Giuseppe Ruggeri

2.3k total citations
93 papers, 1.3k citations indexed

About

Giuseppe Ruggeri is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Giuseppe Ruggeri has authored 93 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Computer Networks and Communications, 27 papers in Electrical and Electronic Engineering and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Giuseppe Ruggeri's work include Caching and Content Delivery (33 papers), Opportunistic and Delay-Tolerant Networks (27 papers) and IoT and Edge/Fog Computing (24 papers). Giuseppe Ruggeri is often cited by papers focused on Caching and Content Delivery (33 papers), Opportunistic and Delay-Tolerant Networks (27 papers) and IoT and Edge/Fog Computing (24 papers). Giuseppe Ruggeri collaborates with scholars based in Italy, France and Spain. Giuseppe Ruggeri's co-authors include Antonella Molinaro, Marica Amadeo, Claudia Campolo, Antonio Iera, Francesco Beritelli, S. Casale, Valéria Loscrì, Franco Cicirelli, Giandomenico Spezzano and Andrea Vinci and has published in prestigious journals such as IEEE Access, IEEE Communications Magazine and Sensors.

In The Last Decade

Giuseppe Ruggeri

88 papers receiving 1.2k citations

Peers

Giuseppe Ruggeri

CNC

EEE

CVPR

Shahriar Nirjon United States

Yoshitaka Shibata Japan

Yunhao Liu China

Cristina Perfecto Spain

Yanchao Zhao China

Kamran Arshad United Kingdom

Aaron Carroll Australia

Pei Huang United States

M. Amaç Güvensan Türkiye

Ashish Bagwari India

Shahriar Nirjon United States

Giuseppe Ruggeri

315 ×0.3

CNC

427 ×1.2

EEE

181 ×1.6

178 ×1.6

286 ×2.7

CVPR

Citations per year, relative to Giuseppe Ruggeri Giuseppe Ruggeri (= 1×) peers Shahriar Nirjon

Countries citing papers authored by Giuseppe Ruggeri

Since Specialization

Citations

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

Fields of papers citing papers by Giuseppe Ruggeri

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Giuseppe Ruggeri

This figure shows the co-authorship network connecting the top 25 collaborators of Giuseppe Ruggeri. A scholar is included among the top collaborators of Giuseppe Ruggeri based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Giuseppe Ruggeri. Giuseppe Ruggeri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Amadeo, Marica, Salvatore Serrano, Antonella Molinaro, Michele Nitti, & Giuseppe Ruggeri. (2025). Enhancing IoT Service Discovery Through Semantic Name-Based Forwarding. IEEE Internet of Things Magazine. 9(2). 142–148.

Ruggeri, Giuseppe, Marica Amadeo, Claudia Campolo, & Antonella Molinaro. (2025). Optimal Placement of the Virtualized Federated Learning Aggregation Function at the Edge. IEEE Transactions on Network and Service Management. 22(3). 2580–2594.

Amadeo, Marica, Claudia Campolo, Giuseppe Ruggeri, & Antonella Molinaro. (2025). Improving communication performance of Federated Learning: A networking perspective. Computer Networks. 267. 111353–111353. 1 indexed citations

Amadeo, Marica & Giuseppe Ruggeri. (2025). Exploring In-Network Computing with Information-Centric Networking: Review and Research Opportunities. Future Internet. 17(1). 42–42. 4 indexed citations

Channa, Asma, et al.. (2024). Cloud-Connected Bracelet for Continuous Monitoring of Parkinson’s Disease Patients: Integrating Advanced Wearable Technologies and Machine Learning. Electronics. 13(6). 1002–1002. 5 indexed citations

Amadeo, Marica, et al.. (2024). Composing Digital Twins for Internet of Everything Applications: A User-Centric Perspective. Aaltodoc (Aalto University). 73–78. 2 indexed citations

Campolo, Claudia, et al.. (2024). An Edge-Based Digital Twin Framework for Connected and Autonomous Vehicles: Design and Evaluation. IEEE Access. 12. 46290–46303. 9 indexed citations

Amadeo, Marica, et al.. (2024). Cloud-Edge Resource Management and Migration: Leveraging Online Learning for Digital Twin Re-placement. Aaltodoc (Aalto University). 1–6.

Amadeo, Marica, et al.. (2023). In-network Placement of Reusable Computing Tasks in an SDN-based Network Edge. IEEE Transactions on Mobile Computing. 1–16. 13 indexed citations

10.

Amadeo, Marica, Claudia Campolo, Giuseppe Ruggeri, & Antonella Molinaro. (2022). Popularity-Aware Closeness Based Caching in NDN Edge Networks. Sensors. 22(9). 3460–3460. 13 indexed citations

11.

Channa, Asma, et al.. (2022). Parkinson's disease resting tremor severity classification using machine learning with resampling techniques. Frontiers in Neuroscience. 16. 955464–955464. 3 indexed citations

12.

Ruggeri, Giuseppe, Marica Amadeo, Claudia Campolo, Antonella Molinaro, & Antonio Iera. (2021). Caching Popular Transient IoT Contents in an SDN-Based Edge Infrastructure. IEEE Transactions on Network and Service Management. 18(3). 3432–3447. 30 indexed citations

13.

Amadeo, Marica, Claudia Campolo, Giuseppe Ruggeri, & Antonella Molinaro. (2021). Beyond Edge Caching: Freshness and Popularity Aware IoT Data Caching via NDN at Internet-Scale. IEEE Transactions on Green Communications and Networking. 6(1). 352–364. 39 indexed citations

14.

Amadeo, Marica, et al.. (2020). Caching Transient Contents in Vehicular Named Data Networking: A Performance Analysis. Sensors. 20(7). 1985–1985. 28 indexed citations

15.

Amadeo, Marica, et al.. (2020). Caching Popular and Fresh IoT Contents at the Edge via Named Data Networking. 610–615. 43 indexed citations

16.

Amadeo, Marica, Giuseppe Ruggeri, Claudia Campolo, & Antonella Molinaro. (2019). IoT Services Allocation at the Edge via Named Data Networking: From Optimal Bounds to Practical Design. IEEE Transactions on Network and Service Management. 16(2). 661–674. 42 indexed citations

17.

Amadeo, Marica, Claudia Campolo, Giuseppe Ruggeri, Antonella Molinaro, & Antonio Iera. (2019). SDN-Managed Provisioning of Named Computing Services in Edge Infrastructures. IEEE Transactions on Network and Service Management. 16(4). 1464–1478. 19 indexed citations

18.

Amadeo, Marica, Giuseppe Ruggeri, Claudia Campolo, et al.. (2019). Fog Computing in IoT Smart Environments via Named Data Networking: A Study on Service Orchestration Mechanisms. Future Internet. 11(11). 222–222. 9 indexed citations

19.

Luciani, Massimiliano, Marco Cecchini, Daniela Altavilla, et al.. (2014). Neural correlate of the projection of mental states on the not-structured visual stimuli. Neuroscience Letters. 573. 24–29. 19 indexed citations

20.

Aloi, Gianluca, Marco Di Felice, Valéria Loscrì, et al.. (2013). STEM-Net: An evolutionary architecture for highly-reconfigurable wireless networks. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 1–10. 2 indexed citations

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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