@proceedings {Tapas2018411, title = {Blockchain-Based IoT-cloud authorization and delegation}, journal = {Proceedings - 2018 IEEE International Conference on Smart Computing, SMARTCOMP 2018}, year = {2018}, note = {cited By 0; Conference of 4th IEEE International Conference on Smart Computing, SMARTCOMP 2018 ; Conference Date: 18 June 2018 Through 20 June 2018; Conference Code:138285}, pages = {411-416}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, address = {Taormina, Italy - 18-20 June 2018}, abstract = {

In a Smart City scenario, the authors envisioned an IoT-Cloud framework for the management of boards and resources scattered over a geographic area. It can also become a tool to let device owners contribute freely to the infrastructure. In comparison to datacenter-oriented Cloud middleware, the administrator and the owner of the infrastructure are not one and the same. This translates into the requirement to support delegation-enabled authorization. In this paper, the authors investigate an authorization and delegation model for the IoT-Cloud based on blockchain technology. In particular, the scheme is implemented in the form of smart contracts over the Ethereum platform. Indeed, this approach represents an enhancement, over a function previously designed in a centralized fashion, by enabling the user to audit authorization operations and inspect how access control is actually performed, without blindly trusting the Cloud as a proxy for access to resources. {\textcopyright} 2018 IEEE.

}, keywords = {Access control, Access to resources, authorization, Blockchain, Cloud middlewares, Clouds, Delegation, Delegation modeling, Ethereum, Geographic areas, Internet of Things, middleware, Smart city, Smart contracts}, isbn = {9781538647059}, doi = {10.1109/SMARTCOMP.2018.00038}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051495365\&doi=10.1109\%2fSMARTCOMP.2018.00038\&partnerID=40\&md5=57e82ce12e19c3286c34b0612a587237}, author = {Nachiket Tapas and Giovanni Merlino and Francesco Longo} } @proceedings {Tricomi2017, title = {Orchestrated Multi-Cloud Application Deployment in OpenStack with TOSCA}, journal = {2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017}, year = {2017}, note = {cited By 0; Conference of 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017 ; Conference Date: 29 May 2017 Through 31 May 2017; Conference Code:128356}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, address = {Hong Kong; China; 29-31 May 2017}, abstract = {

Cloud computing is becoming a relatively mature paradigm in the ICT landscape. In light of the growing appetite for resources and service levels on par with user expectations, multi-cloud scenarios are becoming the next frontier in the usage of distributed datacenters for private and hybrid Cloud scenarios. Application deployment in particular is a noteworthy feature to be evaluated as microservices become mainstream in adoption. Especially so when considered jointly with orchestration services; indeed OpenStack, as the most widely adopted Cloud middleware among the OpenSource community, features an orchestration subsystem, and may orchestrate the deployment of applications and services. In this work the authors will describe an architecture, developed within the H2020 BEACON project, for a standardized approach to orchestrated application deployment in multi-Cloud OpenStack-based setups, with TOSCA providing the specifications. {\textcopyright} 2017 IEEE.

}, keywords = {Cloud federations, deployment, microservices, middleware, Multi-clouds, OpenStack, orchestration, Platform as a Service (PaaS), TOSCA}, isbn = {9781509065172}, doi = {10.1109/SMARTCOMP.2017.7947027}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85023168002\&doi=10.1109\%2fSMARTCOMP.2017.7947027\&partnerID=40\&md5=94bbf6ca2fa1b1d2b92047683723948c}, author = {Giuseppe Tricomi and Alfonso Panarello and Giovanni Merlino and Francesco Longo and Dario Bruneo 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} }