Bandwidth Modeling and Estimation in Peer to Peer Networks

TL;DR

This paper introduces a stochastic model for bandwidth in P2P networks based on the Ornstein-Uhlenbeck process, analyzing its statistical properties, queue behavior, and methods for synthetic data generation and parameter estimation.

Contribution

It presents a novel bandwidth model for P2P networks using stochastic integrals and studies its statistical and queueing properties, including parameter estimation techniques.

Findings

Derived autocovariance structure of bandwidth

Analyzed queue length behavior under the model

Proposed methods for synthetic bandwidth generation and parameter estimation

Abstract

Recent studies have shown that the majority of today's internet traffic is related to Peer to Peer (P2P) traffic. The study of bandwidth in P2P networks is very important. Because it helps us in more efficient capacity planning and QoS provisioning when we would like to design a large scale computer networks. In this paper motivated by the behavior of peers (sources or seeds) that is modeled by Ornstein Uhlenbeck (OU) process, we propose a model for bandwidth in P2P networks. This model is represented with a stochastic integral. We also model the bandwidth when we have multiple downloads or uploads. The autocovariance structure of bandwidth in either case is studied and the statistical parameters such as mean, variance and autocovariance are obtained. We then study the queue length behavior of the bandwidth model. The methods for generating synthetic bandwidth process and estimation of the bandwidth parameters using maximum likehood estimation are presented.