Professor at Carleton University
Department of Systems and Computer Engineering, Ottawa, Canada
Title: Modeling and Simulation of Cellular Networks: formalizing the models
- 2022 McLeod Founder Award for distinguished service to the profession by the Society for Modeling and Simulation International (SCS). This award recognizes a group of technical contributions which have been made by the candidate over a significant period of time. They clearly reflect a commitment by the candidate to nurturing a robust evolution of the profession. The significant nature of the contributions will be supported by their wide dissemination in the technical literature and their discernible impact on the manner in which some aspect of the modeling and simulation activity is carried out.
- 2021 Distinguished Speaker. Association for Computing Machinery (ACM).
- 2020 Outstanding Professional Achievement Award by the Society for Modeling and Simulation International (SCS). The award recognizes outstanding service to the Society by a member.
- 2019 IEEE Outstanding Engineering Award (Ottawa Section). “For innovative and outstanding contributions to the field of discrete-event modeling and simulation”
- 2017 Nepean’s Canada 150th Anniversary Medal. The medal was given in the 150 anniversary of Canadian Confederation to recognize people who have made a difference in the community or excelled in their professional life in the riding of Nepean, ON, Canada.
- 2016 Fellow, the Society for Modeling and Simulation International (SCS).
- DEVS formalism
- Real-Time modelling
- Cellular models
- Modelling and simulation methodologies and tools
- Parallel/distributed/Web-based simulation
- Real-Time operating systems
Modeling and Simulation methods have been used to better analyze the behavior of complex physical systems and it is now common to use simulation as a part of the technological discovery process. Formal M&S appeared in order to try to improve the development task of very complex simulation systems. Some of these techniques proved to be successful in providing a sound base for the development of discrete-event simulation models, improving the ease of model definition and enhancing the application development tasks, reducing costs and favoring reuse.
This is particularly important in the development of computer networks. Future mobile networks should provide high data rate services for their customers regardless of their location. This is a challenging task, specifically for the users in the edge of the cell’s area. To overcome this problem, Long Term Evolution Advanced introduced Coordinated Multi-Point (CoMP) and other advanced techniques were introduced. In this talk, we will present different methods developed recently for the next generation of mobile networks, based on CoMP and other techniques. We discuss different M&S techniques employed, and new results obtained that show that these methods can improve the performance for end users.
We will discuss Upload User Collaboration (UUC); an algorithm can be combined with CoMP to enhance the upload performance of cell-edge users.
We will then discuss new methods to improve the performance of video traffic in cellular networks. We present different algorithms that combine Device-to-Device (D2D) communication, introduced by the Long Term Evolution-Advanced standard (LTE-A). We present two algorithms for improving the throughput of video transmission in cellular networks. The algorithms are called Cached and Segmented Video Download (CSVD), and DIStributed, Cached, and Segmented video download (DISCS).
Finally, we discuss new methods for video streaming applications in Cellular networks. Providing high Quality of Experience (QoE) video streaming services is becoming a challenge due to the limited capacity in cellular networks and the impairments of transmission over radio links (e.g., path-loss and fading). As such, the parameters of the wireless communication on the radio access network between the Base-Station (BS) and User Equipment (UEs) have an effect on video streaming QoE. We study the impact of the wireless trans-mission parameters in Long Term Evolution-Advanced (LTE-A) networks on video streaming QoE. We consider both cell level and link level parameters. Dynamic Adaptive Streaming over HTTP (DASH) -based video streaming is considered here. We built a model for an LTE-A network and ran multiple simulations with various scenarios. We present and analyze the results to evaluate different video streaming QoE metrics, and to see how they are affected by the various cellular communication parameters.
These research results present a real-world use of formal Discrete EVent System specifications (DEVS) for modeling mobile networks, and practical case studies with industrial relevance (algorithms, based on the DEVS studies, were patented by Ericsson Inc. for commercialization). The studies compare different approaches and show how to improve the cell-edge users’ upload performance, and it reduces the time required to upload a file.
Data Science and Operations Research,
Universitat Politècnica de València (UPV, Spain)
Title: Why Sim-Learnheuristics? Solving Optimization Problems under Stochastic and Dynamic Scenarios
Dr. Angel A. Juan is a Full Professor (Catedrático de Universidad) of Data Science and Operations Research at the Universitat Politècnica de València (UPV, Spain). He has also been a Full Professor in the Dept. of Computer Science at the Universitat Oberta de Catalunya (UOC), as well as an Invited Professor at the University College Dublin (Ireland), Universidade Aberta (Portugal), Euncet Business School, Università di Modena e Reggio Emilia (Italy), Universitat Autònoma de Barcelona, and Universitat Politècnica de Catalunya.
Dr. Juan holds a Ph.D. in Industrial Engineering / Applied Mathematics, an M.S. in Information Systems & Technology, and an M.S. & B.Sc. in Mathematics. He completed predoctoral internships at Harvard University (USA) and at Universidad de Alicante (Spain), and has been Visiting Researcher at the following institutions: Massachusetts Institute of Technology (USA), Georgia Institute of Technology (USA), University of Southampton (UK), University of Portsmouth (UK), Technical University of Dortmund (Germany), Trinity College Dublin (Ireland), LAAS-CNRS (France), University of Natural Resources and Life Sciences (Austria), and University of Bologna (Italy).
His main research interests include applications of Data Analytics, Optimization, Simulation, and Artificial Intelligence in Computational Transportation & Logistics, Production & Manufacturing, Computational Finance & Insurance, and Smart Cities. He has published over 150 articles in JCR-indexed journals and more than 325 documents indexed in Scopus. Dr. Juan is or has been Principal Investigator of several R&D projects, including: four Spanish R&D projects, three European projects, two CYTED international networks, six Spanish networks of excellence, two France-Spain CTP networks, three regional projects, and four Erasmus+ Consortia. In addition, he has contributed as a researcher in many other R&D projects of international and national scope.
Dr. Juan is one of the founders of the Decision Science Alliance. He is a member of the Mathematics / Business Expert Panels of the Flanders Research Foundation (FWO) and the Agencia Andaluza del Conocimiento (AAC). He has been a Council member of the INFORMS i-Sim society, as well as an Executive Council member of the Spanish Society of Statistics and Operations Research (SEIO). He is also Referee of the Spanish State Research Agency (AEI) as well as Editorial Board member of several international journals: Internet of Things, J. of Simulation, European J. of Industrial Engineering, Algorithms, Int. J. of Data Analysis Techniques and Strategies, Int. J. of Educational Technology in Higher Education, etc. He has been general co-chair of several international conferences, as well as Proceedings Editor and Track Chair in the prestigious Winter Simulation Conference.
Dr. Juan is the Academic Director of the MBA at UPV-Alcoy. He has been co-founder and Academic Director of the URV-UOC MSc. in Computational Engineering & Mathematics as well as of the UOC MSc. in Bioinformatics & Biostatistics. He has also been the UOC Academic Director of the inter-university Doctoral Program in Bioinformatics (Data Science). He has supervised over 15 PhD theses, 50+ MSc. theses, and 70+ BSc. theses (already finished) in up to 8 different universities in Spain, the UK, Ireland, Portugal, Germany, and the Netherlands.
Dr. Juan has been included in different national and international rankings, such as the ones provided by the DIH Group, and the Research.com.
Optimizing complex problems under uncertainty is a persistent challenge across diverse industries, from logistics and manufacturing to finance and telecommunication networks. In response, Simheuristics have emerged as a flexible approach, seamlessly blending the power of simulation and metaheuristics to tackle optimization tasks under stochastic conditions. However, the world does not always behave in purely stochastic ways; it also presents non-stochastic uncertainties that require unique strategies. Enter Fuzzy Simheuristics, an extension of the traditional framework, capable of addressing these nuanced uncertainties and providing more comprehensive optimization outcomes. But the pursuit of practical applicability does not stop there. To confront dynamic conditions where change is the norm, Sim-Learnheuristics have evolved. This novel approach combines the adaptability of Simheuristics with machine learning, enabling decision-making in environments marked by constant change. In this presentation, we discuss the evolution of these concepts, from Simheuristics to Fuzzy Simheuristics and Sim-Learnheuristics, all tailored to meet the evolving demands of optimization in an ever-uncertain world.