Research Article 
Adaptive Throughput Policy Algorithm with Weibull Traffic Model for Campus IP-Based Network
Murizah Kassim, Mahamod Ismail and Mat Ikram Yusof
Information Technology Journal, 2014, 13(17), 2632-2644.
Abstract
This study presents a new Adaptive Throughput Policy algorithm with Weibull (ATPWT) Traffic Model. Real live inbound internet throughput from IP-based campus network which supports 16 Mbps Committed Access Rate (CAR) is collected. Throughputs are fitted with four best Cumulative Distribution Function (CDF) which are Normal, Lognormal, Exponential and Weibull. Maximum Likelihood Estimator (MLE) technique is used to measure the best CDF fits which presents the maximum log-likelihood. Analysed throughput found that Day 1 and Day 7 present the minimum and maximum log-likelihood, respectively. A fitted 2-parameter Weibull distribution is identified as the best fit which produced new parameters: Scale, α and shape, β. These parameters are simulated as Weibull traffic model in the ATPWT algorithm. ATPWT performances on min-max MLE produces larger bandwidth saving, reduces bucket capacity and faster processing time. Burst traffic controlled in the system is derived with five different Weibull shape, β parameter. Larger value of shape, β produces less burst traffic while smaller shape, β parameter produces larger burst in the system. Thus, ATPWT algorithm derives burst controlled and better performance on internet throughput traffic for IP-based campus network in this research.
ASCI-ID: 28-3571
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Cited By
INTERNATIONAL CONGRESS ON ENGINEERING AND TECHNOLOGY 2024
INTERNATIONAL CONGRESS ON ENGINEERING AND TECHNOLOGY 2024, 2025, 3322(), 060005. DOI: 10.1063/5.0290597