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Modeling Mobile Edge Computing Deployments for Low Latency Multimedia Services

delete2019-06-01
delete45
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OA
AI
J
Jorge Martín‐Pérez *
L
Luca Cominardi
C
Carlos J. Bernardos
A
Antonio de la Oliva
A
Arturo Azcorra
DOI:10.1109/TBC.2019.2901406delete
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Abstract

Abstract

En 中文
Multi-access edge computing (MEC) technologies bring important improvements in terms of network bandwidth, latency, and use of context information and critical for services like multimedia streaming, augmented, and virtual reality. In future deployments, operators will need to decide how many MEC points of presence (PoPs) are needed and where to deploy them, also considering the number of base stations needed to support the expected traffic. This paper presents an application of inhomogeneous Poisson point processes with hard-core repulsion to model feasible MEC infrastructure deployments. With the presented methodology a mobile network operator knows where to locate the MEC PoPs and associated base stations to support a given set of services. We evaluate our model with simulations in realistic scenarios, namely Madrid City Center, an industrial area and a rural area.
Keywords:
5G
MEC
point process
deployment
characterization
network slicing
streaming
low latency
augmented reality
virtual reality
AI Summary

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Journal

IEEE Transactions on Broadcasting cover
IEEE Transactions on Broadcasting
IF:
4.8
Papers:
2.1K
Citations:
3.0K

Organization

U
Universidad Carlos III de Madrid
Scholars:
5.5K
Papers: 5.7K
Citations: 4.5K