PRISM Home Page.
http://www.prismmodelchecker.org.
M. Arns, P. Buchholz & A. Panchenko (2010):
On the Numerical Analysis of Inhomogeneous Continuous-Time Markov Chains.
INFORMS Journal on Computing 22(3),
pp. 416–432,
doi:10.1287/ijoc.1090.0357.
A. Aziz, V. Singhal, F. Balarin, R. Brayton & A. Sangiovanni-Vincentelli (1996):
Verifying Continuous Time Markov Chains.
In: Proceedings of CAV96,
doi:10.1007/3-540-61474-5_75.
C. Baier, B.R. Haverkort, H. Hermanns & J.P. Katoen (2003):
Model-Checking Algorithms for Continuous-Time Markov Chains.
IEEE Trans. Software Eng. 29(6),
pp. 524–541,
doi:10.1109/TSE.2003.1205180.
M. Benaïm & J. Le Boudec (2008):
A Class of Mean Field Interaction Models for Computer and Communication Systems.
Performance Evaluation 65(11-12),
pp. 823–838,
doi:10.1016/j.peva.2008.03.005.
M. Benaïm & J.Y. Le Boudec (2011):
On Mean Field Convergence and Stationary Regime.
CoRR abs/1111.5710.
Available at http://arxiv.org/abs/1111.5710.
P. Billingsley (1979):
Probability and Measure.
John Wiley and Sons.
P. Billingsley (1999):
Convergence of Probability Measures, 2nd Edition.
Wiley,
doi:10.1002/9780470316962.
L. Bortolussi (2008):
On the Approximation of Stochastic Concurrent Constraint Programming by Master Equation.
In: Proceedings of QAPL,
pp. 163–180,
doi:10.1016/j.entcs.2008.11.025.
L. Bortolussi, V. Galpin & J. Hillston (2012):
Hybrid performance modelling of opportunistic networks.
In: Proceedings of QAPL 2012,
EPTCS 85,
pp. 106121,
doi:10.4204/EPTCS.85.8.
L. Bortolussi & J. Hillston (2012):
Fluid Model Checking.
In: Proceedings of CONCUR 2012,
doi:10.1007/978-3-642-32940-1_24.
L. Bortolussi & J. Hillston (2015):
Model Checking Single Agent Behaviour by Fluid Approximation.
Information and Computation 242,
pp. 183–226,
doi:10.1016/j.ic.2015.03.002.
L. Bortolussi, J. Hillston, D. Latella & M. Massink (2013):
Continuous Approximation of Collective Systems Behaviour: a Tutorial.
Perf. Eval. 70(5),
pp. 317–349,
doi:10.1016/j.peva.2013.01.001.
L. Bortolussi & R. Lanciani (2013):
Model Checking Markov Population Models by Central Limit Approximation.
In: Proceedings of QEST,
pp. 123–138,
doi:10.1007/978-3-642-40196-1_9.
E. Clarke, A. Peled & A. Grunberg (1999):
Model Checking.
MIT press.
R.W.R. Darling (2002):
Fluid Limits of Pure Jump Markov Processes: A Practical Guide.
arXiv.org.
R.W.R. Darling & J.R. Norris (2008):
Differential equation approximations for Markov chains.
Probability Surveys 5,
doi:10.1214/07-PS121.
N. Gast & B. Gaujal (2010):
A mean field model of work stealing in large-scale systems.
In: Proceedings of ACM SIGMETRICS 2010,
pp. 13–24.
Available at http://doi.acm.org/10.1145/1811039.1811042.
R. A. Hayden, J. T. Bradley & A. Clark (2013):
Performance Specification and Evaluation with Unified Stochastic Probes and Fluid Analysis.
IEEE Trans. Software Eng. 39(1),
pp. 97–118,
doi:10.1109/TSE.2012.1.
R.A. Howard (2007):
Dynamic Probabilistic Systems, Volume II.
Dover.
A. Kolesnichenko, A. Remke, P.T. de Boer & B.R. Haverkort (2011):
Comparison of the Mean-Field Approach and Simulation in a Peer-to-Peer Botnet Case Study.
In: Proceedings of EPEW,
pp. 133–147,
doi:10.1007/978-3-642-24749-1_11.
S. Krantz & P.R. Harold (2002):
A Primer of Real Analytic Functions (Second ed.).
Birkhäuser,
doi:10.1007/978-0-8176-8134-0.
T. G. Kurtz (1970):
Solutions of Ordinary Differential Equations as Limits of Pure Jump Markov Processes.
Journal of Applied Probability 7,
pp. 49–58,
doi:10.2307/3212147.
D. Latella, M. Loreti & M. Massink (2013):
On-the-fly Fast Mean-Field Model-Checking.
In: Proceedings of TGC,
pp. 297–314,
doi:10.1007/978-3-319-05119-2_17.
J.-Y. Le Boudec (2010):
Performance Evaluation of Computer and Communication Systems.
EPFL Press, Lausanne..
M. Massink, D. Latella, A. Bracciali, M. Harrison & J. Hillston (2012):
Scalable context-dependent analysis of emergency egress models.
Formal Aspects of Computing,
pp. 1–36,
doi:10.1007/s00165-011-0188-1.
H. Qian & E.L. Elson (2002):
Single-molecule enzymology: stochastic Michaelis-Menten kinetics.
Biophysical Chemistry 101,
pp. 565–576,
doi:10.1016/S0301-4622(02)00145-X.
J. Rutten, M. Kwiatkowska, G. Norman & D. Parker (2004):
Mathematical Techniques for Analyzing Concurrent and Probabilistic Systems.
CRM Monograph Series 23.
American Mathematical Society.
A. Stefanek, R. A. Hayden, M. Mac Gonagle & J. T. Bradley (2012):
Mean-Field Analysis of Markov Models with Reward Feedback.
In: Proceedings of ASMTA 2012,
pp. 193–211,
doi:10.1007/978-3-642-30782-9_14.
D.T.J. Sumpter (2000):
From Bee to Society: An Agent-based Investigation of Honey Bee Colonies.
University of Manchester.
Z. Szallasi, J. Stelling & V. Periwal (2012):
System Modeling in Cellular Biology, From Concepts to Nuts and Bolts.
MIT Press.
M. Tribastone, J. Ding, S. Gilmore & J. Hillston (2012):
Fluid Rewards for a Stochastic Process Algebra.
IEEE Trans. Software Eng. 38(4),
pp. 861–874,
doi:10.1109/TSE.2011.81.
N. G. Van Kampen (1992):
Stochastic Processes in Physics and Chemistry.
Elsevier.