@article {Distefano201722,
	title = {Marking dependency in non-Markovian stochastic Petri nets},
	journal = {Performance Evaluation},
	volume = {110},
	year = {2017},
	note = {cited By 0},
	pages = {22-47},
	publisher = {Elsevier B.V.},
	abstract = {<p>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. {\textcopyright} 2017 Elsevier B.V.</p>
},
	keywords = {Algebra, energy management, Kronecker algebra, Marking dependency, Multi-core cpus, non-Markovian stochastic Petri nets, Petri nets, phase type distributions, Power management, Program processors, Random access storage, Semantics, Stochastic systems},
	issn = {01665316},
	doi = {10.1016/j.peva.2017.03.001},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016027299\&doi=10.1016\%2fj.peva.2017.03.001\&partnerID=40\&md5=a00a4d3147bd499b5f8879d3573b4670},
	author = {Salvatore Distefano and Francesco Longo and Marco Scarpa}
}
