Journal of Computer Science and Informatics Engineering
Vol 5 No 3 (2026): July

Optimizing FTP Server Performance Using the Locality-Based Least Connection (LBLC) Algorithm in a Scheduling Algorithm Balancing System

Ahmad Ridwan (Universitas AMIKOM Yogyakarta)
Pramawahyudi Pramawahyudi (Universitas Andalas)
Enda Putri Atika (Universitas AMIKOM Yogyakarta)
Budi Bayu Murti (Universitas Gadjah Mada)
Muzakki Ahmad (Universitas AMIKOM Yogyakarta)



Article Info

Publish Date
16 Jul 2026

Abstract

A simultaneous increase in internet user traffic often causes servers to become overloaded, leading to disruptions, particularly on File Transfer Protocol (FTP) servers. A load-balancing system using Linux Virtual Servers is a solution for distributing traffic evenly. This study aims to analyze the performance of ten scheduling algorithms in a load-balancing system for File Transfer Protocol server applications with an Internet Protocol tunnel topology. The research method involves implementing a server cluster using the Debian operating system with one load-balancing server and two real servers. This topology allows the real servers to be located on geographically separate networks. Performance testing was conducted on ten different scheduling algorithms using five simultaneous clients, measuring response time and throughput using network analysis software. The test results showed that the Least Connections Based on Locality algorithm provided the most optimal performance compared to the other algorithms. The algorithm recorded the lowest average response time of 0.6066 seconds and the highest average throughput of 43 kilobits per second. These results are significantly better than those from tests without a load-balancing system, which yielded a response time of 2.7332 seconds. It can be concluded that the Least Connections Based on Locality algorithm is the most effective when applied to File Transfer Protocol servers with an Internet Protocol tunnel topology to improve network service quality.

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Journal Info

Abbrev

cosie

Publisher

Subject

Computer Science & IT

Description

Artificial Intelligence Machine Learning Natural Language Processing Computer Vision Text Speech Text Mining Data mining Cryptography Data visualization Expert System Deep Learning Fuzzy Logic IoT and smart environments Neural Networks Pattern Recognition Image Processing Optimization Digital Signal ...