SMASH: a SMArt Slicing Heterogeneous 5G network selection algorithm

被引：3
|
作者：
Fontana, Alessandra [1 ]
Desogus, Cristina [1 ]
Murroni, Maurizio [1 ]
机构：
[1] Univ Cagliari, Dept Elect & Elect Engn DIEE, Piazza Armi, I-09123 Cagliari, Italy
来源：
2020 IEEE INTERNATIONAL SYMPOSIUM ON BROADBAND MULTIMEDIA SYSTEMS AND BROADCASTING (BMSB) | 2020年
关键词：
traffic and performance monitoring; networking and QoS; congestion control; 5G: new radio and new core; slicing; neural network;
D O I：
10.1109/BMSB49480.2020.9379744
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The aim of this work is to find a possible solution to problems related to the selection of the network in heterogeneous scenarios with the demand for several different services at the same time. Currently, reputation-based network selection algorithms do not take into account different types of traffic. SMASH, addresses network selection through a reputation algorithm, network slicing and neural networks and presents a new solution to improve the exploitation of resources by controlling congestion and improving network performance in terms of QoS parameters such as the average throughput, packet loss ratio and packet delay.
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页数：6
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