@proceedings {550, title = {Building a Digital Business Technology Platform in the Industry 4.0 Era}, journal = {Accepted for the 1st International Conference on Smart Innovation, Ergonomics and Applied Human Factors (SEAHF)}, year = {2019}, address = {Madrid, Spain}, keywords = {Big Data, data analytics, Digital Business, IoT, linked data knowledge, smart manufacturing}, author = {Maurizio Giacobbe and Maria Gabriella Xibilia and Antonio Puliafito} } @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 {505, title = {A Context-aware Strategy To Properly Use IoT-Cloud Services}, journal = {2017 IEEE International Conference on Smart Computing (SMARTCOMP)}, year = {2017}, month = {05/2017}, pages = {1-6}, publisher = {IEEE}, address = {Hong Kong - China}, abstract = {

Nowadays, we can talk about the Internet of Things (IoT) and Cloud computing union to indicate a new generation of distributed system.

An IoT-Cloud system mainly consists of a set of smart objects which are interconnected through the Internet with a remote Cloud infrastructure, platform, or software.

It allows to achieve new benefits in several contexts, such as smart cities and industrial businesses.

In this paper we propose a context-aware strategy focused on the correct use of the IoT-Cloud services. In particular, a use case driven scenario and a three-step algorithm to define the strategy are presented and discussed.

}, keywords = {Big Data, cloud computing, context-aware systems, Internet of Things, multi criteria decision making, smart cities, smart environments, smart factories}, doi = {10.1109/SMARTCOMP.2017.7946976}, author = {Maurizio Giacobbe and Antonio Puliafito and Riccardo Di Pietro and Marco Scarpa} } @proceedings {Dautov2017, title = {Towards a global intelligent surveillance system}, journal = {11th International Conference on Distributed Smart Cameras, ICDSC 2017}, year = {2017}, note = {cited By 2; Conference of 11th International Conference on Distributed Smart Cameras, ICDSC 2017 ; Conference Date: 5 September 2017 Through 7 September 2017; Conference Code:132201}, publisher = {Association for Computing Machinery}, address = {Stanford, USA - 05-07 September 2017}, abstract = {

Recent technological advances have led to the rapid development of Intelligent Surveillance Systems (ISSs), ubiquitously present in modern urban spaces are constantly generating streams of raw data. As most of the actual Internet traffic is nowadays constituted by visual data streams, often originated by ISSs, it is important to properly manage these avalanches of data so as to support sustainability of this technological trend, which will very likely saturate the current network bandwidth in few years. This paper aims to combine existing technologies and paradigms from the Internet of Things, Cloud, Edge Computing and Big Data into a common framework to enable a shared approach for ISSs at a wide geographical scale, thus envisioning a Global ISS. The proposed solution is based on the idea of pushing data processing tasks as close to data sources as possible, thus increasing security and performance levels, usually critical to surveillance systems. To demonstrate the feasibility and the effectiveness of the proposed approach, the paper presents a case study based on a distributed ISS scenario in a crowded area, implemented on clustered edge devices able to offload tasks in a {\textquoteright}horizontal{\textquoteright} manner. {\textcopyright} 2017 Association for Computing Machinery.

}, keywords = {Big Data, Clouds, Edge, Geographical scale, Information management, Intelligent surveillance systems, Internet of Things, monitoring, Network security, Security and performance, Security systems, Stream processing, Surveillance systems, Technological advances, Technological trends}, doi = {10.1145/3131885.3131918}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047726635\&doi=10.1145\%2f3131885.3131918\&partnerID=40\&md5=a84eba85cc0facc8c5bb0cd664d7d5f0}, author = {Rustem Dautov and Salvatore Distefano and Giovanni Merlino and Dario Bruneo and Francesco Longo 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} } @proceedings {7092964, title = {How to Enhance Cloud Architectures to Enable Cross-Federation: Towards Interoperable Storage Providers}, journal = { IEEE International Conference on Cloud Engineering (IC2E), Tempe, AZ, USA}, year = {2015}, month = {March}, pages = {480-486}, publisher = {IEEE Computer Society}, address = {Washington D.C.}, keywords = {Big Data, Big Data storage, CLEVER, CLEVER message oriented middleware, cloud architectures, cloud computing, cloud storage market, cross-federation, Ecosystems, federated cloud ecosystem, federation, Hadoop, Hadoop distribute file system, HDFS, inter-domain communication management, interoperable storage providers, Message systems, middleware, MOM, Protocols, public domain software, Resource management, Servers, small-medium cloud storage providers, Storage, storage management, XML, XMPP}, doi = {10.1109/IC2E.2015.80}, url = {http://conferences.computer.org/IC2E/2015/index.htm}, author = {Maria Fazio and Antonio Celesti and Massimo Villari and Antonio Puliafito} } @proceedings {Merlino2015909, title = {Software defined cities: A novel paradigm for smart cities through IoT clouds}, journal = {Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 20}, year = {2015}, note = {cited By 1; Conference of Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015 ; Conference Date: 10 August 2015 Through 14 August 2015; Conference Code:122811}, pages = {909-916}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, address = {Beijing (China)}, abstract = {

A Smart City represents an improvement of today cities that strategically exploits many smart factors to increase the city sustainable growth and strengthen city functions, while ensuring citizen quality of life and health. Cities can be perceived as an ecosystem of "things" which citizens daily interact with: street furniture, public buildings, transportation, monuments, public lighting as well as personal smartphones. Thanks to recent advances in ICT such things can be considered always interconnected also providing sensing and actuating facilities according to the Internet of Things and Cyber Physical Systems models. Creating smart services that exploit such a complex infrastructure is a fundamental and current challenge. To this end, aim of this paper is the design and implementation of the Software Defined Cities approach: a Cloud-based infrastructure that, starting from the well known concept of Software Defined paradigms, is able to transform this complex ecosystem in a simple and "programmable" environment where municipalities, companies, scientists, and citizens can easily collaborate in developing innovative smart services. The overall architecture is presented focusing on both the function virtualization and infrastructure aspects also giving details about the software stacks used (e.g., Open Stack) while a use case is laid out to demonstrate the advantages of the proposed approach. {\textcopyright} 2015 IEEE.

}, keywords = {Big Data, Clouds, Complex ecosystems, Complex infrastructures, Cyber physical systems (CPSs), Design and implementations, Ecology, Ecosystems, embedded systems, Internet, Internet of Things, Sensing and actuating, smart cities, Sustainable development, Sustainable growth, Trusted Computing, Ubiquitous computing, Virtual reality, Virtualizations}, isbn = {9781467372114}, doi = {10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.174}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983438378\&doi=10.1109\%2fUIC-ATC-ScalCom-CBDCom-IoP.2015.174\&partnerID=40\&md5=790a6042e6e80594e42b64695d6b014e}, author = {Giovanni Merlino and Dario Bruneo and Francesco Longo and Antonio Puliafito and Salvatore Distefano} } @proceedings {Longo2015204, title = {Stack4Things: An OpenStack-Based Framework for IoT}, journal = {Proceedings - 2015 International Conference on Future Internet of Things and Cloud, FiCloud 2015 and 2015 International Conference on Open and Big Data, OBD 2015}, year = {2015}, note = {cited By 2; Conference of 3rd International Conference on Future Internet of Things and Cloud, FiCloud 2015 ; Conference Date: 24 August 2015 Through 26 August 2015; Conference Code:117067}, pages = {204-211}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, address = {Rome (Italy)}, abstract = {

In the wake of the massive adoption of embedded systems, mobiles, and other smart devices, as the scope of their involvement keeps broadening, complexity may quickly become overwhelming and vertical ad-hoc solutions will not cut it anymore. We propose to reuse as much tooling as possible, taking into account suitable options with regard to infrastructure management, then piggybacking as much advanced functionalities as possible in such kind of environment. In this sense, a widely used and competitive framework for Infrastructure-as-a-Service such as OpenStack, with its breadth in terms of feature coverage and expanded scope, looks like fitting the bill. This work therefore describes the approach and the solutions so far preliminary implemented for enabling Cloud-mediated interactions with droves of sensor-and actuator-hosting nodes by proposing Stack4Things, a framework for Sensing-and-Actuation-as-a-Service. In particular, we focused on describing the subsystem of Stack4Things devoted to resource control and management, highlighting relevant requirements and justifying how our proposed framework addresses them, while also opening up possibilities for a range of future extensions towards complete fulfillment of the Sensing-and-Actuation-as-a-Service vision. {\textcopyright} 2015 IEEE.

}, keywords = {Big Data, Clouds, embedded systems, Infrastructure as a service (IaaS), Infrastructure managements, Internet, Internet of Things, Mediated interaction, OpenStack, Resource control, SAaaS, Sensor and actuators, WAMP, Web Socket}, isbn = {9781467381031}, doi = {10.1109/FiCloud.2015.97}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959059371\&doi=10.1109\%2fFiCloud.2015.97\&partnerID=40\&md5=e702319ada1b2cdde5d5d2061ec278f7}, author = {Francesco Longo and Dario Bruneo and Salvatore Distefano and Giovanni Merlino and Antonio Puliafito} } @article {43, title = {Evaluating A File Fragmentation System For Multi-provider Cloud Storage}, journal = {SCALABLE COMPUTING. PRACTICE AND EXPERIENCE}, volume = {14}, year = {2013}, pages = {265{\textendash}277}, abstract = {

Currently, storage services represent a new way to do business in Cloud computing. This new trend is proved by the number of Cloud storage providers that are appearing on the market. In this work, we present an innovative approach useful for using different Cloud storage providers in a transparent way, avoiding both data lock-in and possible data privacy violation that can be caused by providers themselves. More specifically, we propose an approach enabling Cloud customers to rely on many Cloud storage providers. Differently from other solutions, with our approach only the customers have the full control of their data, and in addition, if a provider suddenly disappears and/or it is not available anymore, the customers will be able to continue accessing their data, reconstructing them from data fragments replicated in other Cloud storage providers. The paper shows how such an approach works. In particular, experiments, besides proving the goodness of our approach, also provide several guidelines regarding how to properly configure software systems in order to meet the customer{\textquoteright}s requirements (in terms of both QoS and costs).

}, keywords = {Big Data, cloud computing, Confidentiality., Reliability, Storage}, doi = {10.12694/scpe.v14i4.932}, url = {http://www.scpe.org/index.php/scpe/article/view/932/0}, author = {Massimo Villari and Antonio Celesti and Maria Fazio and Antonio Puliafito} }