@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}
}
@article {Distefano2015629,
	title = {QoS Assessment of Mobile Crowdsensing Services},
	journal = {Journal of Grid Computing},
	volume = {13},
	number = {4},
	year = {2015},
	note = {cited By 2},
	pages = {629-650},
	publisher = {Springer Netherlands},
	abstract = {<p>The wide spreading of smart devices drives to develop distributed applications of increasing complexity, attracting efforts from both research and business communities. Recently, a new volunteer contribution paradigm based on participatory and opportunistic sensing is affirming in the Internet of Things scenario: Mobile Crowdsensing (MCS). A typical MCS application considers smart devices as contributing sensors able to produce geolocalized data about the physical environment, then collected by a remote application server for processing. The growing interest on MCS allows to think about its possible exploitation in commercial context. This calls for adequate methods able to support MCS service providers in design choices, implementing mechanisms for the quality of service (QoS) assessment while dealing with complex time-dependent phenomena and churning issues due to contributors that unpredictably join and leave the MCS system. In this paper, we propose an analytical modeling framework based on stochastic Petri nets to evaluate QoS metrics of a class of MCS services. This method requires to extend the Petri net formalism by specifying a marking dependency semantics for non-exponentially distributed transitions. The approach is then applied to an MCS application example deriving some QoS measures that can drive quantitative evaluation and characterization of the {\textquotedblleft}crowd{\textquotedblright} behavior. {\textcopyright} 2015, Springer Science+Business Media Dordrecht.</p>
},
	keywords = {crowdsensing, Digital storage, Distributed applications, Marking dependency, Non-Markovian, Performability, Petri nets, Quality of service, Quality of service (QoS) assessments, Quantitative evaluation, Semantics, Stochastic systems, Time dependent phenomena},
	issn = {15707873},
	doi = {10.1007/s10723-015-9338-7},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84958155341\&doi=10.1007\%2fs10723-015-9338-7\&partnerID=40\&md5=3bd7e36a37ab06a3acabb37a21b90ab1},
	author = {Salvatore Distefano and Francesco Longo and Marco Scarpa}
}
