Luis M. Contreras

1.8k total citations
129 papers, 1.2k citations indexed

About

Luis M. Contreras is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Information Systems. According to data from OpenAlex, Luis M. Contreras has authored 129 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 112 papers in Computer Networks and Communications, 69 papers in Electrical and Electronic Engineering and 18 papers in Information Systems. Recurrent topics in Luis M. Contreras's work include Software-Defined Networks and 5G (84 papers), Advanced Optical Network Technologies (44 papers) and Caching and Content Delivery (17 papers). Luis M. Contreras is often cited by papers focused on Software-Defined Networks and 5G (84 papers), Advanced Optical Network Technologies (44 papers) and Caching and Content Delivery (17 papers). Luis M. Contreras collaborates with scholars based in Spain, Italy and United States. Luis M. Contreras's co-authors include Carlos J. Bernardos, Antonio de la Oliva, Vı́ctor López, Albert Banchs, Juan Carlos Zúñiga, Pablo Serrano, Hao Jin, Luis Velasco, Marc Ruiz and Lluís Gifre and has published in prestigious journals such as IEEE Communications Magazine, Sensors and Journal of Lightwave Technology.

In The Last Decade

Luis M. Contreras

117 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Luis M. Contreras Spain 16 973 686 151 64 61 129 1.2k
Marius Corici Germany 18 826 0.8× 478 0.7× 111 0.7× 58 0.9× 54 0.9× 103 1.0k
Ibrahim Afolabi Finland 8 981 1.0× 488 0.7× 88 0.6× 34 0.5× 72 1.2× 9 1.1k
Xenofon Foukas United Kingdom 9 1.1k 1.1× 683 1.0× 66 0.4× 55 0.9× 103 1.7× 21 1.2k
José Ordoñez-Lucena Spain 10 761 0.8× 394 0.6× 83 0.5× 39 0.6× 62 1.0× 23 874
Fabio Giust Spain 14 705 0.7× 471 0.7× 121 0.8× 28 0.4× 49 0.8× 24 784
Jaya Rao Canada 17 791 0.8× 674 1.0× 57 0.4× 42 0.7× 59 1.0× 30 993
Koteswararao Kondepu Italy 16 583 0.6× 671 1.0× 82 0.5× 68 1.1× 35 0.6× 118 928
Hiroaki Harai Japan 17 739 0.8× 1.1k 1.7× 96 0.6× 23 0.4× 56 0.9× 213 1.5k
George Xilouris Greece 17 695 0.7× 314 0.5× 146 1.0× 60 0.9× 53 0.9× 81 858

Countries citing papers authored by Luis M. Contreras

Since Specialization
Citations

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

Fields of papers citing papers by Luis M. Contreras

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luis M. Contreras. 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 Luis M. Contreras. The network helps show where Luis M. Contreras may publish in the future.

Co-authorship network of co-authors of Luis M. Contreras

This figure shows the co-authorship network connecting the top 25 collaborators of Luis M. Contreras. A scholar is included among the top collaborators of Luis M. Contreras 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 Luis M. Contreras. Luis M. Contreras 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.
Moreno, José Ignacio, et al.. (2024). Architecture and Methodology for Green MEC Services Using Programmable Data Planes in 5G and Beyond Networks. 738–743. 3 indexed citations
2.
Díez, Luis, et al.. (2024). QoS-Aware scheduling policies for Open Fronthaul transport networks. UCrea (University of Cantabria). 335–340.
3.
Jiménez, David, et al.. (2024). Multisite gaming streaming optimization over virtualized 5G environment using Deep Reinforcement Learning techniques. Computer Networks. 244. 110334–110334. 5 indexed citations
4.
Velivassaki, Terpsichori-Helen, Theodοre Zahariadis, Panagiotis Karkazis, et al.. (2024). NExt generation Meta Operating systems (NEMO) and Data Space: envisioning the future. 41–49.
5.
Arpanaei, Farhad, Juan Pedro Fernández-Palacios Giménez, Óscar González de Dios, et al.. (2024). TEFNET24: reference packet optical network topology for edge to core transport. Journal of Optical Communications and Networking. 16(11). G28–G28. 3 indexed citations
6.
Chochliouros, Ioannis P., Theodοre Zahariadis, Terpsichori-Helen Velivassaki, et al.. (2023). NEMO: Building the Next Generation Meta Operating System. 1–9. 4 indexed citations
7.
Costa, A. & Luis M. Contreras. (2023). Integration of Network Slice Controller for Enhanced Intent-Based Networking in 5G/6G Networks. Zenodo (CERN European Organization for Nuclear Research). 31–36. 4 indexed citations
8.
Jiménez, David, et al.. (2022). Design, Implementation, and Validation of a Multi-Site Gaming Streaming Service Over a 5G-Enabled Platform. IEEE Transactions on Broadcasting. 68(2). 464–474. 3 indexed citations
9.
Antonopoulos, Angelos, et al.. (2022). Cost-Aware Placement and Enhanced Lifecycle Management of Service Function Chains in a Multidomain 5G Architecture. IEEE Transactions on Network and Service Management. 19(4). 5006–5020. 8 indexed citations
10.
Jiménez, David, et al.. (2022). A Deep Reinforcement Learning Quality Optimization Framework for Multimedia Streaming over 5G Networks. Applied Sciences. 12(20). 10343–10343. 8 indexed citations
11.
Cardoso, Kléber V., et al.. (2021). PlaceRAN: Optimal Placement for the Virtualized Next-Generation RAN.. arXiv (Cornell University).
12.
Contreras, Luis M., et al.. (2020). Information Exchange to Support Multi-Domain Slice Service Provision for 5G/NFV. e-Archivo (Carlos III University of Madrid). 773–778. 2 indexed citations
13.
Lashgari, Maryam, Carlos Natalino, Luis M. Contreras, Lena Wosinska, & Paolo Monti. (2019). Cost Benefits of Centralizing Service Processing in 5G Network Infrastructures. Chalmers Research (Chalmers University of Technology). 3 indexed citations
14.
Neto, Augusto, Rafael Pasquini, Christian Esteve Rothenberg, et al.. (2018). NECOS Project: Towards Lightweight Slicing of Cloud Federated Infrastructures. UCL Discovery (University College London). 406–414. 29 indexed citations
15.
Ruiz, Marc, et al.. (2016). Big Data-backed video distribution in the telecom cloud. Computer Communications. 84. 1–11. 18 indexed citations
16.
Li, Xi, Giada Landi, José Núñez‐Martínez, et al.. (2016). Innovations through 5G-Crosshaul applications. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 382–387. 8 indexed citations
17.
Gifre, Lluís, Massimo Tornatore, Luis M. Contreras, Biswanath Mukherjee, & Luis Velasco. (2015). ABNO-driven content distribution in the telecom cloud. Optical Switching and Networking. 26. 25–38. 1 indexed citations
18.
Contreras, Luis M., Carlos J. Bernardos, & Ignacio Soto. (2011). Rams: A protocol extension to pmipv6 for improving handover performance of multicast traffic. 5 indexed citations
19.
Contreras, Luis M., et al.. (2011). On the efficiency of a dedicated LMA for multicast traffic distribution in PMIPv6 domains. UPM Digital Archive (Technical University of Madrid). 1 indexed citations
20.
Wu, Bo, et al.. (1998). IETF Network Slice Controller and its associated data models. 1 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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