A Complete LTE Mathematical Framework for the Network Slice Planning of the EPC

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Date

2020-01-01

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en

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IEEE Transactions on Mobile Computing

Abstract

5G is the next telecommunications standards that will enable the sharing of physical infrastructures to provision ultra short-latency applications, mobile broadband services, Internet of Things, etc. Network slicing is the virtualization technique that is expected to achieve that, as it can allow logical networks to run on top of a common physical infrastructure and ensure service level agreement requirements for different services and applications. In this vein, our paper proposes a novel and complete solution for planning network slices of the LTE EPC, tailored for the enhanced Mobile BroadBand use case. The solution defines a framework which consists of: i) an abstraction of the LTE workload generation process, ii) a compound traffic model, iii) performance models of the whole LTE network, and iv) an algorithm to jointly perform the resource dimensioning and network embedding. Our results show that the aggregated signaling generation is a Poisson process and the data traffic exhibits self-similarity and long-range-dependence features. The proposed performance models for the LTE network rely on these results. We formulate the joint optimization problem of resources dimensioning and embedding of a virtualized EPC and propose a heuristic to solve it. By using simulation tools, we validate the proper operation of our solution.

Description

| openaire: EC/H2020/723172/EU//5GPagoda

Keywords

LTE, EPC, network slicing, NFV, softwarized networks, mobile networks, traffic characterization, resources dimensioning, network embedding

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Citation

Prados-Garzon , J , Laghrissi , A , Bagaa , M , Taleb , T & M. Lopez-Soler , J 2020 , ' A Complete LTE Mathematical Framework for the Network Slice Planning of the EPC ' , IEEE Transactions on Mobile Computing , vol. 19 , no. 1 , 8603789 , pp. 1-14 . https://doi.org/10.1109/TMC.2018.2890235