@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} } @proceedings {Bruneo2015797, title = {Analytical Modeling of Reactive Autonomic Management Techniques in IaaS Clouds}, journal = {Proceedings - 2015 IEEE 8th International Conference on Cloud Computing, CLOUD 2015}, year = {2015}, note = {cited By 2; Conference of 8th IEEE International Conference on Cloud Computing, CLOUD 2015 ; Conference Date: 27 June 2015 Through 2 July 2015; Conference Code:116940}, pages = {797-804}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, address = {New York (USA)}, abstract = {

Cloud computing infrastructures provide services to a wide number of users whose behavior can deeply change at the occurrence of particular events. To correctly handle such situations a cloud infrastructure have to be reconfigured in a way that does not cause degradation in the overall performance. Otherwise, the quality of service specified in the service level agreement could be violated. To prevent such situations, the infrastructure could be organized as an autonomic system where self-adaptation and self-configuration techniques are implemented. Appropriate design choices become important in order not to fail in this goal. We propose a technique, based on a Petri net model and a specific analytical analysis approach, to represent Infrastructure-as-a-Service (IaaS) systems in the case in which the load conditions can suddenly change and reactive autonomic management techniques are applied to mitigate the consequences of the change. The model we propose is able to appropriately evaluate performance metrics in such critical situations making it suitable as a design tool for IaaS cloud systems. {\textcopyright} 2015 IEEE.

}, keywords = {Autonomic management, cloud computing, Cloud computing infrastructures, Cloud infrastructures, Iaas clouds, Industrial management, Infrastructure as a service (IaaS), Performance metrics, Petri nets, Quality of service, Resiliency, Service Level Agreements, Stochastic reward nets, Stochastic systems}, isbn = {9781467372879}, doi = {10.1109/CLOUD.2015.110}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960155425\&doi=10.1109\%2fCLOUD.2015.110\&partnerID=40\&md5=2aa09923889aea0bc667deb1d6d250d8}, author = {Dario Bruneo and Francesco Longo and Rahul Ghosh and Marco Scarpa and Antonio Puliafito and Kishor Trivedi} } @proceedings {Bruneo201524, title = {Enabling collaborative development in an open stack testbed: The cloud wave use case}, journal = {Proceedings of the 7th International Workshop on Principles of Engineering Service-Oriented and Cloud Systems (PESOS 2015)}, year = {2015}, note = {cited By 0; Conference of 7th International Workshop on Principles of Engineering Service-Oriented and Cloud Systems, PESOS 2015 ; Conference Date: 23 May 2015; Conference Code:117285}, pages = {24-30}, publisher = {IEEE Computer Society}, address = {Florence, Italy, 23 May 2015 - }, abstract = {

The Cloud Wave project embodies a challenging set of goals, including the development of software components that have to be integrated into a single multi-layer Cloud stack based on Open Stack, while cutting across the Infrastructure-as-a-Service, Platform-as-a-Service, and Software-as-a-Service levels by targeting layer-spanning issues such as Feedback-Driven Development and Coordinated Adaptation. A DevOps-ready test bed environment should allow project partners to exert full control over deployed compo entry and collaborate on development. Goals include providing a flexible infrastructure capable of emulating several multi-node Cloud environments, as well as enabling the automatic deployment of Cloud Wave artifacts into such environment in order to simplify integration activities. This paper takes a snapshot of the current situation with regards to the design and implementation of such a setup, trying to gain relevant insight out of this effort. {\textcopyright} 2015 IEEE.

}, keywords = {Automatic deployments, cloud computing, Collaborative development, Continuous integrations, Design and implementations, DevOps, Distributed computer systems, Infrastructure as a service (IaaS), Integration, OpenStack, Platform as a Service (PaaS), Software as a service (SaaS), Test bed environment, Testbeds, Virtual infrastructures}, isbn = {9781479919345}, issn = {21567921}, doi = {10.1109/PESOS.2015.12}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84955273627\&partnerID=40\&md5=3fed56f69ce2ffdc46abcdf129e1e355}, author = {Dario Bruneo and Francesco Longo and Giovanni Merlino and Nicola Peditto and Carmelo Romeo and Fabio Verboso and Antonio Puliafito} } @article {Bruneo20153052, title = {Modeling and Evaluation of Energy Policies in Green Clouds}, journal = {IEEE Transactions on Parallel and Distributed Systems}, volume = {26}, number = {11}, year = {2015}, note = {cited By 0}, pages = {3052-3065}, publisher = {IEEE Computer Society}, abstract = {

Following the as-a-service philosophy, a cloud service provider offers computing utilities in the form of virtual resources instantiated on top of a physical infrastructure. In order to meet business requirements still providing high-quality services, performance evaluation needs to be carefully carried out with the aim of optimizing data center utilization and increasing user satisfaction. In this context, power efficiency plays a critical role pushing service providers towards the application of innovative green strategies. In this paper, we present an analytical framework, based on stochastic reward nets, that allows to evaluate different resource allocation policies in a green cloud. A use case is shown in order to illustrate the approach, modeling scattering and saturation allocation policies and comparing them to a purely physical data center scenario. A validation of the proposed model against the CloudSim framework is presented and several numerical results are provided, demonstrating the effectiveness of the approach as a powerful tool for a cloud service provider to perform well-informed decisions about theresource allocation policies to be enforced. {\textcopyright} 1990-2012 IEEE.

}, keywords = {Allocation policies, Business requirement, cloud computing, Cloud service providers, Distributed database systems, Green Computing, High quality service, Performance evaluation, Quality control, Resource allocation, Resource allocation policy, Stochastic reward nets, Stochastic systems}, issn = {10459219}, doi = {10.1109/TPDS.2014.2364194}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84944075521\&partnerID=40\&md5=ee939ccd602bffca9ab90abdfd8285d9}, author = {Dario Bruneo and Audric Lhoas and Francesco Longo and Antonio Puliafito} } @proceedings {Bruneo2016175, title = {Multi-level adaptations in a CloudWave infrastructure: A telco use case}, journal = {European Conference on Service-Oriented and Cloud Computing}, volume = {567}, year = {2015}, note = {cited By 1; Conference of Workshops on CLIoT, WAS4FI, SeaClouds, CloudWay, IDEA, FedCloudNet 2015 held in conjunction with European Conference on Service-Oriented and Cloud Computing, ESOCC 2015 ; Conference Date: 15 September 2015 Through 17 September 2015; Conference Code:174149}, pages = {175-183}, publisher = {Springer Verlag}, address = {Taormina (Italy)}, abstract = {

CloudWave is a FP7 EU project whose aim is delivering novel technologies and methods for improving both the development of Cloud services and the management of their operation and execution. Such goal is reached by providing mechanisms and policies for coordinating multiple adaptations both at the level of the Cloud infrastructure and at the level of the hosted applications. In this paper, we describe the CloudWave Telco application use case and we provide a proof of concept discussing how the QoS experienced by the application users can be improved thanks to the technologies provided by CloudWave. {\textcopyright} Springer International Publishing Switzerland 2016.

}, keywords = {cloud computing, Cloud infrastructures, Cloud services, Eu projects, Multilevels, Multiple adaptation, Proof of concept, Quality of service}, isbn = {9783319333120}, issn = {18650929}, doi = {10.1007/978-3-319-33313-7_13}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84966667439\&doi=10.1007\%2f978-3-319-33313-7_13\&partnerID=40\&md5=00474a6170ba9f89b97c8a7ef8c59fce}, author = {Dario Bruneo and Francesco Longo and Boris Moltchanov} } @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} } @proceedings {Bruneo2014, title = {CloudWave: Where adaptive cloud management meets DevOps}, journal = {Proceedings of the 5th IEEE International Workshop on Performance Evaluation of Communications in Distributed Systems and Web based Service Architectures (PEDISWESA) Co-located with the 19th International Symposium on Computers and Communications (ISCC)}, year = {2014}, note = {cited By 0; Conference of ISCC 2014 Workshop - 5th IEEE International Workshop on Performance Evaluation of Communications in Distributed Systems and Web based Service Architectures, PEDISWESA 2014 ; Conference Date: 23 June 2014 Through 26 June 2014; Conference Code:108095}, publisher = {IEEE Computer Society}, address = {Island of Madeira, Funchal, Portugal, 23-26 June 2014}, abstract = {

The transition to cloud computing offers a large number of benefits, such as lower capital costs and a highly agile environment. Yet, the development of software engineering practices has not kept pace with this change. Moreover, the design and runtime behavior of cloud based services and the underlying cloud infrastructure are largely decoupled from one another.This paper describes the innovative concepts being developed by CloudWave to utilize the principles of DevOps to create an execution analytics cloud infrastructure where, through the use of programmable monitoring and online data abstraction, much more relevant information for the optimization of the ecosystem is obtained. Required optimizations are subsequently negotiated between the applications and the cloud infrastructure to obtain coordinated adaption of the ecosystem. Additionally, the project is developing the technology for a Feedback Driven Development Standard Development Kit which will utilize the data gathered through execution analytics to supply developers with a powerful mechanism to shorten application development cycles. {\textcopyright} 2014 IEEE.

}, keywords = {cloud computing, Cloud managements, Coordinated Adaptation, DevOps}, isbn = {9781479942770}, issn = {15301346}, doi = {10.1109/ISCC.2014.6912638}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84908149098\&partnerID=40\&md5=a0097ef370a848f29a660ea120514a63}, author = {Dario Bruneo and Thomas Fritz and Sharon Keidar-Barner and Philipp Leitner and Francesco Longo and Clarissa Marquezan and Andreas Metzger and Klaus Pohl and Antonio Puliafito and Danny Raz and Andreas Roth and Eliot Salant and Itai Segall and Massimo Villari and Yaron Wolfsthal and Chris Woods} } @proceedings {Bruneo201384, title = {Analytical evaluation of resource allocation policies in green IaaS clouds}, journal = {Proceedings of the IEEE 3rd International Conference on Cloud and Green Computing (CGC) Co-located with the IEEE 3rd International Conference on Social Computing and Its Applications (SCA)}, year = {2013}, note = {cited By 1; Conference of 3rd IEEE International Conference on Cloud and Green Computing, CGC 2013, Held Jointly with the 3rd IEEE International Conference on Social Computing and Its Applications, SCA 2013 ; Conference Date: 30 September 2013 Through 2 October 2013; Conference Code:102391}, pages = {84-91}, publisher = {IEEE Computer Society}, address = {Karlsruhe, Germany, 30 September - 2 October 2013}, abstract = {

Cloud systems represent the new ICT frontier where computing utilities are offered in terms of virtual instances, following the so called as-a-service philosophy. Different commercial solutions have been already put in place but several aspects need to be faced in order to provide high-value services able to meet business requirements. In particular, performance evaluation plays a critical role being strictly related to data center optimization and user satisfaction. Moreover, the use of large data centers able to respond to the high service demand has increased the attention to power efficiency, thus calling for green solutions and energy-aware strategies that jointly consider environmental and economical aspects. In order to design powerful strategies able to meet the quality of service requirements still reducing the energy costs, performance analysis frameworks are needed. In this paper, we present an analytical model, based on stochastic reward nets, that is able to easily implement resource allocation strategies in a green infrastructure as-a-service cloud. The model is organized into layers that represent the virtual resource pool and the physical machines. Different allocation algorithms (i.e., scattering, saturation) have been implemented by properly managing the coordination between the model layers. Numerical results are provided that demonstrate the effectiveness of the proposed approach. {\textcopyright} 2013 IEEE.

}, keywords = {Analytical evaluation, cloud computing, Distributed computer systems, Green Computing, Performance analysis, Performance evaluation, Quality of service, Resource allocation, Resource allocation policy, Resource allocation strategies, Service requirements, Stochastic reward nets, Stochastic systems}, isbn = {9780769551142}, doi = {10.1109/CGC.2013.21}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84893329592\&partnerID=40\&md5=369f37efc4aabea38300336d819db864}, author = {Dario Bruneo and Audric Lhoas and Francesco Longo and Antonio Puliafito} } @proceedings {Bruneo201371, title = {Availability Assessment of a Vision Cloud Storage Cluster}, journal = {European Conference on Service-Oriented and Cloud Computing (ESOCC)}, volume = {393 Communications in Computer and Information Science}, year = {2013}, note = {cited By 0; Conference of European Conference on Service-Oriented and Cloud Computing, ESOCC 2013 ; Conference Date: 11 September 2013 Through 13 September 2013; Conference Code:106555}, pages = {71-82}, publisher = {Springer Verlag}, address = {Malaga, Spain, 11-13 September 2013}, abstract = {

VISION Cloud is a European Commission funded project, whose aim is to design and propose a new architecture for a scalable and flexible cloud environment. The VISION Cloud reference architecture considers a single cloud as composed by multiple distributed data centers each of which can be composed by a great number of storage clusters. On top of the storage rich nodes forming each cluster, a distributed file system is built. In this paper, we provide an stochastic reward net model for a storage cluster in the context of the storage cloud environment proposed by the VISION Cloud project. The proposed model represents a first step in the direction of obtaining a quantification of the availability level reached through the use of the VISION Cloud proposed architecture from a user perspective. {\textcopyright} Springer-Verlag Berlin Heidelberg 2013.

}, keywords = {Architecture, Availability assessment, cloud computing, Cloud environments, Distributed file systems, European Commission, Proposed architectures, Reference architecture, Stochastic models, Stochastic reward nets, Stochastic systems, User perspectives}, isbn = {9783642453632}, issn = {18650929}, doi = {10.1007/978-3-642-45364-9_7}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84904676242\&partnerID=40\&md5=d7510b50bf986e126b22270279202382}, author = {Dario Bruneo and Francesco Longo and David Hadas and Hillel Kolodner} } @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 {Bruneo2012277, title = {Modeling energy-aware cloud federations with SRNs}, journal = {32nd International Conference on Application and Theory of Petri Nets and Concurrency (Petri Nets)}, volume = {7400 Lecture Notes in Computer Science}, year = {2012}, note = {cited By 4; Conference of 32nd International Conference on Application and Theory of Petri Nets and Concurrency, Petri Nets 2011 ; Conference Date: 20 June 2011 Through 24 June 2011; Conference Code:94089}, pages = {277-307}, publisher = {Springer-Verlag}, address = {Newcastle upon Tyne, United Kingdom, 20-24 June 2011}, abstract = {

Cloud computing is a challenging technology that promises to strongly modify the way computing and storage resources will be accessed in the near future. However, it may demand huge amount of energy if adequate management policies are not put in place. In particular, in the context of Infrastructure as a Service (IaaS) Cloud, optimization strategies are needed in order to allocate, migrate, consolidate virtual machines, and manage the switch on/switch off period of a data centre. In this paper, we present a methodology based on stochastic reward nets (SRNs) to investigate the more convenient strategies to manage a federation of two or more private or public IaaS Clouds. Several policies are presented and their impact is evaluated, thus contributing to a rational and efficient adoption of the Cloud computing paradigm. {\textcopyright} 2012 Springer-Verlag.

}, keywords = {cloud computing, Computing paradigm, Data centres, Digital storage, Energy aware, Energy conservation, Management policy, Optimization strategy, Performance evaluation, Petri nets, Quality of service, Stochastic reward nets, Stochastic systems, Storage resources, Switch-on, virtual machines}, isbn = {9783642351785}, issn = {03029743}, doi = {10.1007/978-3-642-35179-2_12}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84870045120\&partnerID=40\&md5=b1e106331e417cc512bcbc713cc582de}, author = {Dario Bruneo and Francesco Longo and Antonio Puliafito} } @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} } @proceedings {Bruneo2011, title = {Evaluating energy consumption in a cloud infrastructure}, journal = {2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)}, year = {2011}, note = {cited By 4; Conference of 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2011 ; Conference Date: 20 June 2011 Through 23 June 2011; Conference Code:86401}, publisher = {IEEE Computer Society}, address = {Lucca, Italy, 20-23 June 2011}, abstract = {

Cloud computing is a challenging technology that promises to strongly modify the way computing and storage resources will be accessed in the near future. Clouds may demand huge amount of energy if adequate management policies are not put in place. Optimization strategies are needed in order to allocate, migrate, consolidate virtual machines and manage the switch on/switch off period of a data center. In this paper, we present a modeling approach based on Stochastic reward nets to investigate the more convenient strategies to manage a federation of Clouds, having in mind the final goal to reduce the overall energy consumption. Several policies are presented and their impact is evaluated, thus contributing to a rational and efficient adoption of the Cloud computing paradigm. {\textcopyright} 2011 IEEE.

}, keywords = {cloud computing, Clouds, computer systems, Computing paradigm, Data centers, Energy utilization, Management policy, Modeling approach, Multimedia systems, Optimization strategy, Performance evaluation, Quality control, Quality of service, Stochastic reward nets, Stochastic systems, Storage resources, Switch-on, virtual machines, Wireless networks}, isbn = {9781457703515}, doi = {10.1109/WoWMoM.2011.5986479}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-80052709389\&partnerID=40\&md5=9d12783598805d3b668813d0d5b70057}, author = {Dario Bruneo and Francesco Longo and Antonio Puliafito} }