Adaptive Model for Network Resources Prediction in Modern Internet Service Providers

EasyChair Preprint 3894

Abstract

Nowadays, Internet became a crucial tool for service delivery, enhancing network requirements. In this new scenario, through Internet Service Providers (ISPs) tend to evolve to Modern Internet Service Providers (MISPs), addressing situations such as elastic network resource demand that may cause problems of slowness, service interruption and constant disconnections. A promising approach to deal with elastic services is the usage of a network traffic prediction model, but traditional models do have all the necessary features to it. Within this context, this paper presents an adaptive network prediction model for MISPs that adjusts seasonality and trend and removes time series error cycles according to the behavior observed in network traffic. The results, using a real bandwidth data set, suggest that the proposed model improves the existing prediction models.

Keyphrases: Modern Internet Service Providers, elastic demand, prediction model

@booklet{EasyChair:3894,
  author    = {Dyego Oliveira and Francisco Filho and Thelmo de Araujo and Joaquim Celestino Jr and Rafael L. Gomes},
  title     = {Adaptive Model for Network Resources Prediction in Modern Internet Service Providers},
  howpublished = {EasyChair Preprint 3894},
  year      = {EasyChair, 2020}}