<![CDATA[Judging from daily activities, human beings heavily rely on the internet for communication purposes. and exchange information using either social media applications or browsers, vonsistently fast internet speeds are incredibly beneficial for performing tasks and activities, particularly for students and professionals. A sluggish internet connection can be frustrating and may lead to interruptions in online activities and tasks if it persists. Hence, this study examines a comparative evaluation of two approaches, Per Connection Classifier (PCC) and Equal Cost Multi-Path (ECMP) in Load Balancing through GNS3 simulation. Load balancing, as a method for evenly distributing traffic loads, and failover, as a backup mechanism when the main connection experiences problems. GNS3 is a graphical network simulator program that can transmit more complex network topologies compared to other simulators, for example Cisco Packet Tracer. The primary aim of this study is to comprehend how efficiently both techniques distribute traffic loads, maintaining smooth internet access, and increasing reliability. The PCC method produces better throughput, delay and jitter compared to the ECMP method, even though it has slightly different values for each QoS parameter. In testing traffic distribution, the PCC method outperforms the ECMP method. The PCC method can distribute traffic evenly across both ISP lines when downloading and uploading data packets. Meanwhile, the ECMP method can only carry out download and upload activities on one traffic path.]]>
