@article {Distefano2017439, title = {Personalized Health Tracking with Edge Computing Technologies}, journal = {BioNanoScience}, volume = {7}, number = {2}, year = {2017}, note = {cited By 0}, pages = {439-441}, publisher = {Springer New York LLC}, abstract = {

The health monitoring component is the essential block, a pillar of several e-health systems. Plenty of health tracking applications and specific technologies such as smart devices, wearables, and data management systems are available. To be effective, promptly reacting to issues, a health monitoring service must ensure short delays in data sensing, collection, and processing activities. This is an open problem that distributed computing paradigms, such as Internet of Things (IoT), Cloud, and Edge computing, could address. The solution proposed in this paper is based on Stack4Things, an IoT-Cloud framework to manage edge nodes such as mobiles, smart objects, network devices, workstations, as a whole, a computing infrastructure allowing to provide resources on-demand, as services, to end users. Through Stack4Things facilities, the health tracking system can locate the closer computing resource to offload processing and thus reducing latency per the Edge computing paradigm. {\textcopyright} 2016, Springer Science+Business Media New York.

}, keywords = {Clouds, Computing infrastructures, Data management system, Distributed computer systems, Edge computing, Health, Health monitoring, Health tracking systems, human, human computer interaction, Information management, Internet, Internet of Things, Internet of Things (IOT), monitoring, Stack4Things, Tracking application, Wearable technology}, issn = {21911630}, doi = {10.1007/s12668-016-0388-5}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019121810\&doi=10.1007\%2fs12668-016-0388-5\&partnerID=40\&md5=e5aa843f2f869945fe04d5f62c97a6c5}, author = {Salvatore Distefano and Dario Bruneo and Francesco Longo and Giovanni Merlino and Antonio Puliafito} } @proceedings {Merlino2015199, title = {Cloud-based network virtualization: An IoT use case}, journal = {Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST}, volume = {155}, year = {2015}, note = {cited By 2; Conference of 7th International Conference on Ad Hoc Networks, AdHocHets 2015 ; Conference Date: 1 September 2015 Through 2 September 2015; Conference Code:139059}, pages = {199-210}, publisher = {Springer Verlag}, address = {San Remo (Italy)}, abstract = {

In light of an overarching scheme about extending the capabilities of Internet of things (IoT) with Cloud-enabled mechanisms, network virtualization is a key enabler of infrastructure-oriented IoT solutions. In particular, without network virtualization infrastructure cannot really be considered flexible enough to meet emerging requirements, and even administrative duties, such as management, maintenance and large-scale automation, would turn out to be brittle and addressed by special casing, leading to loss of generality and a variety of corner cases. We propose a Cloud-based network virtualization approach for IoT, based on the Open- Stack IaaS framework, where its networking subsystem, Neutron, gets extended to accomodate virtual networks and arbitrary topologies among virtualmachines and globally dispersed smart objects, whichever the setup and constraints of the underlying physical networks. This work outlines a motivating use case for our approach, and the ensuing discussion is provided to frame the benefits of the underlying design. {\textcopyright} Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2015.

}, keywords = {Ad hoc networks, Arbitrary topology, Clouds, Internet of Things, Internet of Things (IOT), IoT, network virtualization, OpenStack, Telecommunication networks, Underlying physical networks, Virtual networks, Virtual reality, WebSocket}, isbn = {9783319250663}, issn = {18678211}, doi = {10.1007/978-3-319-25067-0_16}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84947982973\&doi=10.1007\%2f978-3-319-25067-0_16\&partnerID=40\&md5=f749a4988e888d00cbdabf0649881264}, author = {Giovanni Merlino and Dario Bruneo and Francesco Longo and Salvatore Distefano and Antonio Puliafito} } @proceedings {Merlino2015268, title = {Enabling mechanisms for Cloud-based network virtualization in IoT}, journal = {IEEE World Forum on Internet of Things, WF-IoT 2015 - Proceedings}, year = {2015}, note = {cited By 3; Conference of 2nd IEEE World Forum on Internet of Things, WF-IoT 2015 ; Conference Date: 14 December 2015 Through 16 December 2015; Conference Code:119271}, pages = {268-273}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, address = {Milan (Italy)}, abstract = {

As part of a wider effort in integrating Internet of things (IoT) with the Cloud under the guise of infrastructure to be provided as-a-Service, network virtualization plays an essential role, both as an enabler of Infrastructure-as-a-Service scenarios and as a basic building block of the solution for the IoT-focused Cloud provider. Virtualization of the networking facilities for Cloud-managed IoT resources needs mechanisms to deal with the inherent complexity. This work outlines an implementation-agnostic approach to such a problem, reflected in our evolving Stack4Things architecture, derived from OpenStack, and implemented starting from such codebase, by leveraging also a choice of modern tooling and protocols. A specific use case and the discussion that follows are provided to frame the benefits of this strategy. {\textcopyright} 2015 IEEE.

}, keywords = {Basic building block, Cloud providers, Clouds, Complex networks, Infrastructure as a service (IaaS), Inherent complexity, Internet, Internet of Things, Internet of Things (IOT), Network architecture, network virtualization, OpenStack, Virtual reality, Virtualizations, WebSocket}, isbn = {9781509003655}, doi = {10.1109/WF-IoT.2015.7389064}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964453184\&doi=10.1109\%2fWF-IoT.2015.7389064\&partnerID=40\&md5=555a2a5aad4f3af24fac04fc0e4a8280}, author = {Giovanni Merlino and Dario Bruneo and Salvatore Distefano and Francesco Longo and Antonio Puliafito} } @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 = {

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.

}, 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 = {

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.

}, 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} } @proceedings {249, title = {Quantitative dependability assessment of distributed systems subject to variable conditions}, journal = {Internet and Distributed Computing Systems}, volume = {8223}, year = {2013}, pages = {385{\textendash}398}, publisher = {Springer Berlin Heidelberg}, address = {Berlin}, abstract = {

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.

}, keywords = {Dependability assessments, Dependability evaluation, Distributed computing systems, Internet of Things (IOT), Phase Type Distributions., Solution techniques, Variable conditions}, doi = {10.1007/978-3-642-41428-2_31}, author = {Distefano S. and Bruneo D. and Longo F. and Scarpa M.} }