@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} } @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} }