What is LINE?
LINE is an open source engine for system performance and reliability modeling based on queueing theory.
Main features
The tool offers a language to specify extended queueing networks and layered queueing networks together with analytical and simulation-based techniques for their solution.
Models are solved in LINE with either native algorithms (CTMC, fluid, simulation, MVA, ...) or via external solvers, such as JMT, LQNS, and BuTools. The tool output metrics include throughputs, utilizations, response times, queue-lengths, and state probabilities. Metrics can be averages or distribution/percentiles, either in steady-state or transient regime.
Download
LINE offers two releases. The source code allows users to program arbitrary models. The binary release relies on the royalty-free MATLAB compiler runtime and only accepts models in JMT or LQNS format.
- Source release (requires MATLAB version 2020a or later)
- Binary release (Docker image, MATLAB compiler runtime-based, no MATLAB license required)
Installation information is available in the README file.
Documentation
Documentation and the getting started examples can be found in the user manual and on the LINE wiki.
License
The LINE solver is copyrighted by Imperial College London, 2012-2020 and distributed under the BSD-3 license.
How to cite LINE
If you use LINE, please cite the following article:
- Giuliano Casale. Integrated Performance Evaluation of Extended Queueing Network Models with LINE. Proceedings of the 2020 Winter Simulation Conference, ACM Press, December 2020.
Acknowledgement
The development of LINE has been partially funded by the European Commission grants FP7-318484 (MODAClouds), H2020-644869 (DICE), H2020-825040 (RADON), and by the EPSRC grant EP/M009211/1 (OptiMAM).
Downloads
2.0.x (May 2019-Present)
Latest stable release: This version has been tested with MATLAB 2020b.Latest dev release source code:
git clone https://github.com/imperial-qore/line-solver.git line-solver
New features:- Major tool overhaul and refactoring, not backward compatible with 0.x.x and 1.0.x versions.
- New solver-agnostic modelling language to describe extended queueing networks and layered models.
- New engine featuring solvers for extended queueing networks (CTMC, MVA, SSA, JMT, FLUID) and layered queueing models (LQNS, LN).
- Automated import of models specified in JMT using JSIMgraph or JSIMwiz.
- New user manual, wiki, and examples.
1.0.0 (June 2016)
This version can be used with Palladio Bench and SPACE4Cloud.
Binaries and source code:- Windows 64 bits. Requires MATLAB MCR version 2013a.
- Linux 64 bits. Requires MATLAB MCR version 2013a.
- LINE now offers support for both synchronous and asynchronous calls. This is achieved by extending the transformation from LQN models to incorporate asynchronous calls, and by extending the analysis to differentiate how these two types of calls account for remote execution time.
- This version includes beta versions of solvers for two extended types of execution: simultaneous resource possession (SRP) and synchronous calls with blocking (SCP). These can be used at the script level.
- This version has undergone a naming revision, simplifying names of scripts.
Resources
This page lists useful resources such as publications and public presentations.
Papers
If you use LINE, consider citing the following publications:
- G. Casale. Integrated Performance Evaluation of Extended Queueing Network Models with LINE. Winter Simulation Conference, ACM Press, December 2020.
- G. Casale. Automated Multi-paradigm Analysis of Extended and Layered Queueing Models with LINE. ACM/SPEC ICPE, 2019.
- J. F. Pérez and G. Casale, LINE: Evaluating Software Applications in Unreliable Environments, IEEE Transactions on Reliability, 66(3), pp. 837 - 853, Sept 2017.
- C. Müller, P. Rygielski, S. Spinner and S. Kounev. Enabling Fluid Analysis for Queueing Petri Nets via Model Transformation. Intl. Workshop on Practical Applications of Stochastic Modelling (PASM), 2016.
- D. J. Dubois and G. Casale. OptiSpot: minimizing application deployment cost using spot cloud resources. IEEE CLOUD, 2016.
- R. Osman, J. F. Perez and G. Casale. Quantifying the Impact of Replication on the Quality-of-Service in Cloud Databases. IEEE Intl. Conference on Software Quality, Reliability, and Security (QRS), 2016.
- D. J. Dubois and G. Casale. OptiSpot: minimizing application deployment cost using spot cloud resources. Cluster Computing, 2016.
- J. F. Pérez and G. Casale, Assessing SLA compliance from Palladio component models, in Proceedings of the 2nd Workshop on Management of resources and services in Cloud and Sky computing (MICAS), IEEE Press, 2013. [IEEE Xplore]
Presentations
- This presentation provides an overview of LINE and its application to cloud applications: G. Casale. Quality-driven development of multi-cloud applications, July 2016.