Self-organization is a feasible metaphor for dealing with the growing complexity of today's software systems. Self-organization makes desired global system's behavior appear as an emergent property from component local interactions. The corresponding dynamics is usually non-linear so that the adoption of stochastic simulation and probabilistic model checking becomes essential in the early design stage. In this paper, as a reference example, a possible application of such techniques is shown on a problem called collective sort, whose emergent properties were analyzed by relying on the PRISM probabilistic model checker.
Matteo Casadei, Mirko Viroli (2009). Using Probabilistic Model Checking and Simulation for Designing Self-Organizing Systems. NEW YORK : ACM [10.1145/1529282.1529747].
Using Probabilistic Model Checking and Simulation for Designing Self-Organizing Systems
CASADEI, MATTEO;VIROLI, MIRKO
2009
Abstract
Self-organization is a feasible metaphor for dealing with the growing complexity of today's software systems. Self-organization makes desired global system's behavior appear as an emergent property from component local interactions. The corresponding dynamics is usually non-linear so that the adoption of stochastic simulation and probabilistic model checking becomes essential in the early design stage. In this paper, as a reference example, a possible application of such techniques is shown on a problem called collective sort, whose emergent properties were analyzed by relying on the PRISM probabilistic model checker.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
