@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 {Bruneo201598, title = {An SRN-based resiliency quantification approach}, journal = {Proceedings of the 36th International Conference on Application and Theory of Petri Nets and Concurrency (Petri Nets)}, volume = {9115 Lecture Notes in Computer Science}, year = {2015}, note = {cited By 0; Conference of 36th International Conference on Application and Theory of Petri Nets and Concurrency, Petri Nets 2015 ; Conference Date: 21 June 2015 Through 26 June 2015; Conference Code:119609}, pages = {98-116}, publisher = {Springer Verlag}, address = {Brussels, Belgium, 21-26 June 2015}, abstract = {

Resiliency is often considered as a synonym for faulttolerance and reliability/availability. We start from a different definition of resiliency as the ability to deliver services when encountering unexpected changes. Semantics of change is of extreme importance in order to accurately capture the real behavior of a system. We propose a resiliency analysis technique based on stochastic reward nets that allows the modeler: (1) to reuse an already existing dependability or performance model for a specific system with minimal modifications, and (2) to adapt the given model for specific change semantics. To automate the model analysis an algorithm is designed and the modeler is provided with a formalism that corresponds to the semantics. Our algorithm and approach is implemented to demonstrate the proposed resiliency quantification approach. Finally, we discuss the differences between our approach and an alternative technique based on deterministic and stochastic Petri nets and highlight the advantages of the proposed approach in terms of semantics specification. {\textcopyright} Springer International Publishing Switzerland 2015.

}, keywords = {Analysis techniques, Deterministic and stochastic Petri nets, Model analysis, Performance Model, Petri nets, Resiliency, Semantics, Stochastic models, Stochastic reward nets, Stochastic systems}, isbn = {9783319194875}, issn = {03029743}, doi = {10.1007/978-3-319-19488-2_5}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84937428490\&partnerID=40\&md5=7d0bbe99afba1a79df65b4e35e86a02c}, author = {Dario Bruneo and Francesco Longo and Marco Scarpa and Antonio Puliafito and Rahul Ghosh and Kishor S. Trivedi} } @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} } @article {Bruneo20111213, title = {Performance analysis of job dissemination techniques in Grid systems}, journal = {Concurrency Computation Practice and Experience - John Wiley \& Sons, Inc.}, volume = {23}, number = {11}, year = {2011}, note = {cited By 2}, pages = {1213-1235}, abstract = {

In the last few years, remarkable efforts have been made to extend the Grid paradigm to commercial solutions. Business-oriented grids call for effective Quality of Service strategies able to adapt to different user requirements and to address Service Level Agreements. Performance analysis and prediction with respect to different load conditions or management policies are required to define such strategies. However, the highly distributed nature of Grid systems and the presence of distinct administrative domains make it difficult to carry out performance estimations. In fact, several parameters are involved and the autonomy of each site could make it complex to set them in a proper way. In this paper, we present a non-Markovian Stochastic Petri Net methodology that allows to conduct performance analysis of Grid systems focusing on aspects related to the Virtual Organization as a whole. In particular, different job allocation techniques can be evaluated with respect to both user and provider points-of-view. The influence of different information update policies on the accuracy of the allocation schemes can also be investigated, highlighting the costs/benefits in terms of job waiting time, service availability, and system utilization. The proposed methodology is designed to be as general as possible and it can be applied to analyze a gLite Grid infrastructure taken as case study. {\textcopyright} 2011 John Wiley \& Sons, Ltd.

}, keywords = {Grid computing, Grid infrastructures, Grid systems, Information updates, Job allocation, Load condition, Management policy, Non-Markovian, Performance analysis, Performance estimation, performance measurements, Petri nets, Quality of service, Random access storage, Service availability, Service Level Agreements, Stochastic Petri Nets, Stochastic systems, System utilization, User requirements, Virtual organization, Waiting-time}, issn = {15320626}, doi = {10.1002/cpe.1697}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-79960133545\&partnerID=40\&md5=a557a0ec6dd02249f31a6a0960e2bc92}, author = {Dario Bruneo and Francesco Longo and Marco Scarpa and Antonio Puliafito} } @proceedings {Bruneo2010243, title = {VO-level performance analysis of gLite Grids}, journal = {Proceedings of the 19th IEEE Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)}, year = {2010}, note = {cited By 0; Conference of 19th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE 2010 ; Conference Date: 28 June 2010 Through 30 June 2010; Conference Code:81490}, pages = {243-248}, publisher = {IEEE Computer Society}, address = {Larissa, Greece, 28-30 June 2010}, abstract = {

Business oriented grids call for effective Quality of Service strategies able to adapt to different user requirements. Performance analyses and predictions with respect to different load conditions or management policies are essential instruments to define such strategies. In this paper, we present a non-Markovian Stochastic Petri Net model that allows to conduct performance analyses of Grid systems focusing on aspects related to the Virtual Organization as a whole. Different job allocation techniques will be evaluated with respect to both user and provider point-of-views. We will also investigate the influence of different information update policies on the accuracy of the allocation schemes, highlighting the costs/benefits in terms of job waiting time, service availability, and system utilization. {\textcopyright} 2010 IEEE.

}, keywords = {Business-oriented, gLite middleware, Graph theory, Grid computing, Grid systems, Information updates, Job allocation, Load condition, Management policy, middleware, Non-Markovian, Performance analysis, performance measurements, Petri nets, Quality of service, Random access storage, Service availability, Stochastic models, Stochastic Petri Nets, Stochastic systems, System utilization, User requirements, Virtual organization, Waiting-time}, isbn = {9780769540634}, issn = {15244547}, doi = {10.1109/WETICE.2010.45}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-77955917215\&partnerID=40\&md5=5f89b9d07327325a09d78d1af77f0519}, author = {Dario Bruneo and Francesco Longo and Marco Scarpa and Antonio Puliafito} }