OPTIMALISASI JARINGAN CLUSTER IP DAN BANDWIDTH DENGAN METODE LOAD BALANCING MENGGUNAKAN TEKNIK PER CONNECTION CLASSIFIER PADA GNS 3

Saputra, Dany Mulya (2023) OPTIMALISASI JARINGAN CLUSTER IP DAN BANDWIDTH DENGAN METODE LOAD BALANCING MENGGUNAKAN TEKNIK PER CONNECTION CLASSIFIER PADA GNS 3. Undergraduate thesis, Universitas Muhammadiyah Malang.

[thumbnail of SKRIPSI.pdf] Text
SKRIPSI.pdf
Restricted to Registered users only

Download (4MB) | Request a copy

Abstract

The Internet is a combination of two or several computers that are interconnected so that they can communicate or interact with other computers. Such as receiving information, exchanging information for shared use, and providing or receiving services used over computer networks. The server has the function of providing service access to the client, so the server is required to be able to serve request requests from all connected clients. Devices used for cluster ip address and bandwidth management are GNS 3 Simulator and Mikrotik Router. Load balance is a method to distribute traffic load on two or more connection lines in a balanced manner, so that traffic can run optimally, maximize throughput, reduce response time and can avoid overload on one connection line. Load Balance and Per Connection Classifier can overcome problems that occur in cluster ip address and bandwidth division so that it is possible to be more efficient in sharing, bandwidth management using Winbox proxy and the cluster loadbalance function works when the server is processing requests, all requests will be distributed evenly throughout, the path that exists on the cluster so that the server does not experience overload. Router loadbalance can run commands in accordance with setting ip address and pcc load balancing techniques, testing speedtest bandwidth PC Client is able to regulate every upload and download speed on ISP 1 and ISP 2 provider networks. Load Balance using the per connection classifier technique will run effectively and close to balance if more connections from clients are accessed.

Item Type: Thesis (Undergraduate)
Student ID: 201710130311107
Keywords: Kata Kunci : Internet, Cluster IP, Load Balance, PCC, QoS, Mikrotik.
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Faculty of Engineering > Department of Electrical Engineering (20201)
Depositing User: 201710130311107 masdanymulyasa
Date Deposited: 03 Nov 2023 07:48
Last Modified: 03 Nov 2023 07:48
URI: https://eprints.umm.ac.id/id/eprint/583

Actions (login required)

View Item
View Item