Skripsi
ANALISA LOAD BALANCING PADA CLOUD COMPUTING MENGGUNAKAN METODE LEAST CONNECTION
Cloud computing provides dynamic computing resources over a network. However, an increasing number of user requests can lead to higher server workloads and decreased service performance. This study aims to analyze the performance of load balancing using the Least Connection method with HAProxy as the load balancer. The system was implemented in a VMware-based virtual machine environment consisting of one client, one load balancer, and three Apache backend servers. Performance testing was conducted using Apache JMeter with gradually increasing numbers of users. The Quality of Service (QoS) parameters analyzed include throughput, delay, packet loss, jitter, error rate, and response time. The results show that the Least Connection method effectively distributes traffic based on active connections, resulting in more balanced load distribution. Although delay and response time increased under higher workloads, the system remained stable with a low error rate. Therefore, this method is considered effective in improving the performance and reliability of cloud computing services.
| Title | Edition | Language |
|---|---|---|
| IMPLEMENTASI SISTEM DETEKSI ATRIAL FIBRILASI BERBASIS KOMPUTASI AWAN MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK | id |