A novel prediction‐based collision resolution algorithm

Abstract

Purpose

The purpose of this paper is to introduce the performance of traditional collision resolution algorithm (CRA) under self‐similar traffic and present a prediction‐based CRA for wireless media access. With experimentations, the method is there after evaluated.

Design/methodology/approach

The traditional traffic models are mostly based on “Poisson” model or “Bernoulli” process, but recent decade traffic measurements found the coexistence of both long‐ and short‐range dependence in network traffic. On the other hand, CRA is an effective strategy to improve the performance of multiple access protocol and it achieves the highest capacity among all known multiple access protocols under the Poisson traffic model. In this paper, a CRA model is built on OPNET to study the effects of different traffic traces such as the fractional autoregressive integrated moving average process with non‐Gaussian white driving sequence and the real traffic data that are captured at a well‐attended ACM Conference. The performance is compared of traditional CRA based on the self‐similar traffic model and Poisson model and a novel CRA based on time – series prediction theory under self‐similar traffic models is designed.

Findings

The traditional Poisson traffic model gets the best performance under traditional CRA, while the self‐similar traffic performance under traditional CRA is too poor to be applied in an actual network environment. For example, the Poisson traffic model obtains the biggest throughput, the smallest delay and smallest collision resolution numbers under traditional CRA. This paper demonstrates the first‐come first‐serve (FCFS) must be improved under self‐similar traffic models. The novel collision resolution strategy‐based prediction can provide better performance under self‐similar traffic. The parameters of performance, such as throughput, delay and collision resolution numbers, are better than the traditional CRA.

Originality/value

This paper presents a prediction‐based CRA for self‐similar traffic which is the combination of the FCFS and the prediction theory and also provides a new method to resolve packets colliding.

Citation

Yang, S. and Guo, W. (2010), "A novel prediction‐based collision resolution algorithm", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 29 No. 2, pp. 405-416. https://doi.org/10.1108/03321641011014878