@proceedings {Puliafito201897,
	title = {Companion fog computing: supporting things mobility through container migration at the edge},
	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 = {97-105},
	publisher = {Institute of Electrical and Electronics Engineers Inc.},
	address = {Taormina, Italy - 18-20 June 2018},
	abstract = {<p>Due to their intrinsic resource constraints, the mobile Internet of Things (IoT) devices are not able to provide intensive services by just relying on their own facilities. Fog Computing effectively helps overcome this hurdle. Indeed, it extends the Cloud toward the network edge, distributing resources and services of computing, storage, and networking close to the end devices. This topological proximity is the key enabler of several advantages that are essential in many emerging ICT domains. Nonetheless, the mobility of an IoT device compromises such benefits as it increases the topological distance to the serving Fog node. Therefore, the Fog service has to be migrated in order to be always close enough to the served IoT device. We name this Companion Fog Computing (CFC), since the Fog service behaves as a {\textquoteright}companion{\textquoteright} of the correspondent application on the mobile device. In this paper, we present a Fog Computing Platform that performs stateful container (i.e., Fog service) migrations in order to enable CFC. Specifically, we introduce a CFC model from which we derive a reference architecture comprising all the functionalities required in a platform to make migration decisions and carry them out. Moreover, we demonstrate the soundness of the proposed reference architecture by discussing a proof-of-concept implementation based on the Stack4Things (S4T) platform, and we report a set of conducted experiments to show the feasibility of stateful container migrations. {\textcopyright} 2018 IEEE.</p>
},
	keywords = {Carrier mobility, Computing platform, containers, Docker, Fog, Fog computing, Internet of Things, Migration, Mobile devices, Network architecture, Proof of concept, Reference architecture, Resource Constraint, Topological distance, Topological proximity, Topology},
	isbn = {9781538647059},
	doi = {10.1109/SMARTCOMP.2018.00079},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051489867\&doi=10.1109\%2fSMARTCOMP.2018.00079\&partnerID=40\&md5=4a8069123a5f19d5e842a86b2e9163f4},
	author = {Carlo Puliafito and Enzo Mingozzi and Carlo Vallati and Francesco Longo and Giovanni Merlino}
}
@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 {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 = {<p>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.</p>
},
	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}
}
