MOYAL Pascal

I work in Probability theory and Applied Probability. My research activities focuses on stochastic processes: 

• Markov modeling,
• Weak approximation and convergence,
• Random dynamics on graphs and general discrete structures,
• Random graphs,
• Ergodic theoretical approach,
• Reinforcement learning.

My work find their applications in:

• Optimization of Healthcare systems;
• Performance analysis of Telecommunication networks;
• Network modeling;
• Epidemiology.

PhD students (current):

• Thomas Masanet (Co-advised by C. Jacquelinet)
• Runbo Su (Co-advised by E. Natalizio).

PhD student (past):

• Mohammed Habib Diallo Aoudi (Co-advised with V. Robin – defended June 2023)
• Jocelyn Begeot (Co-advised with I. Marcovici – defended December 2022)
• Youssef Rahme (Defended April 2021)
• Eustache Besançon (Co-advised with L. Decreusefond – defended December 2020).

• Agence de la Biomédecine
• LORIA
• LIP6
• IEMS Department – Northwestern University
• UC London Business School
• CONICET
• Telecom ParisTech
• UTC
• University of North Carolina,
• LAAS Toulouse

• I am Head of the M2 IMSD (Ingénierie Mathématiques et Sciences des Données) of Université de Lorraine.
• I am also Lecturer at Telecom ParisTech, in the Parisian Master program in Operations Research (MPRO) at Ecole des Ponts and Telecom Sud Paris.

In 2024-25, I teach the following classes:

• Introduction to Mathematical Finance (M2 IMSD);
• Stochastic calculus for finance (M2 IMSD);
• Applied stochastic modeling (M2 IMSD);
• Reinforcement learning (M2 IMSD);
• Random graphs applications (M2 MFA);
• Random graphs and Neural networks (M1 math);
• Queueing theory and simulation (MPRO);
• Stochastic calculus (Telecom ParisTech);
• Operations research, queueing theory and graph theory (Ecole des Ponts);
• Queueing systems (Telecom Sud Paris).

Books

• Stochastic Modeling and Analysis of Telecom Networks (with L. Decreusefond) ISTE Wiley , 2012.
• Modelisation et Analyse Stochastiques des reseaux de Telecommunications (in French) (with L. Decreusefond) Hermes Lavoisier , 2011.

Recent work

• Soprano Loto, N., Jonckheere, M. and Moyal, P. Online matching for the multiclass stochastic block model, submitted for publication,
• Moyal, P., Busic, A. and Mairesse, J. Loynes construction for the extended bipartite matching, submitted for publication.
• Su, R., Riahi Sfar, A., Natalizio, E., Moyal, P. and Song, Y.Q. SOPHT: a PHase-based Trust management framework for Service-oriented IoT/IIoT, under revision,
• Masanet, T., Audry, B., Jacquelinet, C. and Moyal, P. Toward organ shortage resilient allocation policies using real-time queueing models for liver transplantation, under revision,
• Diallo Aoudi, M.H.A., Moyal, P. and Robin, V. Large graph limits of local matching algorithms on uniform random graphs, submitted for publication.
• Jean, L. and Moyal, P. Dynamic programming for the stochastic matching model on general graphs: the case of the `N-graph’, submitted for publication.

Papers in international journals

• [33] Moyal, P., Busic, A. and Mairesse, J. (2024). On the sub-additivity of stochastic matching, Queueing systems: Theory and applications 107, 295-339. 
• [32] Su, R., Riahi, A., Natalizio, E., Moyal, P., Saint-Jore, A. and Song, Y. Q. (2024) Assessing intra-and inter-community trustworthiness in IoT: A role-based attack-resilient dynamic trust management model, Internet of Things: 101213.
• [31] Masanet, T. and Moyal, P. (2024) Perfect sampling of stochastic matching models with reneging, Advances in Applied Probability 56(4), 1-32. 
• [30] Besançon, E., Coutin, L., Decreusefond, L. and Moyal, P. (2024) Diffusive limits of Lipschitz functionals of Poisson measures, Annals of Applied Probability 34(1A), 555-584. 
• [29] Begeot, J., Marcovici, I. and Moyal, P. (2023)  Stability regions of systems with compatibilities, and ubiquitous measures on graphs, Queueing Systems: Theory and Applications 103, 275–312.
  
• [28] Jonckheere, M., Moyal, P., Ramírez, C. and Soprano-Loto, N. (2023) Generalized max-weight policies in stochastic matching , Stochastic Systems 13(1), 40-58.
• [27] Diallo Aoudi, M.H.A., Moyal, P. and Robin, V. (2022) Markovian online matching algorithms on large bipartite random graphs, Methodology and Computing in Applied Probability 24, 3195–3225.
  
• [26] Moyal, P. and Perry O. (2022) Many-server limits for service systems with dependent service and patience times , Queueing Systems: Theory and Applications 100, 337-339.
• [25] Mairesse, J. and Moyal, P. Moyal, (2022) New frontiers for stochastic matching, Queueing Systems: Theory and Applications 100, 473-475.
• [24] Su, R., Riahi Sfar, A., Natalizio, E., Moyal, P. and Song, Y.Q. (2022) Ensure trustworthiness in IoIT/AIoT: a phase-based approach, IEEE Internet of Things magazine 5(2), 84-88,
• [23] Moyal, P. and Perry, O. (2022) Stability of parallel server systems, Operations Research 70(4), 2456-2476.
• [22] Begeot, J., Marcovici, I., Moyal, P. and Rahme, Y. (2021) A general stochastic matching model on multigraphs, ALEA 18, 1-27.
• [21] Rahme, Y. and Moyal, P. (2021) A stochastic matching model on hypergraphs, Advances in Applied Probability 53(4), 951-980.
• [20] Moyal, P., Busic, A. and Mairesse, J. (2021) A product form for the general stochastic matching model, Journal of Applied Probability 58(2), 449-468.
• [19] Besançon, E., Decreusefond, L. and Moyal, P. (2020) Stein’s method for diffusive limits of queueing processes , Queueing systems: Theory and Applications 95(3-4), 173-201.
• [18] Moyal, P. (2019) Coupling in the queue with impatience: case of several servers, Discrete Events Dynamic Systems 29(2), 145-162.
• [17] Sfar, A. R., Natalizio, E., Moyal, P., Challal, Y., Chtourou, Z. (2019) “A game theoretic approach for privacy preserving model in IoT-based commercial transportation”, IEEE Transactions on Intelligent Transportation Systems 20(12), 4405-4414.
• [16] Moyal, P. and Perry, O. (2017) On the instability of matching queues, Annals of Applied Probability 27(6), 3385-3434.
• [15] Moyal, P. (2017) A pathwise comparison of parallel queues, Discrete Events Dynamic Systems 27, 573-584,
• [14] Bermolen, P., Jonckheere, M. and Moyal, P. (2017) The Jamming constant of uniform random graphs, Stochastic Processes and their Applications 127(7), 2138-2178,
• [13] Moyal, P. (2017) On the stability of a class of non-monotonic systems of parallel queues, Discrete Events Dynamic Systems 27(1), 85-107,
• [12] Mairesse, J. and Moyal, P. (2016) Stability of the stochastic matching model, Journal of Applied Probability 53(4), 1064-1077,
• [11] Bermolen, P., Jonckheere, M., Larroca, F. and Moyal, P. (2016) Estimating the Transmission Probability in Wireless Networks with Configuration Models, ACM Transactions on Modeling and Performance Evaluation of Computing Systems, 1(2), Art.9,
• [10] Moyal, P. (2015) A generalized backwards scheme for solving non monotonic stochastic recursions, Annals of Applied Probability 25(2), 582-599,
• [9] Moyal, P. (2013) On queues with impatience: stability, and the optimality of Earliest Deadline First, Queueing Systems: Theory and Applications 75(2-4), 211-242,
• [8] Decreusefond, L., Dhersin, J.S., Moyal, P. and Tran, V.C. (2012) Large graph limit for an SIR process in random network with heterogeneous connectivity, Annals of Applied Probability 22(2), 541-575,
• [7] Berczes, T., Georgiadis, S., Limnios, N., Moyal, P., Orosz, P. and Sztrik, J. (2012). “Tool supported modeling of sensor communication networks by using finite-source priority retrial queues”, Carpathian Journal of Electronic and Computer Engineering 5, 13-18,
• [6] Moyal, P. (2010) The queue with Impatience: Construction of the Stationary Workload under FIFO, Journal of Applied Probability 47(2), 498-512, pdf
• [5] Decreusefond, L. and Moyal, P. (2008) A Functional Central Limit Theorem for the M/GI/infinity queue, Annals of Applied Probability 18(6), 2156-2178, pdf
• [4] Moyal, P. (2008) Stability of a processor sharing queue with varying throughput, Journal of Applied Probability 45(4), 953-962, pdf
• [3] Decreusefond, L. and Moyal, P. (2008) Fluid limit of a heavily loaded EDF queue with impatient customers, Markov Processes and Related fields 14, 131-158,
• [2] Moyal, P. (2008) Convex comparison of service disciplines in real time queues, Operation Research Letters, 36(4), 496-499, pdf
• [1] Moyal, P. (2007) Stationarity of measure-valued stochastic recursions. Applications to the pure delay system and the SRPT queue, C. R. Acad. Sci. Paris, Ser 1 345, 233-237.pdf

Refereed Proceedings

• [5] Su, R., Sfar, A. R., Natalizio, E., Moyal, P. and Song, Y. Q. (2023). “A Game Theoretical Model addressing Misbehavior in Crowdsourcing IoT”. 20th IEEE International Conference on Sensing, Communication, and Networking (SECON 2023): 195–203,
• [4] Su, R., Riahi Sfar, A., Natalizio, E., Moyal, P. and Song, Y.Q. (2021). “PDTM: Phase-based dynamic trust management for Internet of things.” IEEE Proceedings ICCN 2021: 1-7,
• [3] Geogiadis, S., Moyal, P. Berczes, T. and Sztrik, J. (2013). A Fluid Limit for the Engset Model – Applications to retrial queues, Proceedings ICORES 2013 315-320,
• [2] Decreusefond, L. and Moyal, P. (2005). Fluid limit of the M/M/1+GI-EDF queue, IEEE Proceedings SAINT’05: 248-251,
• [1] Decreusefond, L. and Moyal, P. (2003). Elements for the Study of Stability and Performances in Real-Time Queues, IEEE Proceedings ICT’03: 1124-1132.