Aim and Scope

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (ToMPECS) is a quarterly peer-reviewed journal that publishes refereed articles on all aspects of the modeling, analysis, and performance evaluation of computing and communication systems. It solicits and will publish articles that:

    Define, develop, and assess new performance evaluation methodologies, including analytical techniques, experimental design, formal methods, instrumentation techniques, mathematical modeling, optimization, queueing theory, reliability analysis, simulation, statistical analysis, stochastic modeling, verification and validation, and workload characterization;

    Provide new insights on the performance of computing and communication systems; or

    Introduce new settings within which performance modeling and evaluation can play an important role.

Target areas for these performance evaluation methodologies include traditional areas such as computer architecture, computer networks, database systems, distributed systems, enterprise systems, fault-tolerant systems, file and I/O systems, memory systems, multimedia systems, operating systems, peer-to-peer networks, real-time systems, sensor networks, software systems, storage systems, telecommunication networks, Web-based systems, and wireless networks, as well as up and coming areas such as data centers, green computing and communications, energy grid networks, on-line social networks, and networks at large.

The scope of papers published in TOMACS includes, but is not limited to, the following general areas:

Modeling Methodology: modeling languages, model reuse, component-based approaches, agent-based approaches, multi-formalism modeling, hierarchical, multi-level modeling, meta modeling and visual modeling, composition and refinement of models, hybrid modeling.

Model Execution: development and analysis of algorithms and data structures, approximative algorithms, hybrid algorithms, parallel algorithms, including GPU based approaches, distributed simulation, grid-based and cloud-based execution, inter-operation of simulation systems, distributed simulations for training, test and evaluation purposes, data driven simulation.

Random numbers and objects: random number generators and testing, low-discrepancy sequences, random variate transformations, stochastic process and random object generators, statistical distribution fitting and data modeling.

Experiment design and simulation analysis: analysis of the stochastic nature of simulation output and algorithms, including rare event simulation, simulation-based optimization and search, sensitivity analysis, variance reduction techniques and Markov chain Monte Carlo approaches.

Verification, validation, and accreditation of models: detailed studies, workflow-based support, addressing questions of provenance, statistical model checking, reproducibility of simulation results

Interplay between other areas of computer science and simulation: simulation for decision support, workflows, artificial intelligence, virtual reality, big data, service-oriented approaches, grid-computing, visual analytics, probabilistic programming.

Advanced Applications: Novel techniques and tools for simulating specific complex systems such as those arising in communication networks, computer science, cyber physical systems, health care, manufacturing, social science, systems biology, systems medicine, transportation systems.

More information on ACM publications can be found at this ACM web site, including policies on copyrights.