A lot of research is being carried out about Internet of Things (IoT) and in the following years it will emerge more and more in our lives. Furthermore, with the advent of future fully-integrated 5G networks, new constraints need to be satisfied such as ultra-reliability and low-latency. With the help of Fog computing and the Multi-access Edge Computing (MEC) framework, services can be offered to the end users in a fast and practical way. Our work presents DRIVE a framework for service discovery in a 5G environment. However, in order to guarantee dynamic distribution and best management of services, we plan to deploy those services as container (e.g. Docker container). Moreover, we propose distribution of edge services at three different layer of communication: Application, Service, and Communication Layer. Given the above considerations, we propose an edge node, placed at the edge of network, that acts as the «brain» and take over the computation. The main innovative elements of the proposed framework, compared to the existing literature, include the possibility to select the working layer, the dynamic reconfiguration of the edge node and the field experimental results about the performance achieved by our solution over rapidly deployable environments with resourcelimited edge nodes such as Raspberry Pi devices.

DRIVE: Discovery seRvice for fully-Integrated 5G enVironmEnt in the IoT / Bellavista, Paolo; Foschini, Luca; Scotece, Domenico; Karypidou, Kyriaki; Chatzimisios, Periklis. - ELETTRONICO. - 2018-:(2018), pp. 8514999.1-8514999.6. (Intervento presentato al convegno 23rd IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2018 tenutosi a esp nel 2018) [10.1109/CAMAD.2018.8514999].

DRIVE: Discovery seRvice for fully-Integrated 5G enVironmEnt in the IoT

Bellavista, Paolo;Foschini, Luca;Scotece, Domenico;
2018

Abstract

A lot of research is being carried out about Internet of Things (IoT) and in the following years it will emerge more and more in our lives. Furthermore, with the advent of future fully-integrated 5G networks, new constraints need to be satisfied such as ultra-reliability and low-latency. With the help of Fog computing and the Multi-access Edge Computing (MEC) framework, services can be offered to the end users in a fast and practical way. Our work presents DRIVE a framework for service discovery in a 5G environment. However, in order to guarantee dynamic distribution and best management of services, we plan to deploy those services as container (e.g. Docker container). Moreover, we propose distribution of edge services at three different layer of communication: Application, Service, and Communication Layer. Given the above considerations, we propose an edge node, placed at the edge of network, that acts as the «brain» and take over the computation. The main innovative elements of the proposed framework, compared to the existing literature, include the possibility to select the working layer, the dynamic reconfiguration of the edge node and the field experimental results about the performance achieved by our solution over rapidly deployable environments with resourcelimited edge nodes such as Raspberry Pi devices.
2018
IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD
1
6
DRIVE: Discovery seRvice for fully-Integrated 5G enVironmEnt in the IoT / Bellavista, Paolo; Foschini, Luca; Scotece, Domenico; Karypidou, Kyriaki; Chatzimisios, Periklis. - ELETTRONICO. - 2018-:(2018), pp. 8514999.1-8514999.6. (Intervento presentato al convegno 23rd IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2018 tenutosi a esp nel 2018) [10.1109/CAMAD.2018.8514999].
Bellavista, Paolo; Foschini, Luca; Scotece, Domenico; Karypidou, Kyriaki; Chatzimisios, Periklis
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/663608
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact