1 research outputs found
Forecasting and Event Detection in Internet Resource Dynamics using Time Series Models
At present Internet has emerged as a country's predominant and viable data
communication infrastructure. The Autonomous System (AS) resources which are
building blocks of the Internet are AS numbers, IPv4 and IPv6 Prefixes. AS
number growth is one of Internet infrastructure development indicators. Hence
understanding on long term trend and stochastic variation behaviour are
essential to detect significant events during the growth. In this work, time
series based approximation is considered for mathematical modelling and
forecast the yearly AS growth. The AS data of five countries namely India,
China, Japan, South Korea and Taiwan are extracted from APNIC archive. ARIMA
models with different Auto Regressive and Moving Average parameters are
identified for forecasting. Model validation, parameter estimation, point
forecast and prediction intervals with 95 % confidence levels for the five
countries are reported in the paper. The significant level change in
variations, positive growth percentage in Inter Annual Absolute Variations
(IAAV) and higher percentage of advertised ASes when compared to other
countries indicate India's fast growth and wider global reachability of
Internet infrastructure from 2007 onwards. The correlation between IAAV change
point and GDP growth period indicates that service sector industry growth is
the driving force behind significant yearly changes.Comment: 22 pages, 15 figure