A Queuing based Dynamic Auto Scaling Algorithm for the LTE EPC Control Plane

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2018 IEEE Global Communications Conference, GLOBECOM 2018, IEEE Global Communications Conferences
Network softwarization paradigm, whose main enabler is Network Functions Virtualization (NFV), facilitates the automation of the management operations and orchestration of the future networks, thus reducing the operational expenditures of the network. The envisioned management practices include the introduction of automation in the scaling of network services. This may enable operators to handle workload fluctuations to keep the desired performance with great agility and reduced costs. This procedure introduces a non-negligible delay in allocating or releasing virtual resources. Therefore, waiting until the system is overloaded or underutilized so as to scale resources up or down could negatively impact user Quality of Experience, or lead to inefficient resource utilization. In this vein, this paper proposes a novel and agile Dynamic Auto Scaling Algorithm for the Long Term Evolution (LTE) virtualized Evolved Packet Core (vEPC) Control Plane (CP). The resources dimensioning stage of the algorithm is based on an original queuing model for the LTE CP. To model the LTE CP, we use an open network of G/G/m queues. We also provide expressions to derive the steady state transition probabilities of the queuing network. Finally, we validate the proper operation of our solution using accurate simulation tools.
| openaire: EC/H2020/723172/EU//5GPagoda
queuing model, dimensioning, LTE EPC, control plain, NFV, network softwarization, dynamic resource provisioning, dynamic auto scaling algorithm
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Prados-Garzon , J , Laghrissi , A , Bagaa , M & Taleb , T 2018 , A Queuing based Dynamic Auto Scaling Algorithm for the LTE EPC Control Plane . in 2018 IEEE Global Communications Conference, GLOBECOM 2018 . IEEE Global Communications Conferences , IEEE , IEEE Global Communications Conference , Abu Dhabi , United Arab Emirates , 09/12/2018 . https://doi.org/10.1109/GLOCOM.2018.8648023