@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 = {<p>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.</p>
},
	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 {Marquezan201555,
	title = {3-D cloud monitoring: Enabling effective cloud infrastructure and application management},
	journal = {Proceedings of the 10th International Conference on Network and Service Management (CNSM)},
	year = {2014},
	note = {cited By 0; Conference of 10th International Conference on Network and Service Management, CNSM 2014 ; Conference Date: 17 November 2014 Through 21 November 2014; Conference Code:110192},
	pages = {55-63},
	publisher = {IEEE Computer Society},
	address = {Rio de Janeiro, Brazil, 17-21 November 2014},
	abstract = {<p>A cloud environment is a complex environment composed of many different entities and layers. Each of these cloud entities may be furnished with mechanisms offering various management actions. For any given situation, different management actions may be applicable and often simultaneously. Enforcing isolated management actions or combining contradictory management actions may negatively affect cloud application quality and cloud infrastructure performance. This means that correctly selecting and effectively combining these management actions for a given situation becomes an important challenge in cloud computing. In this paper, we address the problem of identifying situations where more than one management action can be performed. The key contributions of our paper are: (1) a three dimensional (3-D) monitoring model for analyzing cloud monitoring information; (2) the concept and formalization of Context of Interest (CoI) that specifies how to retrieve meaningful information from the 3-D model to support the coordination of management actions between cloud infrastructure and application. We conducted experiments in a real testbed using Openstack and the WordPress Web site application. Our results show that analyzing cloud monitoring information using the 3-D model and the CoI can support a more effective identification of management actions to be taken. {\textcopyright} 2014 IFIP.</p>
},
	keywords = {Application management, Cloud applications, Cloud environments, Cloud infrastructures, Complex environments, Complex networks, Formalization of context, Monitoring models, Three dimensional computer graphics, Threedimensional (3-d)},
	isbn = {9783901882661},
	doi = {10.1109/CNSM.2014.7014141},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84922823116\&partnerID=40\&md5=14afe05eea8a48d4fc7c6c8e57dd6208},
	author = {Clarissa Marquezan and Dario Bruneo and Francesco Longo and Florian Wessling and Andreas Metzger and Antonio Puliafito}
}
