@article {Longo2015280, title = {Dependability modeling of Software Defined Networking}, journal = {Computer Networks}, volume = {83}, year = {2015}, note = {cited By 6}, pages = {280-296}, publisher = {Elsevier}, abstract = {

Software Defined Networking (SDN) is a new network design paradigm that aims at simplifying the implementation of complex networking infrastructures by separating the forwarding functionalities (data plane) from the network logical control (control plane). Network devices are used only for forwarding, while decisions about where data is sent are taken by a logically centralized yet physically distributed component, i.e., the SDN controller. From a quality of service (QoS) point of view, an SDN controller is a complex system whose operation can be highly dependent on a variety of parameters, e.g., its degree of distribution, the corresponding topology, the number of network devices to control, and so on. Dependability aspects are particularly critical in this context. In this work, we present a new analytical modeling technique that allows us to represent an SDN controller whose components are organized in a hierarchical topology, focusing on reliability and availability aspects and overcoming issues and limitations of Markovian models. In particular, our approach allows to capture changes in the operating conditions (e.g., in the number of managed devices) still allowing to represent the underlying phenomena through generally distributed events. The dependability of a use case on a two-layer hierarchical SDN control plane is investigated through the proposed technique providing numerical results to demonstrate the feasibility of the approach. {\textcopyright} 2015 Elsevier B.V.

}, keywords = {Availability, Complex networks, Controllers, Degree of distributions, Distributed components, Electric network topology, Information dissemination, Markov processes, Networking infrastructure, Non-Markovian, Quality control, Quality of service, Random processes, Reliability, Reliability and availability, Software defined networking (SDN), Software reliability, Software-defined networkings, Stochastic models, Stochastic systems, Topology, Type expansions}, issn = {13891286}, doi = {10.1016/j.comnet.2015.03.018}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946489290\&doi=10.1016\%2fj.comnet.2015.03.018\&partnerID=40\&md5=b4f32c89d2b7b79fefcaf97082764960}, author = {Francesco Longo and Salvatore Distefano and Dario Bruneo and Marco Scarpa} } @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 {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} }