Applying the firefly algorithm to Traffic Matrix Estimation Problem

Abstract

Computational problems of NP nature are of utmost interest to computerscientists as these problems are not easily solvable incorporating deterministic algorithms. Non deterministic approaches which make use of random numbers to solve these problems have become a point of focus for many scientists as they offer a viable solution to many problems of this type. Nature inspired swam intelligence is one such approach which incorporates abstracted algorithms from nature which seems to be constantly solving these types of problems. In this project the focus will be on firefly algorithm which was proposed by Xin She Yang in 2008[1]. The paper which were used for reference was [2]  and [3] which applied this algorithm to QAP (quadratic asignment poblem), and used an elephant and mice approach to predict correct traffic estimate respectively. The main focus of this Project is not to get better results but comparable results as it is of exploratory nature. The problem of interest in this paper is Traffic estimation problem which is ubiquitious in the area of networking. Data was used from the Abilene dataset.