@conference {8726749,
	title = {Extending Openstack for Cloud-Based Networking at the Edge},
	booktitle = {2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)},
	year = {2018},
	month = {July},
	pages = {162-169},
	abstract = {Cloud-controlled virtual networking at the edge can be considered a critical feature, highly in demand in the IoT infrastructure management domain. Fostering the vision of the Cloud as a suitable control surface for IoT, an integration between the two ecosystems is achievable at a genuinely Infrastructure-as-a-Service level. This work thus describes an integration design between an IoT-centric infrastructure Cloud framework, already capable of limited networking functionality, and Neutron, the networking subsystem belonging to the core services of the OpenStack platform. Design considerations and trade-offs are detailed in the paper.},
	keywords = {Bridges, Cloud, cloud computing, Cloud-controlled virtual networking, control surface, critical feature, Edge computing, IaaS, infrastructure management domain, Infrastructure-as-a-Service level, integration design, Internet of Things, IoT, IoT-centric infrastructure Cloud framework, Linux, network topology, network virtualization, networking functionality, networking subsystem, Neutron, Neutrons, OpenStack, OpenStack platform, Topology, Virtualization},
	doi = {10.1109/Cybermatics_2018.2018.00058},
	author = {Zakaria Benomar and D. Bruneo and S. Distefano and K. Elbaamrani and N. Idboufker and F. Longo and G. Merlino and A. Puliafito}
}
@article {275,
	title = {Energy control in dependable Wireless Sensor Networks: a modeling perspective},
	journal = {PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS. PART O, JOURNAL OF RISK AND RELIABILITY},
	volume = {225},
	year = {2011},
	pages = {424{\textendash}434},
	abstract = {<p>Wireless sensor networks (WSN) are composed of a large number of tiny sensor nodes randomly distributed over a geographical region. In order to reduce power consumption, battery-operated sensors undergo cycles of sleeping-active periods that reduce their ability to send/receive data. Starting from the Markov reward model theory, this paper presents a dependability model to analyse the reliability of a sensor node. Also, a new dependability parameter is introduced, referred to as producibility, which is able to capture the capability of a sensor to accomplish its mission. Two different model solution techniques are proposed, one based on the evaluation of the accumulated reward distribution and the other based on an equivalent model based on non-Markovian stochastic Petri nets. The obtained results are used to investigate the dependability of a whole WSN taking into account the presence of redundant nodes. Topological aspects are taken into account, providing a quantitative comparison among three typical network topologies: star, tree, and mesh. Numerical results are provided in order to highlight the advantages of the proposed technique and to demonstrate the equivalence of the proposed approaches.</p>
},
	keywords = {Energy consumption, Markov reward models, network topology, non-Markovian stochastic Petri nets, producibility, Reliability, Wireless sensor networks},
	doi = {10.1177/1748006X10397845},
	author = {D. Bruneo and A. Puliafito and Marco Scarpa}
}
