Evaluation of PCC Load Balancing for Dual ISP Networks: Enhancing Throughput and Traffic Stability

Bustomi Bustomi; Muhlis Tahir

doi:10.29408/edumatic.v10i1.34243

Authors

Bustomi Bustomi Universitas Trunodjoyo Madura https://orcid.org/0009-0008-1530-1873
Muhlis Tahir Universitas Trunodjoyo Madura https://orcid.org/0000-0001-9205-744X

DOI:

https://doi.org/10.29408/edumatic.v10i1.34243

Keywords:

dual isp, load balancing, mikrotik, network traffic management, per connection classifier

Abstract

Multi-ISP network management often experiences imbalanced traffic distribution and decreased connection stability despite having adequate bandwidth capacity. Previous studies indicate that load balancing methods such as PCC are effective in traffic distribution; however, they remain limited to implementation aspects, with constraints in analyzing network processing efficiency and inconsistencies in results across various testing conditions. This study aims to empirically evaluate the effectiveness of PCC integrated with failover in improving dual ISP network performance. It employs a controlled experimental design with a comparative approach before and after implementation in a real network environment. The measured parameters include throughput, traffic distribution, connection stability, and packet rate, which are analyzed using a quantitative measurement-based comparative approach. The results show an increase in download throughput from 15–18 Mbps to 36–41 Mbps (±130–150%) and upload throughput from 14–17 Mbps to 36–40 Mbps (±120–140%), more balanced traffic distribution, and a significant reduction in packet rate, indicating improved network processing efficiency. The integration of failover also ensures service continuity without significant disruption. This study provides empirical evidence that a connection-based load balancing approach not only improves traffic distribution but also enhances network processing efficiency, extends previous research, and is relevant for multi-ISP networks with dynamic traffic.

References

Abuhamdah, A., & Al-Shabi, M. (2022). Hybrid load-balancing algorithm for fog computing environment. International Journal Of Software Engineering & Computer Systems (IJSECS), 8(1), 11–21. https://doi.org/10.15282/ijsecs.8.1.2022.2.0092

Al Reshan, M. S., Syed, D., Islam, N., Shaikh, A., Hamdi, M., Elmagzoub, M. A., ... & Talpur, K. H. (2023). A fast converging and globally optimized approach for load balancing in cloud computing. IEEE Access, 11, 11390-11404. https://doi.org/10.1109/ACCESS.2023.3241279

Aldossary, D., Aldahasi, E., Balharith, T., & Helmy, T. (2025). A Systematic Literature Review on Load-Balancing Techniques in Fog Computing: Architectures, Strategies, and Emerging Trends. Computers, 14(6), 217. https://doi.org/10.3390/computers14060217

Ali, H., Abouelatta, M. A., & Youssef, K. Y. (2025). Dynamic Connectivity Hub : Multiple ISPs Smart Aggregation for Optimized IoT Connectivity. IEEE Access, 13, 18734–18748. https://doi.org/10.1109/ACCESS.2025.3529486

Amalia, E. R., Nurheki, Saputra, R., Ramadhana, C., & Yossy, E. H. (2022). Computer network design and implementation using load balancing technique with per connection classifier (PCC) method based on MikroTik router. Procedia Computer Science, 216, 103–111. https://doi.org/10.1016/j.procs.2022.12.116

Dong, P., Shen, R., Li, Y., Nie, C., Xie, J., Gao, K., & Zhang, L. (2022). An Energy-Saving Scheduling Algorithm for Multipath TCP in. Electronics, 1–16. https://doi.org/10.3390/electronics11030490

Fathurrohim, M., & Basuki, A. (2025). Evaluation of traffic distribution performance of ECMP and PCC + CAKE for Multi-ISP load balancing on real networks using MikroTik. KINETIK: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 4(4), 583-592. https://doi.org/10.22219/kinetik.v10i4.2374

Jasim, A. M., & Al-raweshidyg, H. (2024). An Adaptive SDN-Based Load Balancing Method for Edge/Fog-Based Real-Time Healthcare Systems. IEEE Systems Journal, 18(2), 1139–1150. https://doi.org/10.1109/JSYST.2024.3402156

Komathi, A., Kishore, S. R., & Velmurugan, A. K. (2024). Network load balancing and data categorization in cloud computing. Indonesian Journal of Electrical Engineering and Computer Science, 35(3), 1942–1951. https://doi.org/10.11591/ijeecs.v35.i3.pp1942-1951

Lilhore, U. K., Simaiya, S., Prajapati, Y. N., Rai, A. K., Ghith, E. S., Tlija, M., Lamoudan, T., & Abdelhamid, A. A. (2025). A multi-objective approach to load balancing in cloud environments integrating ACO and WWO techniques. Scientific Reports, 15. https://doi.org/10.1038/s41598-025-96364-1

Maripini, H., Ghosh, T., & Vanajakshi, L. (2025). Queue Dissipation-Based Max Pressure Signal Control Using Vehicle Re-Identification Data. IEEE Access, 13, 166530–166541. https://doi.org/10.1109/ACCESS.2025.3612125

Nugroho, K. T., Julianto, B., Tisna, D. R., & S, D. F. N. M. (2023). Quality Analysis of Service Load Balancing Using PCC, ECMP, and NTH Methods. Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI, 12(2021), 33–41. https://doi.org//10.23887/janapati.v12i1.55894

Oikonomou, E., & Rouskas, A. (2024). Efficient Schemes for Optimizing Load Balancing and Communication Cost in Edge Computing Networks. Information, 15(11), 670. https://doi.org/10.3390/info15110670

Simone, L. De, Mauro, M. Di, Member, S., Longo, M., Natella, R., Member, S., & Postiglione, F. (2023). Multi-Provider IMS Infrastructure With Controlled Redundancy : A Performability Evaluation. IEEE Transactions on Network and Service Management, 20(4), 3984–3998. https://doi.org/10.1109/TNSM.2023.3282745

Tawfeeg, T. M., Yousif, A., Hassan, A., Alqhtani, S. M., Hamza, R., Bashir, M. B., & Ali, A. (2022). Cloud Dynamic Load Balancing and Reactive Fault Tolerance Techniques : A Systematic Literature Review (SLR). IEEE Access, 10, 71853–71873. https://doi.org/10.1109/ACCESS.2022.3188645

Trung, K. N., & Kim, Y. (2025). Design and Implementation of a Cost-Effective Failover Mechanism for Containerized UPF. Electronics, 14, 1–23. https://doi.org/10.3390/electronics14152991

Verma, L. P., Sharma, V. K., Kumar, M., Kanellopoulos, D., & Mahanti, A. (2022). DB CMT : A New Concurrent Multi path Stream Control. In Journal of Network and Systems Management. Springer US. https://doi.org/10.1007/s10922-022-09677-1

Wiharti, W., Lumasa, I., Rifka, S., Hidayatullah, I., & Febrian, A. (2023). Load Balancing and Fail Over MikroTik Implementation Using Per Connection Classifier (PCC) on Two Internet Providers Interconnection. International Journal of Advanced Science Computing and Engineering, 5(2), 129–135.

Windarta, S., Suryadi, S., Ramli, K., Pranggono, & Surya, B. gunawan T. (2022). Lightweight Cryptographic Hash Functions: Design Trends, Comparative Study, and Future Directions. IEEE Access, 10, 82272–82294. https://doi.org/10.1109/ACCESS.2022.3195572

Zhou, J., Lilhore, U. K., Poongodi, M., Hai, T., Simaiya, S., Norhayati, D., Jawawi, A., Alsekait, D. M., Ahuja, S., Biamba, C., & Hamdi, M. (2023). Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing. Journal of Cloud Computing: Advances, Systems and Applications, 12, 85. https://doi.org/10.1186/s13677-023-00453-3