Web Server Performance Improvement Using Dynamic Load Balancing Techniques: A Review

Abstract

Today, web services rapidly increased and are accessed by many users, leading to massive traffic on the Internet. Hence, the web server suffers from this problem, and it becomes challenging to manage the total traffic with growing users. It will be overloaded and show response time and bottleneck, so this massive traffic must be shared among several servers. Therefore, the load balancing technologies and server clusters are potent methods for dealing with server bottlenecks. Load balancing techniques distribute the load among servers in the cluster so that it balances all web servers. The motivation of this paper is to give an overview of the several load balancing techniques used to enhance the efficiency of web servers in terms of response time, throughput, and resource utilization. Different algorithms are addressed by researchers and get good results like the pending job, and IP hash algorithms achieve better performance.

Simulasi Implementasi Load Balancing pada Jaringan Internet dengan Metode Per Connection Classifier (PCC) dan Server dengan Metode IP Hash Menggunakan GNS3

“…Selanjutnya, Bhayangkara dan Riadi (2014) membahas implementasi proxy server dan load balancing menggunakan Mikrotik dalam studi kasus Shmily.net, yang menghasilkan peningkatan keandalan koneksi internet secara real-time [17]. Analisis terhadap metode load balancing juga dilakukan oleh Amalia (2020) dalam lingkungan virtual OpenStack, dapat meningkatkan kinerja web server melalui teknik ini [18]. Sementara itu, penelitian Ohyver dan Chandra (2023) mengenai simulasi keamanan jaringan dengan menggunakan OpenvSwitch dan NIDS menunjukkan tingkat keberhasilan yang signifikan dalam mendeteksi serangan DOS [19].…”

Performance Efficiency Evaluation based on ISO/IEC 25010:2011 applied to a Case Study on Load Balance and Resilient

“…Software solutions, on the other hand, involve installing additional programs or nodes and using a load-balancing algorithm. In general, this approach is more flexible and cost-effective than hardware-based solutions [Ibrahim et al 2021].…”