Marking dependency in non-Markovian stochastic Petri nets

作者：Distefano Salvatore; Longo Francesco^*; Scarpa Marco

来源：Performance Evaluation, 2017, 110: 22-47.

DOI：10.1016/j.peva.2017.03.001

• Marking dependency
• Non-Markovian stochastic Petri nets
• Phase type distributions
• Kronecker algebra
• Power management
• Multi-core CPUs

Marking dependency is a powerful tool that allows different firing time distributions to be associated with a stochastic Petri net transition, depending on the marking. Through this feature, the modeler can easily and compactly represent advanced properties and behaviors of the system. While a semantics and specific solution techniques have been provided for generalized stochastic Petri nets thus covering homogeneous Markovian aspects, in the non-homogeneous/non-Markovian case marking dependency still needs to be investigated. To fill this gap, this paper provides a formalization of marking dependent semantics in non-Markovian stochastic Petri nets (NMSPNs) and a solution technique, based on phase type distributions and Kronecker algebra, able to deal with such a feature allowing both transient and steady-state analyses. To motivate the actual need of marking dependency in NMSPN modeling and to demonstrate the potential of such a feature as well as the validity of the proposed solution technique a case study on a multi-core CPU system with power management facilities is explored.

• 出版日期2017-4