Methods of analytical and stochastic modelling are widely used in engineering to assess and design various complex systems, like computer and communication networks, and manufacturing systems. The ASMTA conference is a main forum for advancing these techniques and their applications and aims to bring together researchers of academia and industry to discuss the latest developments in analytical, numerical and simulation algorithms for stochastic systems.

This year, the conference will be held as a workshop within IFIP WG 7.3 Performance 2026 in Ghent, Belgium.

ASMTA 2026 seeks both methodological papers that propose novel analytical and numerical solution techniques for stochastic systems, as well as application-oriented papers that apply stochastic modelling techniques to practical performance problems. The website for ASMTA 2026 will be at https://asmta.github.io. Submissions will be on Microsoft CMT at https://cmt3.research.microsoft.com/ASMTA2026

The proceedings of ASMTA 2026 will be published in the Springer Lecture Notes in Computer Science (LNCS) series. Submissions may already be prepared in LNCS format and must not exceed 15 pages, including figures, tables, and references; see the information for authors on Springer as web site for formatting instructions (Springer).

A selection of the best papers will be invited to submit a fast-tracked extended version of the work to the Performance Evaluation (PEVA) journal.

Important Dates

Paper submission deadline: August 28, 2026 (Extended, FIRM)
Notification of acceptance: September 11, 2026
Organisation

TPC Chairs:

Illés Horváth Budapest University of Technology and Economics, Hungary
Vincenzo Mancuso, University of Palermo, Italy & IMDEA Networks Institute, Madrid, Spain
Scope and Topics

ASMTA 2026 seeks both methodological papers that propose novel analytical and numerical solution techniques for stochastic systems, as well as application-oriented papers that apply stochastic modelling techniques to practical performance problems. Topics of interest include the following.

Performance-Oriented Methodologies:

Markov Processes
Queueing Systems and Networks
Capacity Planning, Resource Allocation, Routing, Scheduling and Quality of Service
Branching Processes and Epidemic Models
Game Theory and Stochastic Games
Reliability Theory
(Computationally Intensive) Statistical Methods
Stochastic Control, Decision Processes and Optimisation
Rare Events and Stochastic Simulation
Approximations, Bounds and Limits of Stochastic Models
Reinforcement Learning Techniques for Dynamic Resource Allocation
Fluid and Diffusion Limits
Random Graphs
Envisaged Application Areas:

Complex Systems
Computer and Information Systems
Workflow Management Systems
Communication Systems and Networks
Wireless and Mobile Systems and Networks
Peer-to-Peer Applications and Services
Embedded Systems and Sensor Networks
Storage Systems, Data Centres, Content Delivery, Cloud/Fog/Edge
Workload Modelling and Characterisation
Road Traffic and Transportation
Social Networks
Modelling of Virtualisation
Energy-Aware Optimisation
Stochastic Modelling for Systems Biology
Biologically Inspired Network Design
Artificial Intelligence and Machine Learning Platforms
Blockchains and Crypto-Currency
Network Economics and Platform Designs
Matching Systems and Sharing Economy
Submission

Submissions will be on Microsoft CMT at https://cmt3.research.microsoft.com/ASMTA2026

The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.