Research

At the intersection of applied mathematics, computer science, and engineering, I'm interested in the broad field of decision making under uncertainty. My research leverages methods from applied probability and operations research to develop highly scalable algorithms that reduce congestion and operational costs in large-scale distributed systems. I use Markov processes to model the dynamics of cloud networks, focusing on analyzing delays and power consumption in practically relevant limiting regimes.

Keywords: queueing theory, reinforcement learning, Markov decision processes, load balancing, auto-scaling, power consumption minimization, cloud systems.

Selected recent publications

1. J. Anselmi Asynchronous Load Balancing and Auto-scaling: Mean-field Limit and Optimal Design, IEEE/ACM Transactions on Networking, vol. 32, no. 4, pp. 2960-2971, Aug. 2024
   
2. J. Anselmi, B. Gaujal, L.S. Rebuffi Reinforcement Learning in a Birth and Death Process: Breaking the Dependence on the State Space , NeurIPS '22: Proceedings of the 36th International Conference on Neural Information Processing Systems, 2022
   
3. J. Anselmi, N. Walton Stability and Optimization of Speculative Queueing Networks, IEEE/ACM Transactions on Networking, vol. 30, no. 2, pp. 911-922, April 2022
   
4. J. Anselmi, F. Dufour Power-of-d-Choices with Memory: Fluid Limit and Optimality, Mathematics of Operations Research, 45, 3, 862-888, 2020
   
5. J. Anselmi Combining Size-Based Load Balancing with Round-Robin for Scalable Low Latency, IEEE Transactions on Parallel and Distributed Systems, vol. 31, no. 4, pp. 886-896, 2020

Students

A PhD position is available on the themes of i) reinforcement learning in structured Markov decision processes and ii) load balancing and autoscaling. If you are a student interested in the broad field of decision making under uncertainty, with a solid background in computer science or applied math, please contact me.

PhD students:
- Louis-Sebastien Rebuffi (with B. Gaujal). Subject: "Reinforcement Learning Algorithms for Controlled Queueing Systems" [thesis defended on December 2023].

Interns:
[Reinforcement learning] Abednego Kambale [01-07/2025], Bel Houari-Durand Sehane [02-08/2024]
[Auto-scaling and load balancing] Jules BURGAT [02-08/2023], Mingming DAI [02-08/2023], Dorian BUFFIÈRE [03-09/2022]
[Power consumption minimization] Karl Gottlieb [02-08/2025]

Publications

My publications on [Google scholar] [hal.science] [dblp.org]

Submitted

1. J. Anselmi, B. Gaujal, L.S. Rebuffi Non-Stationary Gradient Descent for Optimal Auto-Scaling in Serverless Platforms
   

Refereed journal papers

1. J. Anselmi, J. Doncel Balanced Splitting: A Framework for Achieving Zero-wait in the Multiserver-job Model, IEEE Transactions on Parallel and Distributed Systems (to appear)
   
2. J. Anselmi Asynchronous Load Balancing and Auto-scaling: Mean-field Limit and Optimal Design, IEEE/ACM Transactions on Networking, vol. 32, no. 4, pp. 2960-2971, Aug. 2024
   
3. J. Anselmi, B. Gaujal, L.S. Rebuffi Learning Optimal Admission Control in Partially Observable Queueing Networks, Queueing Systems, 108, 31-79, 2024
   
4. J. Anselmi, J. Doncel Load Balancing with Job-Size Testing: Performance Improvement or Degradation?, ACM Transactions on Modeling and Performance Evaluation of Computing Systems, 9, 2, Article 8, 2024, 27 pages.
   
5. F. Filippini, J. Anselmi, D. Ardagna, B Gaujal A Stochastic Approach for Scheduling AI Training Jobs in GPU-based Systems , IEEE Transactions on Cloud Computing, vol. 12, no. 01, pp. 53-69, 2024.
6. J. Anselmi, N. Walton Stability and Optimization of Speculative Queueing Networks, IEEE/ACM Transactions on Networking, vol. 30, no. 2, pp. 911-922, April 2022.
7. J. Anselmi Replication vs speculation for load balancing, Queueing Systems, 100, 389–391 (2022).
8. J. Anselmi, B. Gaujal, L.S. Rebuffi Optimal Speed Profile of a DVFS Processor under Soft Deadlines, Performance Evaluation, Vol. 152, 2021, 102245 (also accepted at IFIP Performance '21) [video]
9. J. Anselmi, F. Dufour Power-of-d-Choices with Memory: Fluid Limit and Optimality, Mathematics of Operations Research, 45, 3, 862-888, 2020.
10. J. Anselmi Combining Size-Based Load Balancing with Round-Robin for Scalable Low Latency, IEEE Transactions on Parallel and Distributed Systems, vol. 31, no. 4, pp. 886-896, 2020
11. J. Anselmi, J. Doncel Asymptotically Optimal Size-Interval Task Assignments, IEEE Transactions on Parallel and Distributed Systems, vol. 30, no. 11, pp. 2422-2433, 2019
12. J. Anselmi, F. Dufour, T. Prieto-Rumeau Computable approximations for average Markov decision processes in continuous-time, Journal of Applied Probability, 55(2), 571-592, 2018
13. J. Anselmi Asymptotically optimal open-loop load balancing, Queueing Systems, Vol. 87, 3-4, pp. 245-267, 2017
14. J. Anselmi, D. Ardagna, J. C.S. Lui, A. Wierman, Y. Xu, Z. Yang The economics of the cloud: price competition and congestion, ACM Transactions on Modeling and Performance Evaluation of Computing Systems, Vol. 2, 4 (18), 2017
15. J. Anselmi, F. Dufour, T. Prieto-Rumeau Computable approximations for continuous-time Markov decision processes on Borel spaces based on empirical measures, Journal of Mathematical Analysis and Applications, 443 (2), 1323–1361, 2016
16. J. Anselmi, N.S. Walton Decentralized Proportional Load Balancing, SIAM Journal on Applied Mathematics, 76(1), 391-410, 2016
17. J. Anselmi, B. Gaujal, T. Nesti Control of parallel non-observable queues: asymptotic equivalence and optimality of periodic policies, Stochastic Systems, Vol. 5 No. 1, (2015), 120-145
18. M. Passacantando, J. Anselmi, D. Ardagna Generalized Nash Equilibria for Platform-as-a-Service Clouds, European Journal of Operational Research, 236(1):326-339, 2014
19. J. Anselmi, B. Gaujal Efficiency of simulation in monotone hyper-stable queueing networks, Queueing Systems, 76(1):51-72, 2014
20. J. Anselmi, B. D'Auria, N. Walton Closed queueing networks under congestion: non-bottleneck independence and bottleneck convergence, Mathematics of Operations Research, 38:3, 469-491, 2013
21. J. Anselmi, G. Casale Heavy-Traffic Revenue Maximization in Parallel Multiclass Queues, Perform. Eval., 70(10): 806-821 (2013)
22. T. Radivojevic, J. Anselmi, E. Scalas Ergodic transition in a simple model of the continuous double auction Plos one 9(2): e88095.
23. J. Anselmi, B. Gaujal The 'Price of Forgetting' in parallel and non-observable queues, Perform. Eval., 68(12): 1291-1311 (2011)
24. J. Anselmi, U. Ayesta, A. Wierman Competition yields efficiency in load balancing games, Perform. Eval., 68(11): 986-1001 (2011)
25. J. Anselmi, I.M. Verloop Energy-aware capacity scaling in virtualized environments with performance guarantees, Perform. Eval., 68(11): 1207-1221 (2011)
26. J. Anselmi, P. Cremonesi A unified framework for the bottleneck analysis of multiclass queueing networks, Perform. Eval., 67(4): 218-234 (2010)
27. J. Anselmi, Y. Lu, M. Sharma, M. S. Squillante Improved approximations for the Erlang loss model, Queueing Systems, 63(1-4): 217-239 (2009)

Refereed conference papers

1. J. Anselmi, B. Gaujal, L.S. Rebuffi Reinforcement Learning in a Birth and Death Process: Breaking the Dependence on the State Space , NeurIPS '22: Proceedings of the 36th International Conference on Neural Information Processing Systems, 2022.
2. J. Anselmi, B. Gaujal Energy Optimal Activation of Processors for the Execution of a Single Task with Unknown Size, IEEE MASCOTS 2022, 30th International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, October 18-20, 2022 Nice, France
   Best Paper Award
3. H. Zhang, F. Dufour, J. Anselmi, D. Laneuville, A. Nègre Piecewise Optimal Trajectories of Observer for Bearings-Only Tracking of Maneuvering Target, 2018 IEEE Aerospace Conference, 2018, pp. 1-7
4. H. Zhang, F. Dufour, J. Anselmi, D. Laneuville, A. Nègre Piecewise Optimal Trajectories of Observer for Bearings-Only Tracking by Quantization, 20th International Conference on Information Fusion (Fusion), 2017, pp. 1-7
5. J. Anselmi, B. D'Auria, N. Walton A Processor-Sharing Heuristic for Multipath Congestion Control, Proc. of the 51st Annual Allerton Conference on Communication, Control, and Computing, 2013, pp. 1-9
6. J. Anselmi, B. Gaujal Optimal Routing in Parallel, non-Observable Queues and the Price of Anarchy Revisited, 22nd International Teletraffic Congress, ITC-22, IEEE, 2010
7. J. Anselmi, B. Gaujal Performance Evaluation of a Work Stealing Algorithm for Streaming Applications, 13th Int. Conf. On Principle Of DIstributed Systems (OPODIS), 2009, Springer LNCS, Vol. 5923/2009, pp. 18-32.
8. J. Anselmi, E. Amaldi, P. Cremonesi On the Consolidation of Data-centers with Performance Constraints, 5th Int. Conf. on the Quality of Software Architectures (QoSA), 2009, Springer LNCS, Vol. 5581/2009, pp. 163-176.
9. J. Anselmi A New Framework Supporting the Bottleneck Analysis of Multiclass Queueing Networks, ACM VALUETOOLS 08: Third Int. Conf. on Performance Evaluation Methodologies and Tools, October 20-24, 2008, Athens, Greece.
   
10. J. Anselmi, P. Cremonesi Bounding the Performance of BCMP Networks with Load-Dependent Stations, IEEE MASCOTS 2008, 16th Annual Meeting of the IEEE Int. Symp. on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, Baltimore, Maryland, USA, 8-10 September 2008.
11. J. Anselmi, P. Cremonesi Exact Asymptotic Analysis of Closed BCMP Networks with a Common Bottleneck, ASMTA'08: The 15th Int. Conf. on Analytical and Stochastic Modelling Techniques and Applications, Springer LNCS, Nicosia, Cyprus, 4-6 June 2008
12. J. Anselmi, E. Amaldi, P. Cremonesi Service Consolidation with End-to-End Response Time Constraints, SEAA'08: Euromicro Conference on Service Engineering and Advanced Applications, Italy, IEEE, Parma, 3-5 September 2008
13. J. Anselmi, G. Casale, P. Cremonesi Approximate Solution of Multiclass Queueing Networks with Region Constraints, IEEE MASCOTS 2007, 15th IEEE Int. Symp. on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, Istanbul, Turkey, October 2007.

Additional Publications: Workshop Papers, Technical Reports, and Other Contributions

1. J. Anselmi, J. Doncel Dispatching and scheduling multiserver jobs for throughput optimality, Perform. Eval. Rev. (to appear)
2. J. Anselmi, D. Ardagna, J. C.S. Lui, A. Wierman, Y. Xu, Z. Yang The economics of the cloud: price competition and congestion, SIGecom Exchanges 13(1): 58-63 (2014). Also appeared in: SIGMETRICS Performance Evaluation Review 41(4): 47-49 (2014)
3. M. Larrañaga, J. Anselmi, U. Ayesta, P. Jacko, A. Romo Optimization techniques applied to railway systems, HAL technical report, 2013
4. J. Anselmi, B. Gaujal On the efficiency of perfect simulation in monotone queueing networks, Perform. Eval. Rev., Vol. 39, No. 2, pp. 56-58, 2011 [extended version]
5. J. Anselmi, B. Gaujal The Price of Anarchy in Parallel Queues Revisited, Proc. of ACM SIGMETRICS 2010, pp. 353-354. Poster presentation.
6. J. Anselmi, Y. Lu, M. Sharma, M. S. Squillante Improved approximations for stochastic loss networks, Perform. Eval. Rev., Vol. 37, No. 2, pp. 45-47, 2009.
7. J. Anselmi, P. Cremonesi Bounding the Partition Function of BCMP Multiclass Queueing Networks BWWQT'09: Belarusian Winter Workshop on Queueing Theory, Minsk, Belarus, January 2009 [slides]
8. J. Anselmi, G. Casale, P. Cremonesi A Population-Mix Driven Approximation for Queueing Networks with Finite Capacity Regions, BWWQT'07: Belarusian Winter Workshop on Queueing Theory, Grodno, Belarus, January 2007 [extended version]
9. J. Anselmi, D. Ardagna, P. Cremonesi A QoS-Based Selection Approach of Autonomic Grid Services, HPDC/SOCP '07: ACM Proc. of the 2007 workshop on Service-oriented computing performance: aspects, issues, and approaches, Monterey, CA, USA, 2007.

Teaching

1. Probabilités et simulation ‐ PolyTech Grenoble, INFO4
2. Évaluation de performances ‐ PolyTech Grenoble, INFO4

If you're a student, you may find the R code snippets written in class or for homework useful.