Roberto Riggio

3.1k total citations
133 papers, 2.1k citations indexed

About

Roberto Riggio is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Information Systems. According to data from OpenAlex, Roberto Riggio has authored 133 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 123 papers in Computer Networks and Communications, 71 papers in Electrical and Electronic Engineering and 9 papers in Information Systems. Recurrent topics in Roberto Riggio's work include Software-Defined Networks and 5G (65 papers), Wireless Networks and Protocols (51 papers) and Mobile Ad Hoc Networks (26 papers). Roberto Riggio is often cited by papers focused on Software-Defined Networks and 5G (65 papers), Wireless Networks and Protocols (51 papers) and Mobile Ad Hoc Networks (26 papers). Roberto Riggio collaborates with scholars based in Italy, Spain and Germany. Roberto Riggio's co-authors include Davit Harutyunyan, Estefanía Coronado, Tinku Rasheed, Tejas Subramanya, Fabrizio Granelli, Leonardo Goratti, Karina Gomez, Julius Schulz-Zander, Mahesh K. Marina and Francesco De Pellegrini and has published in prestigious journals such as IEEE Communications Surveys & Tutorials, IEEE Access and IEEE Communications Magazine.

In The Last Decade

Roberto Riggio

131 papers receiving 2.0k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Roberto Riggio 1.8k 1.1k 251 136 96 133 2.1k
Pablo Serrano 1.9k 1.1× 1.4k 1.2× 130 0.5× 134 1.0× 87 0.9× 115 2.2k
Ricard Vilalta 2.0k 1.1× 2.1k 1.9× 303 1.2× 114 0.8× 45 0.5× 282 2.9k
Jiang Xie 2.0k 1.1× 1.6k 1.4× 138 0.5× 135 1.0× 76 0.8× 118 2.3k
Ziaul Haq Abbas 1.1k 0.6× 1.2k 1.0× 309 1.2× 266 2.0× 179 1.9× 118 1.8k
Jude Okwuibe 1000 0.6× 553 0.5× 334 1.3× 223 1.6× 105 1.1× 14 1.3k
Guy Pujolle 1.1k 0.6× 631 0.6× 281 1.1× 207 1.5× 39 0.4× 108 1.4k
Rami Langar 1.3k 0.7× 923 0.8× 249 1.0× 106 0.8× 47 0.5× 74 1.5k
Andrés García‐Saavedra 1.9k 1.0× 1.5k 1.4× 131 0.5× 161 1.2× 155 1.6× 100 2.4k
Jaime Llorca 1.7k 0.9× 597 0.5× 317 1.3× 115 0.8× 100 1.0× 87 1.9k
Cristiano Bonato Both 870 0.5× 537 0.5× 175 0.7× 111 0.8× 72 0.8× 96 1.1k

Countries citing papers authored by Roberto Riggio

Since Specialization
Citations

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

Fields of papers citing papers by Roberto Riggio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roberto Riggio

This figure shows the co-authorship network connecting the top 25 collaborators of Roberto Riggio. A scholar is included among the top collaborators of Roberto Riggio 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 Roberto Riggio. Roberto Riggio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Addis, Bernardetta, et al.. (2024). Function Placement for In-network Federated Learning. Computer Networks. 256. 110900–110900.
2.
Chiumento, Alessandro, et al.. (2023). QoS Aware Slice Resource Management Using Deep Reinforcement Learning in IoT Networks. University of Twente Research Information. 150–154. 1 indexed citations
3.
Coronado, Estefanía, et al.. (2022). Roadrunner: O-RAN-based Cell Selection in Beyond 5G Networks. Università Politecnica delle Marche (Università Politecnica delle Marche). 1–7. 11 indexed citations
4.
Schembra, Giovanni, Wolfgang Kellerer, Christian Jacquenet, et al.. (2022). Guest Editors’ Introduction: Special Section on Smart Management of Future Softwarized Networks. IEEE Transactions on Network and Service Management. 19(3). 1942–1950. 1 indexed citations
5.
Coronado, Estefanía, et al.. (2022). INGR Roadmap Edge Services and Automation Chapter. 1–49. 1 indexed citations
6.
Bayhan, Suzan, Estefanía Coronado, Roberto Riggio, & Anatolij Zubow. (2020). User-AP Association Management in Software-Defined WLANs. IEEE Transactions on Network and Service Management. 17(3). 1838–1852. 10 indexed citations
7.
Ferrús, R., et al.. (2019). Design and Experimental Validation of a Software-Defined Radio Access Network Testbed with Slicing Support. Wireless Communications and Mobile Computing. 2019. 1–17. 16 indexed citations
8.
Harutyunyan, Davit, Roberto Riggio, Sławomir Kukliński, & Toufik Ahmed. (2019). CU placement over a reconfigurable wireless fronthaul in 5G networks with functional splits. International Journal of Network Management. 30(1). 4 indexed citations
9.
Quang, Pham Tran Anh, Abbas Bradai, Kamal Singh, Gauthier Picard, & Roberto Riggio. (2018). Single and Multi-Domain Adaptive Allocation Algorithms for VNF Forwarding Graph Embedding. IEEE Transactions on Network and Service Management. 16(1). 98–112. 40 indexed citations
10.
Harutyunyan, Davit & Roberto Riggio. (2017). Flexible functional split in 5G networks. Institutional Research Information System (Università degli Studi di Trento). 1–9. 25 indexed citations
11.
Subramanya, Tejas, et al.. (2017). A practical architecture for mobile edge computing. Institutional Research Information System (Università degli Studi di Trento). 1–4. 12 indexed citations
12.
Coronado, Estefanía, Roberto Riggio, José Villalón, & A. Garrido. (2017). Efficient Real-Time Content Distribution for Multiple Multicast Groups in SDN-Based WLANs. IEEE Transactions on Network and Service Management. 15(1). 430–443. 10 indexed citations
13.
Riggio, Roberto, et al.. (2016). SWAN: Base-Band Units Placement over Reconfigurable Wireless Front-Hauls. 28–36. 2 indexed citations
14.
Welzl, Michael, et al.. (2016). Congestion control in the recursive InterNetworking Architecture (RINA). Università Politecnica delle Marche (Università Politecnica delle Marche). 1–7. 4 indexed citations
15.
Riggio, Roberto. (2016). The EmPOWER mobile network operating system. Università Politecnica delle Marche (Università Politecnica delle Marche). 87–88. 5 indexed citations
16.
Riggio, Roberto, Francesco De Pellegrini, Elio Salvadori, Matteo Gerola, & Roberto Doriguzzi-Corin. (2013). Progressive virtual topology embedding in OpenFlow networks. Integrated Network Management. 1122–1128. 16 indexed citations
17.
Sicari, Sabrina, Alberto Coen‐Porisini, & Roberto Riggio. (2013). DARE: evaluating Data Accuracy using node REputation. Computer Networks. 57(15). 3098–3111. 19 indexed citations
18.
Riggio, Roberto, et al.. (2012). Up in the clouds: A taxonomical analysis of network management functionalities from a network as a service perspective. European Wireless Conference. 1–8. 2 indexed citations
19.
Riggio, Roberto, Francesco De Pellegrini, Daniele Miorandi, & Imrich Chlamtac. (2007). A Knowledge Plane for Wireless Mesh Networks. Ad Hoc & Sensor Wireless Networks. 5. 293–311. 3 indexed citations
20.
Pellegrini, Francesco De, et al.. (2007). Measuring the Quality of VoIP Traffic on a WiMAX Testbed. Università Politecnica delle Marche (Università Politecnica delle Marche). 19. 1–10. 16 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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