Call for papers
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: July 24, 2026
- 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.