@article {549, title = {An IoT service ecosystem for Smart Cities: The $\#$SmartME project}, journal = {Internet of Things - Elsevier}, volume = {5}, year = {2019}, pages = {12-33}, abstract = {

$\#$SmartME has been one of the first initiatives in Italy to realize a Smart City through the use of open technologies. Thanks to the use of low cost sensor-powered devices scattered over the city area, different {\textquotedblleft}smart{\textquotedblright} services have been deployed having the Stack4Things framework as the common underlying middleware.\ In this paper, we present the results obtained after 2 years of project highlighting the vertical solutions that have been proposed in different areas ranging from environmental monitoring to parking management.

}, keywords = {Arduino, Blockchain, cloud computing, IoT, OpenStack, Smart city}, issn = {2542-6605}, doi = {https://doi.org/10.1016/j.iot.2018.11.004}, author = {Dario Bruneo and Salvatore Distefano and Maurizio Giacobbe and Antonino Longo Minnolo and Francesco Longo and Giovanni Merlino and Davide Mulfari and Alfonso Panarello and Giuseppe Patan{\`e} and Antonio Puliafito and Carlo Puliafito and Nachiket Tapas} } @article {Panarello2018, title = {Blockchain and iot integration: A systematic survey}, journal = {Sensors - MDPI}, volume = {18}, number = {8}, year = {2018}, note = {cited By 10}, publisher = {MDPI AG}, abstract = {

The Internet of Things (IoT) refers to the interconnection of smart devices to collect data and make intelligent decisions. However, a lack of intrinsic security measures makes IoT vulnerable to privacy and security threats. With its {\textquotedblleft}security by design,{\textquotedblright} Blockchain (BC) can help in addressing major security requirements in IoT. BC capabilities like immutability, transparency, auditability, data encryption and operational resilience can help solve most architectural shortcomings of IoT. This article presents a comprehensive survey on BC and IoT integration. The objective of this paper is to analyze the current research trends on the usage of BC-related approaches and technologies in an IoT context. This paper presents the following novelties, with respect to related work: (i) it covers different application domains, organizing the available literature according to this categorization, (ii) it introduces two usage patterns, i.e., device manipulation and data management (open marketplace solution), and (iii) it reports on the development level of some of the presented solutions. We also analyze the main challenges faced by the research community in the smooth integration of BC and IoT, and point out the main open issues and future research directions. Last but not least, we also present a survey about novel uses of BC in the machine economy. {\textcopyright} 2018 by the authors. Licensee MDPI, Basel, Switzerland.

}, keywords = {Blockchain, Cryptography, Future research directions, Information management, Integration, Intelligent decisions, Internet of thing (IOT), Internet of Things, Privacy and security, Research communities, Security by designs, Security measure, Security requirements, Surveying, Surveys}, issn = {14248220}, doi = {10.3390/s18082575}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051401073\&doi=10.3390\%2fs18082575\&partnerID=40\&md5=07247598c49b9507bea67e04bb3e325f}, author = {Alfonso Panarello and Nachiket Tapas and Giovanni Merlino and Francesco Longo and Antonio Puliafito} } @proceedings {535, title = {Building a Smart City Service Platform in Messina with the $\#$SmartME Project}, journal = {The 32nd IEEE International Conference on Advanced Information Networking and Applications (IEEE AINA-2018)}, year = {2018}, month = {05/2018}, address = {Pedagogical University of Cracow, Poland}, abstract = {

Some words mark an era, and "Smart City" is definitely one of these. A Smart City is an urban area where the Information and Communication Technologies (ICT) are employed to improve citizens{\textquoteright} Quality of Life (QoL) in areas such as: mobility, urban surveillance, and energy management. Throughout this paper, we present the $\#$SmartME project, which aims to create an infrastructure and an ecosystem of "smart" services by exploiting existing devices, sensors, and actuators distributed in the city of Messina. We also present the Stack4Things framework, which is the management core of the $\#$SmartME project.

}, keywords = {$\#$SmartME, Arduino, Blockchain, cloud computing, IoT, OpenData, OpenStack, Smart city, Stack4Things}, author = {Dario Bruneo and Sebastiano Chillari and Salvatore Distefano and Maurizio Giacobbe and Antonino Longo Minnolo and Francesco Longo and Giovanni Merlino and Davide Mulfari and Alfonso Panarello and Giuseppe Patan{\`e} and Antonio Puliafito and Carlo Puliafito and Marco Scarpa and Nachiket Tapas and Giancarlo Visalli} } @proceedings {Tricomi2017, title = {Orchestrated Multi-Cloud Application Deployment in OpenStack with TOSCA}, journal = {2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017}, year = {2017}, note = {cited By 0; Conference of 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017 ; Conference Date: 29 May 2017 Through 31 May 2017; Conference Code:128356}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, address = {Hong Kong; China; 29-31 May 2017}, abstract = {

Cloud computing is becoming a relatively mature paradigm in the ICT landscape. In light of the growing appetite for resources and service levels on par with user expectations, multi-cloud scenarios are becoming the next frontier in the usage of distributed datacenters for private and hybrid Cloud scenarios. Application deployment in particular is a noteworthy feature to be evaluated as microservices become mainstream in adoption. Especially so when considered jointly with orchestration services; indeed OpenStack, as the most widely adopted Cloud middleware among the OpenSource community, features an orchestration subsystem, and may orchestrate the deployment of applications and services. In this work the authors will describe an architecture, developed within the H2020 BEACON project, for a standardized approach to orchestrated application deployment in multi-Cloud OpenStack-based setups, with TOSCA providing the specifications. {\textcopyright} 2017 IEEE.

}, keywords = {Cloud federations, deployment, microservices, middleware, Multi-clouds, OpenStack, orchestration, Platform as a Service (PaaS), TOSCA}, isbn = {9781509065172}, doi = {10.1109/SMARTCOMP.2017.7947027}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85023168002\&doi=10.1109\%2fSMARTCOMP.2017.7947027\&partnerID=40\&md5=94bbf6ca2fa1b1d2b92047683723948c}, author = {Giuseppe Tricomi and Alfonso Panarello and Giovanni Merlino and Francesco Longo and Dario Bruneo and Antonio Puliafito} } @proceedings {161, title = {Costs of a Federated and Hybrid Cloud Environment Aimed at MapReduce Video Transcoding}, journal = {2015 IEEE Symposium on Computers and Communication (ISCC), Larnaca Cyprus}, year = {2015}, month = {2015}, pages = {258-263}, publisher = {IEEE Computer Society}, address = {Larnaca, Cyprus}, abstract = {
In this paper we investigate the applicability of the federation among several Cloud platform, demonstrating that a federated environment provides evident benefits despite the costs for the setup and maintainance of the federation itself. Also, we propose a new solution able to manage resource allocation in federated Clouds where resource requests occur in a dynamic way. We adopt such a solution to setup distributed Hadoop nodes of virtual clusters for the parallel MapReduce processing of large data sets. To increase their capabilities, Cloud Providers establish a federation relationship, making the Hadoop-based Cloud platforms much more performing than in the isolate case, adding a further level of parallelization in service provisioning. The results analyzed in the referece use case, that is a video transcoding using the MapReduce paradigm in a federated fashion, show how the federation costs in terms of delays and overhead are low in comparison with the service provisioning costs, and also highlight how federation makes the offered Cloud service more streamlined and fast.
}, keywords = {Apache Hadoop, Big Data, CLEVER, cloud computing, HDFS, Horizontal Federation, IEEE P2302, MapReduce}, doi = {10.1109/ISCC.2015.7405525}, url = {http://ieeexplore.ieee.org/xpl/login.jsp?tp=\&arnumber=7405525\&url=http\%3A\%2F\%2Fieeexplore.ieee.org\%2Fxpls\%2Fabs_all.jsp\%3Farnumber\%3D7405525}, author = {Alfonso Panarello and Maria Fazio and Antonio Celesti and Massimo Villari and Antonio Puliafito} } @proceedings {221, title = {A Federated MapReduce-based Video Transcoding System to Face the Future Massive Video-Selfie Sharing Trend}, journal = {Fourth European Conference on Service-Oriented and Cloud Computing (ESOCC 2015) - 3rd International Workshop on Cloud for IoT}, year = {2015}, publisher = {Springer International Publishing}, edition = {Communications in Computer and Information Science (CCSI)}, abstract = {
The massive use of mobile devices and social networks is causing the birth of a new compulsive users{\textquoteright} behaviour. The activity photo selfie sharing is gradually turning into video selfie. These videos will be transcoded into multiple formats to support different visualization mode. We think there will be the need to have systems that can support, in a fast, efficient and scalable way, the millions of requests for video sharing and viewing. We think that a single Cloud Computing services provider cannot alone cope with this huge amount of incoming data (Big Data), so in this paper we propose a Cloud Federation-based system that exploiting the Hadoop MapReduce paradigm performs the video transcoding in multiple format and its distribution in a fastest and most efficient possible way. Experimental results highlight the major factors involved for job deployment in a federated Cloud environment and the efficiency of the proposed system.
}, keywords = {Adaptive Streaming, Apache Hadoop, Big Data, CLEVER, cloud computing, HDFS, Horizontal Federation, IEEE P2302, MapReduce}, author = {Alfonso Panarello and Antonio Celesti and Maria Fazio and Massimo Villari and Antonio Puliafito} }