caa a22 4500 606244786 CHVBK 20210128101332.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s10723-015-9338-7 doi (NATIONALLICENCE)springer-10.1007/s10723-015-9338-7 QoS Assessment of Mobile Crowdsensing Services [Elektronische Daten] [Salvatore Distefano, Francesco Longo, Marco Scarpa] 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 "crowd” behavior. Springer Science+Business Media Dordrecht, 2015 Crowdsensing nationallicence QoS nationallicence performability nationallicence Non-Markovian phenomena nationallicence Petri nets nationallicence Marking dependency nationallicence Distefano Salvatore Social and Urban Computing Lab, Higher Institute of Information Technology and Information Systems (ITIS), Kazan Federal University, Kazan, Russia aut Longo Francesco Università degli Studi di Messina, Contrada di Dio, 98166, Messina, Italy aut Scarpa Marco Università degli Studi di Messina, Contrada di Dio, 98166, Messina, Italy aut Journal of Grid Computing Springer Netherlands 13/4(2015-12-01), 629-650 1570-7873 13:4<629 2015 13 10723 https://doi.org/10.1007/s10723-015-9338-7 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10723-015-9338-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Distefano Salvatore Social and Urban Computing Lab, Higher Institute of Information Technology and Information Systems (ITIS), Kazan Federal University, Kazan, Russia aut NATIONALLICENCE 700 1- Longo Francesco Università degli Studi di Messina, Contrada di Dio, 98166, Messina, Italy aut NATIONALLICENCE 700 1- Scarpa Marco Università degli Studi di Messina, Contrada di Dio, 98166, Messina, Italy aut NATIONALLICENCE 773 0- Journal of Grid Computing Springer Netherlands 13/4(2015-12-01), 629-650 1570-7873 13:4<629 2015 13 10723