Probabilistic self-stabilization
Information Processing Letters
Randomized algorithms
Memory space requirements for self-stabilizing leader election protocols
Proceedings of the eighteenth annual ACM symposium on Principles of distributed computing
Self-stabilization
Self-stabilizing systems in spite of distributed control
Communications of the ACM
Proceedings of the 17th Conference on Foundations of Software Technology and Theoretical Computer Science
Lectures on Petri Nets I: Basic Models, Advances in Petri Nets, the volumes are based on the Advanced Course on Petri Nets
PRISM: Probabilistic Symbolic Model Checker
TOOLS '02 Proceedings of the 12th International Conference on Computer Performance Evaluation, Modelling Techniques and Tools
Local and global properties in networks of processors (Extended Abstract)
STOC '80 Proceedings of the twelfth annual ACM symposium on Theory of computing
Service Time Optimal Self-Stabilizing Token Circulation Protocol on Anonymous Unidrectional Rings
SRDS '02 Proceedings of the 21st IEEE Symposium on Reliable Distributed Systems
Genetic Programming and Model Checking: Synthesizing New Mutual Exclusion Algorithms
ATVA '08 Proceedings of the 6th International Symposium on Automated Technology for Verification and Analysis
A systematic review of search-based testing for non-functional system properties
Information and Software Technology
Genetic programming with fitness based on model checking
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Model checking-based genetic programming with an application to mutual exclusion
TACAS'08/ETAPS'08 Proceedings of the Theory and practice of software, 14th international conference on Tools and algorithms for the construction and analysis of systems
Synthesizing solutions to the leader election problem using model checking and genetic programming
HVC'09 Proceedings of the 5th international Haifa verification conference on Hardware and software: verification and testing
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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Randomised algorithms traditionally make stochastic decisions based on the result of sampling from a uniform probability distribution, such as the toss of a fair coin. In this paper, we relax this constraint, and investigate the potential benefits of allowing randomised algorithms to use non-uniform probability distributions. We show that the choice of probability distribution influences the non-functional properties of such algorithms, providing an avenue of optimisation to satisfy non-functional requirements. We use Multi-Objective Optimisation techniques in conjunction with Genetic Algorithms to investigate the possibility of trading-off non-functional properties, by searching the space of probability distributions. Using a randomised self-stabilising token circulation algorithm as a case study, we show that it is possible to find solutions that result in Pareto-optimal trade-offs between non-functional properties, such as self-stabilisation time, service time, and fairness.