Ivan Zyrianoff
Impact in
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- IoT and Edge/Fog Computing
- Caching and Content Delivery
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- Context-Aware Activity Recognition Systems
Papers in ⓘ
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- IoT and Edge/Fog Computing 25
- Caching and Content Delivery 4
- Software System Performance and Reliability 4
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- Context-Aware Activity Recognition Systems 11
- Co-authors
- Carlos Kamienski (24 shared papers)Marco Di Felice (24 shared papers)Tullio Salmon Cinotti (5 shared papers)Federico Montori (11 shared papers)João Henrique Kleinschmidt (6 shared papers)Juha-Pekka Soininen (3 shared papers)Luca Sciullo (11 shared papers)Angelo Trotta (7 shared papers)
In The Last Decade
Ivan Zyrianoff
37 papers receiving 337 citations
Peers
Comparison fields: 5 of 58
- Computer Networks and Communications 198
- Computer Vision and Pattern Recognition 61
- Information Systems 67
- Computer Science Applications 11
- Water Science and Technology 27
Countries citing papers authored by Ivan Zyrianoff
This map shows the geographic impact of Ivan Zyrianoff'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 Ivan Zyrianoff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Zyrianoff more than expected).
Fields of papers citing papers by Ivan Zyrianoff
This network shows the impact of papers produced by Ivan Zyrianoff. 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 Ivan Zyrianoff. The network helps show where Ivan Zyrianoff may publish in the future.
Co-authors
The 25 scholars most cited alongside Ivan Zyrianoff, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 53 | |
| 2 | 2017 | 32 | |
| 3 | 2018 | 31 | |
| 4 | 2015 | 22 | |
| 5 | 2018 | 21 | |
| 6 | 2023 | 21 | |
| 7 | 2020 | 18 | |
| 8 | 2022 | 15 | |
| 9 | 2024 | 13 | |
| 10 | 2020 | 12 | |
| 11 | 2021 | 10 | |
| 12 | 2020 | 10 | |
| 13 | 2023 | 9 | |
| 14 | 2023 | 9 | |
| 15 | 2022 | 9 | |
| 16 | 2022 | 8 | |
| 17 | 2024 | 6 | |
| 18 | 2021 | 5 | |
| 19 | 2018 | 5 | |
| 20 | 2021 | 5 |
About Ivan Zyrianoff
Ivan Zyrianoff is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Information Systems and Plant Science, having authored 41 papers that have together received 345 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (25 papers), Context-Aware Activity Recognition Systems (11 papers), IoT Networks and Protocols (7 papers), Caching and Content Delivery (4 papers), Blockchain Technology Applications and Security (4 papers), Cloud Computing and Resource Management (4 papers), Software System Performance and Reliability (4 papers) and Smart Agriculture and AI (4 papers). The work is most often cited by research in Computer Networks and Communications (198 citations), Computer Vision and Pattern Recognition (61 citations), Information Systems (67 citations), Computer Science Applications (11 citations) and Water Science and Technology (27 citations). Ivan Zyrianoff has collaborated with scholars based in Italy, Brazil and Germany. Frequent co-authors include Carlos Kamienski, Marco Di Felice, Tullio Salmon Cinotti, Federico Montori, João Henrique Kleinschmidt, Juha-Pekka Soininen, Luca Sciullo, Angelo Trotta, Marc Jentsch and Luca Roffia. Their work appears in journals such as IEEE Internet of Things Journal, IEEE Access, Ad Hoc Networks, Applied Sciences and IEEE Communications Magazine.
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.