Jasmin Guth

403 citations
5 papers · 143 · h-index 4

Impact in

    • IoT and Edge/Fog Computing
    • Software System Performance and Reliability
    • Cloud Computing and Resource Management
    • Blockchain Technology Applications and Security
    • Service-Oriented Architecture and Web Services

Papers in

Journals
Fachbereich Informatik (University of Stuttgart) (3 papers)IEEE Conference Proceedings (1 paper)
Partner nations
Germany

In The Last Decade

Jasmin Guth

5 papers receiving 136 citations

Peers

Jasmin Guth
Comparison fields: 5 of 43
  • Computer Networks and Communications 104
  • Information Systems 60
  • Software 6
  • Industrial and Manufacturing Engineering 12
  • Media Technology 9
Replace Lukas Reinfurt with:
Lukas Reinfurt Germany
Didier Donsez France
Samer Salam Lebanon
Matteo Casadei Italy
Hamid R. Barzegar Italy
Joaõ Pedro Dias Portugal
Abdelrahman H. Hussein Jordan
Ali Raza United States
Biresh Kumar India
Mercedes Amor Spain
Jasmin Guth relative to Lukas Reinfurt Germany Lukas Reinfurt's profile →
Citations per field
00.5×1.5×
Lukas Reinfurt · 1×
Citations per year

Countries citing papers authored by Jasmin Guth

Since Specialization
Citations

This map shows the geographic impact of Jasmin Guth's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jasmin Guth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jasmin Guth more than expected).

Fields of papers citing papers by Jasmin Guth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jasmin Guth. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jasmin Guth. The network helps show where Jasmin Guth may publish in the future.

Co-authors

The 5 scholars most cited alongside Jasmin Guth, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jasmin Guth Line = papers co-authored together Jasmin Guth links everyone, so they are left out of the graph.

All Works

5 of 5 papers shown
#Work
1 2016122
2 201812
3 20194
4
Pattern-based Deployment Models Revisited: Automated Pattern-driven Deployment Configuration
20203
5
Comparison of IoT platform architectures: A field study based on a reference architecture
20162

About Jasmin Guth

Jasmin Guth is a scholar working on Computer Networks and Communications, Artificial Intelligence, Software, Information Systems and Computer Vision and Pattern Recognition, having authored 5 papers that have together received 143 indexed citations. Recurring topics across this work include Model-Driven Software Engineering Techniques (2 papers), Advanced Software Engineering Methodologies (2 papers), Embedded Systems Design Techniques (1 paper), Service-Oriented Architecture and Web Services (1 paper), Green IT and Sustainability (1 paper), Cloud Computing and Resource Management (1 paper), Modular Robots and Swarm Intelligence (1 paper) and Software System Performance and Reliability (1 paper). The work is most often cited by research in Computer Networks and Communications (104 citations), Information Systems (60 citations), Software (6 citations), Industrial and Manufacturing Engineering (12 citations) and Media Technology (9 citations). Jasmin Guth has collaborated with scholars based in Germany. Frequent co-authors include Frank Leymann, Uwe Breitenbücher, Michael Falkenthal, Lukas Reinfurt and C. Krieger. Their work appears in journals such as Fachbereich Informatik (University of Stuttgart) and IEEE Conference Proceedings.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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