Perbandingan Performa Algoritma Load Balancing Least Connection Dan Source IP Hash Pada Web Server Berbasis Software Defined Network

Gihon Mahendra(1*), Abd Hadi(2),

(1) Institut Teknologi dan Bisnis Asia Malang, Indonesia
(2) Institut Teknologi dan Bisnis Asia Malang, Indonesia
(*) Corresponding Author

Abstract


The increasing number of internet users demands more efficient server infrastructure, particularly in handling high client request volumes. One common issue faced by web servers is overload, which can lead to server unresponsiveness or even downtime. A solution to address this problem is the implementation of load balancing techniques. This study compares the performance of two commonly used load balancing algorithms, namely Least Connection and Source IP Hash, within a Software Defined Network-based web server architecture. The implementation was conducted using Mininet as a network simulator and POX as the controller. The testing environment consisted of three servers and three clients, with simulation scenarios involving 3,000 requests at three different connection rates: 75, 150, and 300 connections per second. The results indicate that the Least Connection algorithm is more adaptive to increasing loads, as it distributes requests based on the number of active connections on each server. This leads to more stable server responses and reduces the likelihood of packet loss. On the other hand, the Source IP Hash algorithm uses a hashing technique based on the user's IP address to direct requests to consistent servers, effectively maintaining session stability. However, it poses the risk of uneven load distribution when traffic dynamically changes. This algorithm also demonstrated better packet delivery stability (jitter), particularly under high load scenarios. Based on the analysis, it can be concluded that the Least Connection algorithm is more suitable for high and dynamic load network environments, while the Source IP Hash algorithm is better suited for systems requiring consistent client-server connection sessions.

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DOI: https://doi.org/10.30645/kesatria.v6i2.602

DOI (PDF): https://doi.org/10.30645/kesatria.v6i2.602.g597

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