SMASH: a SMArt Slicing Heterogeneous 5G network selection algorithm
| Autor: | Cristina Desogus, Alessandra Fontana, Maurizio Murroni |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
Network packet Quality of service Distributed computing 020206 networking & telecommunications Throughput 02 engineering and technology 01 natural sciences 010309 optics Network congestion Packet loss 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Network performance Selection algorithm Selection (genetic algorithm) |
| Zdroj: | BMSB |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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