Modeling Mobile Edge Computing Deployments for Low Latency Multimedia Services

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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.
5G, Mec, Point Process, Deployment, Characterization, Network Slicing, Streaming, Low Latency, Augmented Reality, Virtual Reality.
Bibliographic citation
Martín Pérez, J., Cominardi, L., Bernardos, C.J., Oliva, A. de la y Azcorra, A. (2019). Modeling Mobile Edge Computing Deployments for Low Latency Multimedia Services. IEEE Transactions on Broadcasting