Daniel Grzonka

400 citations
18 papers · 249 · h-index 9

Impact in

    • IoT and Edge/Fog Computing
    • Distributed and Parallel Computing Systems
    • Caching and Content Delivery
    • Network Security and Intrusion Detection
    • Cloud Computing and Resource Management
    • Blockchain Technology Applications and Security
    • Cloud Data Security Solutions

Papers in

Daniel Grzonka

18 papers receiving 226 citations

Peers

Daniel Grzonka
Comparison fields: 5 of 45
  • Computer Networks and Communications 177
  • Information Systems 167
  • Hardware and Architecture 29
  • Management Information Systems 10
  • Artificial Intelligence 34
Replace Saloni Jain with:
Saloni Jain United States
Zujie Ren China
Ismael Solís Moreno United Kingdom
Mayank Aggarwal India
Mostapha Zbakh Morocco
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Citations per field
00.5×2.8×
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Citations per year

Countries citing papers authored by Daniel Grzonka

Since Specialization
Citations

This map shows the geographic impact of Daniel Grzonka'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 Daniel Grzonka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Grzonka more than expected).

Fields of papers citing papers by Daniel Grzonka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Grzonka. 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 Daniel Grzonka. The network helps show where Daniel Grzonka may publish in the future.

Co-authors

The 19 scholars most cited alongside Daniel Grzonka, 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 Daniel Grzonka Line = papers co-authored together Daniel Grzonka links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 201765
2 201442
3 201841
4 201621
5 201613
6 201511
7 201710
8
Application of selected supervised classification methods to bank marketing campaign
20169
9 20158
10 20256
11 20146
12 20234
13 20174
14 20253
15 20213
16 20231
17 20221
18 20191

About Daniel Grzonka

Daniel Grzonka is a scholar working on Information Systems, Computer Networks and Communications, Hardware and Architecture, Sociology and Political Science and Artificial Intelligence, having authored 18 papers that have together received 249 indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (11 papers), Distributed and Parallel Computing Systems (6 papers), IoT and Edge/Fog Computing (5 papers), Parallel Computing and Optimization Techniques (4 papers), Cloud Data Security Solutions (3 papers), Caching and Content Delivery (3 papers), Spam and Phishing Detection (1 paper) and Cellular Automata and Applications (1 paper). The work is most often cited by research in Computer Networks and Communications (177 citations), Information Systems (167 citations), Hardware and Architecture (29 citations), Management Information Systems (10 citations) and Artificial Intelligence (34 citations). Daniel Grzonka has collaborated with scholars based in Poland, Saudi Arabia and Malaysia. Frequent co-authors include Joanna Kołodziej, Agnieszka Jakóbik, Sabri Pllana, Jie Tao, Samee U. Khan, Alejandro Fernández-Montes, Francesco Palmieri, Horacio González–Vélez, Grażyna Suchacka and Irshad Ahmed Abbasi. Their work appears in journals such as Future Generation Computer Systems, Scientific Reports, Journal of Parallel and Distributed Computing, Simulation Modelling Practice and Theory and Mobile Networks and Applications.

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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