

• A Taxonomy of Workflow Management Systems for Grid Computing

  Citation: 484

  Authors: Jia, Rajkumar

• A Survey on Resource Scheduling in Cloud Computing: Issues and Challenges

  Citation: 375

  Authors: Sukhpal, Inderveer

• Mapping Abstract Complex Workflows onto Grid Environments

  Citation: 322

  Authors: Ewa, James, Yolanda, Carl, Gaurang, Karan, Kent, Albert, Adam, Richard, Scott

• Resource Management Approaches in Fog Computing: a Comprehensive Review

  Citation: 262

  Authors: Mostafa, Alireza, Ali A.

• An Energy-Efficient Task Scheduling Algorithm in DVFS-enabled Cloud Environment

  Citation: 231

  Authors: Zhuo, Ling, Zhenzhen, Kenli, Samee U., Keqin

• Architectural Requirements for Cloud Computing Systems: An Enterprise Cloud Approach

  Citation: 221

  Authors: Bhaskar Prasad, Admela, Dimitrios, Yves

• A Survey of Data-Intensive Scientific Workflow Management

  Citation: 221

  Authors: Ji, Esther, Patrick, Marta

• iCanCloud: A Flexible and Scalable Cloud Infrastructure Simulator

  Citation: 217

  Authors: Alberto, Jose L., Agustin C., Gabriel G., Jesus, Ignacio M.

• WeNMR: Structural Biology on the Grid

  Citation: 165

  Authors: Tsjerk A., Marc, Nuno, Gijs, Sjoerd J., Christophe, Johan, Rolf, Andrea, Lucio, Antonio, Ivano, Torsten, Hendrik R. A., Anurag, Victor, Peter, Harald, Wim F., Jurgen F., Gert, Geerten W., Daniel, Alexey, Dmitri I., Rasmus H., John, Ernest D., Chris, Simonas, Marco, Simone, Stefano, Mirco, Eric, Alexandre M. J. J.

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