@proceedings {Distefano201377,
	title = {Investigating mobile crowdsensing application performance},
	journal = {Proceedings of the 3rd ACM International Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications (DIVANet), Co-located with the 16th ACM Int. Conf. on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM)},
	year = {2013},
	note = {cited By 0; Conference of 3rd ACM Int. Symp. on Design and Analysis of Intelligent Vehicular Networks and Applications, DIVANet 2013, Held in Conjunction with the 16th ACM Int. Conf. on Modeling, Analysis and Simulation of Wireless and Mobile Systems, MSWiM 2013 ; Conference Date: 3 November 2013 Through 8 November 2013; Conference Code:101342},
	pages = {77-83},
	publisher = {ACM},
	address = {Barcelona, Spain, 3-8 November 2013},
	abstract = {<p>Mobile Crowdsensing (MCS) is an emerging distributed paradigm lying at the intersection between the Internet of Things and the volunteer/crowd-based approach. MCS applications are usually deployed on contributing nodes such as smart devices and mobiles, equipped by sensing resources that sample the physical environment and provide the sensed data, once filtered, aggregated and preprocessed, to the MCS application server. The MCS opportunistic approach unlocks new form of pervasive, participatory sensing applications, acquiring interests also in business contexts that call for adequate techniques and tools to drive architects and developers in MCS application design. Aim of this paper is to evaluate the performance of an MCS application though a stochastic model able to stochastically represent the overall MCS environment, thus providing a valid support to MCS application development. The Petri nets formalism is used due to its expressiveness and the capabilities to represent complex, dependent, non-Markovian, phenomena usually characterizing MCS environments. A specific MCS application is then evaluated to demonstrate the effectiveness of the proposed technique on a real case study. {\textcopyright} 2013 ACM.</p>
},
	keywords = {Application development, Application performance, Complex networks, crowdsensing, Design, Digital storage, Internet of Things (IOT), Participatory sensing applications, Performance, Petri nets, Physical environments, Stochastic models, Techniques and tools},
	isbn = {9781450323581},
	doi = {10.1145/2512921.2512931},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84889685098\&partnerID=40\&md5=15df22b992482173437dcd8080bbbc94},
	author = {Salvatore Distefano and Francesco Longo and Marco Scarpa}
}
@proceedings {Distefano2013385,
	title = {Quantitative dependability assessment of distributed systems subject to variable conditions},
	journal = {6th International Conference on Internet and Distributed Computing Systems (IDCS)},
	volume = {8223 Lecture Notes in Computer Science},
	year = {2013},
	note = {cited By 1; Conference of 6th International Conference on Internet and Distributed Computing Systems, IDCS 2013 ; Conference Date: 28 October 2013 Through 30 October 2013; Conference Code:102547},
	pages = {385-398},
	publisher = {Springer-Verlag},
	address = {Hangzhou, China, 28-30 October 2013},
	abstract = {<p>Dependability evaluation plays a key role in the design of a broad range of systems, where related properties have to be carefully analyzed in order to meet the requirements. This is particularly challenging in distributed contexts, where several entities may interact influencing each other. In this paper, we present an analytical framework that allows the study of a class of phenomena where different working conditions alternate, changing the stochastic behavior of the system. The proposed solution technique, based on phase type distributions and on ad-hoc fitting algorithms, can be applied in dependability evaluation of a wide class of distributed systems. Examples are provided to show the usefulness and the applicability of the framework, characterizing and investigating different dependability aspects of two distributed computing systems, i.e., connection-oriented networks and Internet of Things. {\textcopyright} Springer-Verlag 2013.</p>
},
	keywords = {Artificial intelligence, Computer science, Computers, Dependability assessments, Dependability evaluation, Distributed computing systems, Internet, Internet of Things (IOT), phase type distributions, Solution techniques, Stochastic behavior, Variable conditions},
	isbn = {9783642414275},
	issn = {03029743},
	doi = {10.1007/978-3-642-41428-2_31},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84893743730\&partnerID=40\&md5=8ebf6bc7152dd9f2734b969030b62365},
	author = {Salvatore Distefano and Dario Bruneo and Francesco Longo and Marco Scarpa}
}
