Tesi etd-08202020-121548
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Tipo di tesi
Master di Primo Livello
Autore
TADESSE, TEWODROS GASHAW
Indirizzo email
tewodrosg.tadesse@gmail.com
URN
etd-08202020-121548
Titolo
Achieving Deterministic Latency for Optical Metro Network with Edge Computing
Struttura
Istituto di Tecnologie della Comunicazione, dell'Informazione e della Percezione
Corso di studi
Corsi Alta Formazione - PHOTONIC INTEGRATED CIRCUITS, SENSORS AND NETWORKS (PIXNET)
Commissione
relatore Prof. CASTOLDI, PIERO
Relatore Prof. CALABRETTA, NICOLA
Relatore Prof. CALABRETTA, NICOLA
Parole chiave
- 5G
- data center
- deterministic latency
- jitter
Data inizio appello
08/09/2020;
Disponibilità
completa
Riassunto analitico
The future optical metro network with edge computing should provide low and deterministic latency service to support mission-critical applications with the other traffics. Due to a lack of flexibility, high latency, and jitter, the conventional network architecture can't fulfill these critical applications' QoS requirements. Thus, we need a dynamic and fast reconfigurable network. Using the novel metro network model introduced in our colleagues' recent study, in this paper, we proposed and implemented a prioritization method at the scheduler and jitter compensation mechanism in the top-of-rack (TOR) switch to achieve deterministic latency for mission-critical applications. We numerically investigate the performance of the proposed methods via the OMNET++ simulator in terms of latency, jitter, and packet loss ratio under different edge node locations. The numerical analysis also includes the other two application types (Massive Internet of Things, and content delivery network) to examine the impact of the methods on the remaining traffic flow. Considering a typical metro access network topology with 20 nodes that serves around 1 million population, we have achieved 65 μs deterministic latency with 37 ps jitter, and 8E-7 packet loss ratio at load 0.5 for mission-critical applications by allocating ten edge computing nodes.
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Tadessetesi.pdf | 2.02 Mb |
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