Edge-Assisted Congestion Control Mechanism for 5G Network Using Software-Defined Networking

TL;DR

This paper presents a MEC-based congestion control mechanism for 5G networks that uses real-time network data and a dedicated engine to optimize traffic buffering and offloading, improving congestion management.

Contribution

It introduces a novel congestion control engine integrated with MEC and SDN to enable real-time, intelligent traffic management in 5G networks.

Findings

The mechanism effectively alleviates network congestion.

Real-time decision-making improves QoS for high-priority traffic.

Analytical results confirm enhanced congestion control efficiency.

Abstract

In order to cope with the explosive growth of data traffic which is associated with a wide plethora of emerging applications and services that are expected to be used by both ordinary users and vertical industries, the congestion control mechanism is considered to be vital. In this paper, we proposed a congestion control mechanism that could function within the framework of Multi-Access Edge Computing (MEC). The proposed mechanism is aiming to make real-time decisions for selectively buffering traffic while taking network condition and Quality of Service (QoS) into consideration. In order to support a MEC-assisted scheme, the MEC server is expected to locally store delay-tolerant data traffics until the delay conditions expire. This enables the network to have better control over the radio resource provisioning of higher priority data. To achieve this, we introduced a dedicated function known as Congestion Control Engine (CCE), which can capture Radio Access Network (RAN) condition through Radio Network Information Service (RNIS) function, and use this knowledge to make the real-time decision for selectively offloading traffic so that it can perform more intelligently. Analytical evaluation results of our proposed mechanism confirm that it can alleviate network congestion more efficiently.