Intelligent Hybrid model to Enhance Time Series Models for Predicting Network Traffic, the proposed research has used the clustering approach to handle the ambiguity from the entire network data for enhancing the existing time series models.
1) 4G Cell traffic from Kaggle
The q-data collected from Kaggle data set contains loading packets of 4G cells.
4G cell traffic is known as the traffic of users of a mobile data service; the mobile device will be served by a nearby 4G cell.
The data contains one week of traffic; Cell 039872 is serving 50 subscribers, and each subscriber in 1 hour x uses an average of 10Mb => Traffic of cell 039872.
In this research, one day (10-16-2016) of traffic was considered to test the proposed model
2)MAWI (Measurement and Analysis on the WIDE Internet)
This trace is collected from a backbone of WIDE internet with a connection speed of 150 Mbps.
The MAWI (Measurement and Analysis on the WIDE Internet) repository contains numbers of network traffic data.
The WIDE is the backbone of a Japanese academic network. We have considered the 2015 traffic trace. \