@proceedings {Bruneo2017,
	title = {Head in a Cloud: An approach for Arduino YUN virtualization},
	journal = {GIoTS 2017 - Global Internet of Things Summit, Proceedings},
	year = {2017},
	note = {cited By 0; Conference of 2017 Global Internet of Things Summit, GIoTS 2017 ; Conference Date: 6 June 2017 Through 9 June 2017; Conference Code:130055},
	publisher = {Institute of Electrical and Electronics Engineers Inc.},
	address = {Geneva; Switzerland; 6-9 June 2017},
	abstract = {<p>Smart boards are triggering the IoT revolution, allowing to make common objects and things smart through their network, storage and processing capabilities. Arduino boards have a prominent role in this revolution, due to their customizability and programming freedom. From a different perspective, another strategic development for the IoT is towards Cloud, allowing to properly manage things and data ubiquitously, on demand, as services. Pushing in this direction, we can pave the way to the Cloud of Things, where real things, rather than the data they produce, can be provided to third parties, by adopting a {\textquoteright}device-centric{\textquoteright} approach. To this purpose, virtualization of physical resources becomes an essential step and core mechanism. In this paper we focus on smart board virtualization, implementing a flexible solution for Arduino boards based on Stack4Things, allowing to create, multiplex, migrate and deploy virtual boards in IoT-Cloud contexts. The results obtained by a preliminary implementation and experiments on the $\#$SmartME testbed are shown in the paper to demonstrate the feasibility and the effectiveness of the proposed solution. {\textcopyright} 2017 IEEE.</p>
},
	keywords = {Arduino YUN, Clouds, Computer operating systems, Core mechanisms, Customizability, Digital storage, GPIO pins, Internet of Things, Physical resources, Processing capability, Stack4Things, Strategic development, Virtual reality, Virtualization},
	isbn = {9781509058730},
	doi = {10.1109/GIOTS.2017.8016263},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029291785\&doi=10.1109\%2fGIOTS.2017.8016263\&partnerID=40\&md5=4a8eed3e1348ab91166e648151d625c0},
	author = {Dario Bruneo and Salvatore Distefano and Francesco Longo and Giovanni Merlino and Antonio Puliafito and Angelo Zaia}
}
@proceedings {Distefano2014255,
	title = {Non-Markovian modeling of a BladeCenter chassis midplane},
	journal = {Proceedings of the 11th European Workshop on Computer Performance Engineering (EPEW)},
	volume = {8721 Lecture Notes in Computer Science},
	year = {2014},
	note = {cited By 0; Conference of 11th European Workshop on Computer Performance Engineering, EPEW 2014 ; Conference Date: 11 September 2014 Through 12 September 2014; Conference Code:107431},
	pages = {255-269},
	publisher = {Springer Verlag},
	address = {Florence, Italy, 11-12 September 2014},
	abstract = {<p>In distributed contexts such as Cloud computing, the reliability and availability of the provided resources and services have to be assured in order to meet user requirements. At the infrastructure level, this specification is translated into tighter ones on the datacenter hosting physical resources. In this paper, starting from a real case study of the IBM BladeCenter, we provide a technique for the quantitative evaluation of datacenter infrastructure availability. The proposed technique allows one to take into account both aging phenomena and multiple operating conditions. In particular, one subsystem of the BladeCenter, the chassis midplane, is studied. Indeed, based on the stochastic characterization of the midplane reliability through statistic measurements, a model dealing with the non-exponential failure time distribution thus obtained is evaluated to demonstrate the suitability and the effectiveness of the proposed technique. {\textcopyright} 2014 Springer International Publishing.</p>
},
	keywords = {Aging phenomena, Chassis, Failure-time distribution, Non-Markovian modeling, Operating condition, Physical resources, Quantitative evaluation, Reliability and availability, Stochastic models, Stochastic systems, User requirements},
	isbn = {9783319108841},
	issn = {03029743},
	doi = {10.1007/978-3-319-10885-8_18},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84906969232\&partnerID=40\&md5=6840d4a28b6ed80a602f4db06c10343b},
	author = {Salvatore Distefano and Francesco Longo and Marco Scarpa and Kishor S. Trivedi}
}
