KPI Guarantees in Network Slicing

Autor: Milan Groshev, Jorge Martin-Perez, Francesco Malandrino, Carla-Fabiana Chiasserini, Carlos J. Bernardos
Přispěvatelé: European Commission
Rok vydání: 2022
Předmět:
Zdroj: e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
IEEE/ACM transactions on networking (Online) (2021).
info:cnr-pdr/source/autori:Jorge Martin Perez; Francesco Malandrino; Carla Fabiana Chiasserini; Milan Groshev; Carlos Bernardos/titolo:KPI Guarantees in Network Slicing/doi:/rivista:IEEE%2FACM transactions on networking (Online)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume
ISSN: 1558-2566
1063-6692
DOI: 10.1109/tnet.2021.3120318
Popis: Thanks to network slicing, mobile networks can now support multiple and diverse services, each requiring different key performance indicators (KPIs). In this new scenario, it is critical to allocate network and computing resources efficiently and in such a way that all KPIs targeted by a service are met. Accounting for all sorts of KPIs (e.g., availability and reliability, besides the more traditional throughput and latency) is an aspect that has been scarcely addressed so far and that requires tailored models and solution strategies. We address this issue by proposing a novel methodology and resource orchestration scheme, named OKpi, which provides high-quality decisions on VNF (Virtual Network Function) placement and data routing, including the selection of radio points of attachment. Importantly, OKpi has polynomial computational complexity and accounts for all KPIs required by each service, and for any resource available from the fog to the cloud. We prove several properties of OKpi and demonstrate that it performs very closely to the optimum under real-world scenarios. We also implement OKpi in a testbed supporting a robot-based, smart factory service, and we present some field tests that further confirm the ability of OKpi to make high-quality decisions. This work was supported by the EU Commission through the 5Growth Project under Agreement 856709.
Databáze: OpenAIRE