@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} } @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} } @article {Dautov201829822, title = {Data Processing in Cyber-Physical-Social Systems Through Edge Computing}, journal = {IEEE Access - IEEE}, volume = {6}, year = {2018}, note = {cited By 0}, pages = {29822-29835}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {

Cloud and Fog computing have established a convenient and widely adopted approach for computation offloading, where raw data generated by edge devices in the Internet of Things (IoT) context is collected and processed remotely. This vertical offloading pattern, however, typically does not take into account increasingly pressing time constraints of the emerging IoT scenarios, in which numerous data sources, including human agents (i.e., Social IoT), continuously generate large amounts of data to be processed in a timely manner. Big data solutions could be applied in this respect, provided that networking issues and limitations related to connectivity of edge devices are properly addressed. Although edge devices are traditionally considered to be resource-constrained, main limitations refer to energy, networking, and memory capacities, whereas their ever-growing processing capabilities are already sufficient to be effectively involved in actual (big data) processing. In this context, the role of human agents is no longer limited to passive data generation, but can also include their voluntary involvement in relatively complex computations. This way, users can share their personal computational resources (i.e., mobile phones) to support collaborative data processing, thereby turning the existing IoT into a global cyber-physical-social system (CPSS). To this extent, this paper proposes a novel IoT/CPSS data processing pattern based on the stream processing technology, aiming to distribute the workload among a cluster of edge devices, involving mobile nodes shared by contributors on a voluntary basis, and paving the way for cluster computing at the edge. Experiments on an intelligent surveillance system deployed on an edge device cluster demonstrate the feasibility of the proposed approach, illustrating how its distributed in-memory data processing architecture can be effective. {\textcopyright} 2013 IEEE.

}, keywords = {Apache NiFi, Big Data, Cameras, Cellular telephone systems, cloud computing, Cluster computing, Computer architecture, Cyber physical social systems, Cyber Physical System, Edge computing, Fog computing, Horizontal and Vertical Offloading, Internet of Things, Media streaming, Network security, Servers, Stream processing, Streaming media}, issn = {21693536}, doi = {10.1109/ACCESS.2018.2839915}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047619039\&doi=10.1109\%2fACCESS.2018.2839915\&partnerID=40\&md5=48b52a73084c2f6396c4ce1dd6a690f4}, author = {Rustem Dautov and Salvatore Distefano and Dario Bruneo and Francesco Longo and Giovanni Merlino and Antonio Puliafito} } @article {Dautov20181475, title = {Metropolitan intelligent surveillance systems for urban areas by harnessing IoT and edge computing paradigms}, journal = {Software - Practice and Experience - John Wiley \& Sons, Ltd.}, volume = {48}, number = {8}, year = {2018}, note = {cited By 0}, pages = {1475-1492}, publisher = {John Wiley and Sons Ltd}, abstract = {

Recent technological advances led to the rapid and uncontrolled proliferation of intelligent surveillance systems (ISSs), serving to supervise urban areas. Driven by pressing public safety and security requirements, modern cities are being transformed into tangled cyber-physical environments, consisting of numerous heterogeneous ISSs under different administrative domains with low or no capabilities for reuse and interaction. This isolated pattern renders itself unsustainable in city-wide scenarios that typically require to aggregate, manage, and process multiple video streams continuously generated by distributed ISS sources. A coordinated approach is therefore required to enable an interoperable ISS for metropolitan areas, facilitating technological sustainability to prevent network bandwidth saturation. To meet these requirements, this paper combines several approaches and technologies, namely the Internet of Things, cloud computing, edge computing and big data, into a common framework to enable a unified approach to implementing an ISS at an urban scale, thus paving the way for the metropolitan intelligent surveillance system (MISS). The proposed solution aims to push data management and processing tasks as close to data sources as possible, thus increasing performance and security levels that are usually critical to surveillance systems. To demonstrate the feasibility and the effectiveness of this approach, the paper presents a case study based on a distributed ISS scenario in a crowded urban area, implemented on clustered edge devices that are able to off-load tasks in a {\textquotedblleft}horizontal{\textquotedblright} manner in the context of the developed MISS framework. As demonstrated by the initial experiments, the MISS prototype is able to obtain face recognition results 8 times faster compared with the traditional off-loading pattern, where processing tasks are pushed {\textquotedblleft}vertically{\textquotedblright} to the cloud. Copyright {\textcopyright} 2018 John Wiley \& Sons, Ltd.

}, keywords = {Big Data, cloud computing, Distributed Smart Cameras, Edge computing, Face recognition, Information management, Intelligent surveillance systems, Internet of Things, monitoring, Multiple video streams, Network security, Public safety and securities, Security systems, Smart city, Stack4Things, Stream processing, Surveillance systems, Technological advances}, issn = {00380644}, doi = {10.1002/spe.2586}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049578094\&doi=10.1002\%2fspe.2586\&partnerID=40\&md5=25de910451975bb24c9cfbdf6ca69066}, author = {Rustem Dautov and Salvatore Distefano and Dario Bruneo and Francesco Longo and Giovanni Merlino and Antonio Puliafito and Rajkumar Buyya} } @proceedings {Dautov2018792, title = {Pushing intelligence to the edge with a stream processing architecture}, journal = {Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017}, year = {2017}, note = {cited By 3; Conference of Joint 10th IEEE International Conference on Internet of Things, iThings 2017, 13th IEEE International Conference on Green Computing and Communications, GreenCom 2017, 10th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2017 and the 3rd IEEE International Conference on Smart Data, Smart Data 2017 ; Conference Date: 21 June 2017 Through 23 June 2017; Conference Code:134517}, pages = {792-799}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, address = {Exeter, UK - 21-23 June 2017}, abstract = {

The cloud computing paradigm underpins the Internet of Things (IoT) by offering a seemingly infinite pool of resources for processing/storing extreme amounts of data generated by complex IoT systems. The cloud has established a convenient and widely adopted approach, where raw data are vertically offloaded to cloud servers from resource-constrained edge devices, which are only seen as simple data generators, not capable of performing more sophisticated processing activities. However, there are more and more emerging scenarios, where the amount of data to be transferred over the network to the cloud is associated with increased network latency, making the results of the computation obsolete. As various categories of edge devices are becoming more and more powerful in terms of hardware resources - specifically, CPU and memory - the established way of off-loading computation to the cloud is not always seen as the most convenient approach. Accordingly, this paper presents a Stream Processing architecture for spreading workload among a local cluster of edge devices to process data in parallel, thus achieving faster execution and response times. The experimental results suggest that such a distributed in-memory approach to data processing at the very edge of a computational network has a potential to address a wide range of IoT-related scenarios. {\textcopyright} 2017 IEEE.

}, keywords = {Apache NiFi, cloud computing, Cluster computing, Computational networks, Data handling, Edge computing, Green Computing, Hardware resources, Horizontal offloading, Internet of thing (IOT), Internet of Things, Memory architecture, Network architecture, Network latencies, Processing activity, Stream processing}, isbn = {9781538630655}, doi = {10.1109/iThings-GreenCom-CPSCom-SmartData.2017.121}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047094836\&doi=10.1109\%2fiThings-GreenCom-CPSCom-SmartData.2017.121\&partnerID=40\&md5=4e5a4b0eaffa179565af183066520cdf}, author = {Rustem Dautov and Salvatore Distefano and Dario Bruneo and Francesco Longo and Giovanni Merlino and Antonio Puliafito} } @proceedings {Bruneo2017222, title = {IoT-cloud authorization and delegation mechanisms for ubiquitous sensing and actuation}, journal = {2016 IEEE 3rd World Forum on Internet of Things, WF-IoT 2016}, year = {2016}, note = {cited By 0; Conference of 3rd IEEE World Forum on Internet of Things, WF-IoT 2016 ; Conference Date: 12 December 2016 Through 14 December 2016; Conference Code:126414}, pages = {222-227}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, address = {Reston; United States; 12-14 December 2016}, abstract = {

In the roadmap for the implementation of ubiquitous computing, ubiquitous sensing and actuation is a milestone still to be reached. It refers to providing sensing and actuation facilities anytime and everywhere. This does not just imply to interconnect sensors and actuators through the Internet, but also and mainly to provide this facilities. IoT-Cloud computing paradigms such as the sensing and actuation as a service one could be a proper way to address this problem. In past work we developed an SAaaS framework extending OpenStack with specific functionalities for resource constrained nodes, Stack4Things. In this paper we focus on access control, authorization and delegation mechanisms which are basic mechanisms for the implementation of the UbSA vision. Thus starting from Stack4Things, we describe how we adapted and extended mechanisms provided by OpenStack, with specific regard to Keystone, with new functionalities for delegation and access control. A use case in the smart city scenario of $\#$SmartME describes the proposed solution in practice. {\textcopyright} 2016 IEEE.

}, keywords = {Access control, Arches, Basic mechanism, cloud computing, Delegation, Delegation mechanisms, Interconnect sensors, Internet of Things, Keystone, OpenStack, Platform as a Service (PaaS), Resource constrained nodes, Sensing and Actuation as a Service, Smart city, Ubiquitous computing}, isbn = {9781509041305}, doi = {10.1109/WF-IoT.2016.7845494}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015210244\&doi=10.1109\%2fWF-IoT.2016.7845494\&partnerID=40\&md5=055a280adfbce85756d94736e2b82c55}, author = {Dario Bruneo and Salvatore Distefano and Francesco Longo and Giovanni Merlino and Antonio Puliafito} } @article {Longo20152506, title = {Variable operating conditions in distributed systems: Modeling and evaluation}, journal = {Concurrency Computation Practice and Experience}, volume = {27}, number = {10}, year = {2015}, note = {cited By 1}, pages = {2506-2530}, publisher = {John Wiley and Sons Ltd}, abstract = {

SummaryPerformance and dependability evaluation plays a key role in the design of a broad range of systems, especially when strict requirements need to be met. This is particularly challenging in distributed contexts, where several components may interact among themselves by influencing each other. In this paper, we present an analytical method that allows the study of a class of systems where different operating conditions alternate by changing the stochastic behavior of the system components but still preserving the continuity of the performance and dependability quantities to investigate. The proposed solution technique, based on phase type distributions, Kronecker algebra, and ad-hoc fitting algorithms, can be applied for the analytical evaluation of a wide class of distributed systems. Examples are provided to show the usefulness and the applicability of the methodology, characterizing and investigating different performance and dependability aspects of three distributed computing systems, that is, a connection-oriented network, an Internet of Things application, and an Infrastructure-as-a-Service Cloud. Copyright {\textcopyright} 2014 John Wiley \& Sons, Ltd.

}, keywords = {Algebra, cloud computing, Conservative systems, Dependability, Distributed computer systems, Internet, Internet of Things, Kronecker algebra, Markov processes, Non-Markovian, Performance, phase type distributions, Stochastic systems}, issn = {15320626}, doi = {10.1002/cpe.3419}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84932604392\&partnerID=40\&md5=b8f197a50fa177e85f0c1ac2a93fe392}, author = {Francesco Longo and Dario Bruneo and Salvatore Distefano and Marco Scarpa} } @article {Bruneo20131072, title = {Workload-based software rejuvenation in cloud systems}, journal = {IEEE Transactions on Computers - IEEE Computer Society}, volume = {62}, number = {6}, year = {2013}, note = {cited By 21}, pages = {1072-1085}, abstract = {

Cloud computing is a promising paradigm able to rationalize the use of hardware resources by means of virtualization. Virtualization allows to instantiate one or more virtual machines (VMs) on top of a single physical machine managed by a virtual machine monitor (VMM). Similarly to any other software, a VMM experiences aging and failures. Software rejuvenation is a proactive fault management technique that involves terminating an application, cleaning up the system internal state, and restarting it to prevent the occurrence of future failures. In this work, we propose a technique to model and evaluate the VMM aging process and to investigate the optimal rejuvenation policy that maximizes the VMM availability under variable workload conditions. Starting from dynamic reliability theory and adopting symbolic algebraic techniques, we investigate and compare existing time-based VMM rejuvenation policies. We also propose a time-based policy that adapts the rejuvenation timer to the VMM workload condition improving the system availability. The effectiveness of the proposed modeling technique is demonstrated through a numerical example based on a case study taken from the literature. {\textcopyright} 1968-2012 IEEE.

}, keywords = {Algebraic techniques, Application programs, cloud computing, Endocrinology, Kronecker algebra, Numerical methods, phase type distributions, Proactive fault managements, Reliability theory, Software rejuvenation, System availability, Time-based Rejuvenation, Virtual machine monitors, Virtual reality}, issn = {00189340}, doi = {10.1109/TC.2013.30}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84877311601\&partnerID=40\&md5=185051c9b74e6577b5b06c39cbaf7cc7}, author = {Dario Bruneo and Salvatore Distefano and Francesco Longo and Antonio Puliafito and Marco Scarpa} } @proceedings {Bruneo20128, title = {Software rejuvenation in the cloud}, journal = {Proceedings of the 5th International Conference on Simulation Tools and Techniques (SIMUTools)}, year = {2012}, note = {cited By 0; Conference of 5th International Conference on Simulation Tools and Techniques, SIMUTools 2012 ; Conference Date: 19 March 2012 Through 23 March 2012; Conference Code:110134}, pages = {8-16}, publisher = {ICST}, address = {Desenzano del Garda, Italy, 19-23 March 2012}, abstract = {

In this paper, we investigate how software rejuvenation can be used in a Cloud environment to increase the availability of a virtualized system composed of a single virtual machine monitor (VMM) on top of which a certain number of virtual machines (VMs) can be instantiated. We start from the assumption that the aging of a VMM increases with the number of VMs it is managing, thus characterizing the problem in terms of dynamic reliability. Therefore, by identifying the age of the VMM with its reliability and based on the conservation of reliability principle, we characterize the time to failure of the VMM through continuous phase type distributions. The system availability is thus modeled by an expanded continuous time Markov chain expressed in terms of Kronecker algebra in order to face the state space explosion and to keep memory of the age reached by the VMM in case the number of the hosted VMs change. Time-based rejuvenation is taken into consideration and the optimal timer is evaluated in order to maximize the VMM availability. Copyright {\textcopyright} 2012 ICST.

}, keywords = {Availability, cloud computing, Continuous phase type distributions, Continuous time Markov chain, Continuous time systems, Endocrinology, Java programming language, Markov processes, phase type distributions, Rejuvenation, Reliability, Reliability principles, Software rejuvenation, Virtual machine monitors, Virtual reality, Virtualized environment}, isbn = {9781450315104}, doi = {10.4108/icst.simutools.2012.247772}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84922767370\&partnerID=40\&md5=a03b06eec703c94d55c0f4875f181902}, author = {Dario Bruneo and Francesco Longo and Antonio Puliafito and Marco Scarpa and Salvatore Distefano} }