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- W4387065178 abstract "Traffic in the 5G network is growing exponentially and is predictable to grow in the future. Providing a high quality of service with ever-increasing traffic volumes is challenging in 5G networks. Software defined networking (SDN) along with emerging cloud technologies plays a significant responsibility in enhancing the performance of 5G networks. The 5G SDN paradigm is designed to support real-time and latency-sensitive applications. This chapter aims to summarize the existing technologies, benefits, and challenges of the 5G network. Also, a novel multivariate traffic analysis framework using time series analysis is proposed to enhance traffic management and its performance. Evaluation is performed on open traffic flow datasets and the analysis results show that the proposed framework performs better despite the inherent uncertainty in terms of classification and forecast accuracy." @default.
- W4387065178 created "2023-09-27" @default.
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- W4387065178 date "2023-09-26" @default.
- W4387065178 modified "2023-10-14" @default.
- W4387065178 title "Traffic Management of SDN/NFV-Based Smart 5G Networks Using Time Series Analysis" @default.
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- W4387065178 doi "https://doi.org/10.4018/979-8-3693-0744-1.ch009" @default.
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