@article { 11570_3131536, title = {A Novel IoT-as-a-Service Strategy to Achieve Energy and Cost Saving In Microgrids}, journal = {INTERNATIONAL JOURNAL OF ENGINEERING \& TECHNOLOGY}, volume = {7}, year = {2018}, pages = {120{\textendash}123}, abstract = {Smart Grids play a crucial role for always more efficient, flexible and reliable integration of technologies in the electricity marketplace. At the {\textquotedblleft}edge{\textquotedblright} of Smart Grids, appliances and consumer devices consume electricity by Microgrids. End-users need easily and dynamically accessible electricity marketplace and heterogeneous renewable energy sources (e.g., solar, wind, etc.), in order to satisfy energy needs. This implies two main challenges: 1) managing the variable availability of renewables, mainly due both to variable electricity marketplace conditions and to a not-continuous energy sourcing; 2) managing the energy supply/demand ratio especially in presence of scarcity or surplus conditions in the electrical energy providing service. In this paper the authors propose a novel two-levels Internet of Things-as-a-Service (IoTaaS) strategy to {\textquotedblleft}win{\textquotedblright} the above-mentioned challenges.}, keywords = {cloud computing, energy management, Internet of Things, IoTaaS, smart grids}, doi = {10.14419/ijet.v7i4.16}, url = {https://www.sciencepubco.com/index.php/ijet/article/view/21767}, author = {Giacobbe, Maurizio and Puliafito, Antonio and Scarpa, Marco Lucio and Xibilia, Maria Gabriella} } @article {Distefano201722, title = {Marking dependency in non-Markovian stochastic Petri nets}, journal = {Performance Evaluation}, volume = {110}, year = {2017}, note = {cited By 0}, pages = {22-47}, publisher = {Elsevier B.V.}, abstract = {

Marking dependency is a powerful tool that allows different firing time distributions to be associated with a stochastic Petri net transition, depending on the marking. Through this feature, the modeler can easily and compactly represent advanced properties and behaviors of the system. While a semantics and specific solution techniques have been provided for generalized stochastic Petri nets thus covering homogeneous Markovian aspects, in the non-homogeneous/non-Markovian case marking dependency still needs to be investigated. To fill this gap, this paper provides a formalization of marking dependent semantics in non-Markovian stochastic Petri nets (NMSPNs) and a solution technique, based on phase type distributions and Kronecker algebra, able to deal with such a feature allowing both transient and steady-state analyses. To motivate the actual need of marking dependency in NMSPN modeling and to demonstrate the potential of such a feature as well as the validity of the proposed solution technique a case study on a multi-core CPU system with power management facilities is explored. {\textcopyright} 2017 Elsevier B.V.

}, keywords = {Algebra, energy management, Kronecker algebra, Marking dependency, Multi-core cpus, non-Markovian stochastic Petri nets, Petri nets, phase type distributions, Power management, Program processors, Random access storage, Semantics, Stochastic systems}, issn = {01665316}, doi = {10.1016/j.peva.2017.03.001}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016027299\&doi=10.1016\%2fj.peva.2017.03.001\&partnerID=40\&md5=a00a4d3147bd499b5f8879d3573b4670}, author = {Salvatore Distefano and Francesco Longo and Marco Scarpa} } @proceedings {479, title = {Re-Powering Service Provisioning Through Virtual Machine Migration in Federated Cloud Environments: An Algorithm Combining Energy Sustainability and Cost-Saving Strategies}, journal = {The 4th International Workshop on CLoud for IoT (CLIoT 2016)}, volume = {Advances in Service-Oriented and Cloud Computing}, year = {2016}, month = {01/2018}, pages = {19-33}, publisher = {Springer International Publishing}, address = {Vienna, Austria}, abstract = {

Cloud federation offers new business models to enforce more flexible energy management strategies. Typically, an independent Cloud provider is exclusively bounded to the specific energy supplier powering its data center. The situation radically change if we consider a federation of cooperating Cloud providers. In such a context a proper migration of virtual machines among providers can lead to global energy sustainability and cost-saving strategies.\ 
In this paper, we discuss a decision algorithm, for Cloud federation brokerage, able to combine these two strategies. More specifically, we present a Multi-Criteria Decision Making (MCDM) algorithm able to discover the most convenient Cloud provider candidates to join a particular energy-aware federation. In the end, by modelling different possible real Cloud providers, we demonstrate how the algorithm can accommodate different Cloud federation scenarios characterized by particular energy-aware parameters.

}, keywords = {cloud brokerage, cloud computing, cloud federation, energy cost-saving, Energy Efficiency, energy management, Energy Sustainability}, issn = {978-3-319-72125-5}, doi = {10.1007/978-3-319-72125-5_2}, author = {Maurizio Giacobbe and Antonio Celesti and Maria Fazio and Massimo Villari and Antonio Puliafito} }