Comparative Analysis of PCC Load Balancing and Quality of Service (QoS) Queue Tree Methods on Mikrotik for Bandwidth Optimization

The increasing demand for fast, stable, and efficient Internet connectivity requires optimal bandwidth management, especially in PLN's operational networks. This study analyzes and compares two MikroTik bandwidth management methods, namely Per Connection Classifier (PCC) Load Balancing and Quality of Service (QoS) Queue Tree, to optimize network performance. An experimental approach was conducted under three traffic conditions: low, medium, and high. The evaluation focused on key network parameters, including throughput, latency, packet loss, and connection stability. The results indicate that PCC Load Balancing achieves higher throughput and more effective traffic distribution across multiple Internet Service Providers (ISPs), making it suitable for networks with many general users. In contrast, QoS Queue Tree provides lower latency and jitter while ensuring better traffic prioritization for critical services such as SCADA systems and internal communications. Therefore, PCC is more effective in maximizing bandwidth utilization, whereas QoS Queue Tree offers superior service quality and network stability. A hybrid implementation of both methods is recommended to achieve optimal efficiency and performance in PLN operational environments.