Prof. Dr. Rafael Kunst
Applied Computing Graduate Program, University of Rio dos Sinos Valley (Unisinos), Sao Leopoldo, Brazil
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Academic Career Length
18Years (2009-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications1 May 2019 in Ad Hoc Networks
Journal Article
PMPatric Marques
Patric Marques
DMDiogo Manfroi
Diogo Manfroi
EDEduardo Deitos
Eduardo Deitos
JCJonatan Cegoni
Jonatan Cegoni
RCRodrigo Castilhos
Rodrigo Castilhos
Rafael Kunst +2
1 October 2021 in Computer Networks
Journal Article
LCLuis Antonio L.F. da Costa
Luis Antonio L.F. da CostaRafael Kunst
Edison Pignaton de FreitasJournal Article
FPFaezeh Pasandideh
Faezeh PasandidehJCJoão Paulo Carvalho Lustosa Da Costa
João Paulo Carvalho Lustosa Da CostaRafael Kunst
Nahina IslamWHWibowo Hardjawana
Wibowo HardjawanaEdison Pignaton de FreitasRecent advances in unmanned aerial vehicles (UAVs), or drones, have made them able to communicate and collaborate, forming flying ad hoc networks (FANETs). FANETs are becoming popular in many application domains, including precision agriculture, goods delivery, construction, environment and climate monitoring, and military surveillance. These interesting new avenues for the use of UAVs are motivating researchers to rethink the existing research on FANETs. Therefore, this paper provides a comprehensive and thorough review of the different types of UAVs used in FANETs, their mobility models, main characteristics, and applications, as well as the routing protocols used in this type of network. Other important contributions of this paper include the investigation of emerging technologies integrated with FANETs.
1 February 2020 in Computers and Electronics in Agriculture
Journal Article
RRRodrigo da Rosa Righi
Rodrigo da Rosa Righi
GGGuilherme Goldschmidt
Guilherme Goldschmidt
Rafael KunstCDCássio Deon
Cássio Deon
Cristiano da Costa1 August 2019 in Engineering Applications of Artificial Intelligence
Journal Article
Rafael KunstLALeandro Avila
Leandro AvilaABAlécio Binotto
Alécio Binotto
Edison Pignaton de FreitasSBSergio Bampi
Sergio Bampi
JRJuergen Rochol
Juergen Rochol
1 April 2013
Conference Paper
LFLeonardo Roveda Faganello
Leonardo Roveda Faganello
Rafael KunstCBCristiano Bonato Both
Cristiano Bonato BothLGLisandro Zambenedetti Granville
Lisandro Zambenedetti Granville
JRJuergen Rochol
Juergen Rochol
Cognitive Radio Networks enable a higher number of users to access the spectrum of frequency simultaneously. This access is possible due to the implementation of dynamic spectrum allocation algorithms. In this context, one of the main algorithms found in the literature is the reinforcement learning based approach called Q-Learning. Although been widely applied, this algorithm does not take into account accurate information about the behavior of users neither the channel propagation conditions. In this sense, we propose three improvements to the dynamic spectrum allocation algorithms based on reinforcement learning for cognitive sensor networks. Simulation results show that all the proposed algorithms allow allocating channels with up to 6dB better quality and 4% higher efficiency than Q-Learning.
About Me
Rafael Kunst is a professor and researcher at the Applied Computing Graduate Program of the University of Vale do Rio dos Sinos (Unisinos), Brazil, where he is a member of the Software Innovation Laboratory (SOFTWARELAB). He is a faculty member of the Economics Graduate Program working with topics related to data science. He is an ad hoc consultant for the Brazilian Ministry of Education. He holds a PhD and an MSc degree in computer science, both received from the Federal University of Rio Grande do Sul (UFRGS). His current research interests involve data science, machine learning, next-generation mobile communications such as 5G and 6G, military communications, Industry 4.0, smart cities, and the Internet of things. He has extensive experience as a consultant, coordinating and participating in projects with companies from Brazil and abroad. In 2009 and 2010, he was an invited researcher at the University of Pisa, Italy, and in 2020, he was a visiting professor at the IBM Watson IoT Center in Munich, Germany.