A Bio-Inspired Quality of Service (QoS) Routing Algorithm

Author

Mellouk, Abdelhamid ; Hoceini, Said ; Zeadally, Sherali

Author_Institution

LiSSi Lab., Univ. of Paris-Est (UPEC), Vitry-sur-Seine, France

Volume

15

Issue

9

fYear

2011

fDate

9/1/2011 12:00:00 AM

Firstpage

1016

Lastpage

1018

Abstract

We propose in this letter a bio-inspired Quality of Service (QoS) routing algorithm that is based on the trial/error paradigm combined with a continuous adaptive function to optimize three QoS criteria: static cumulative cost path and dynamic end-to-end delay and residual bandwidth. Our proposed approach uses a model that combines a stochastic planned pre-navigation for the exploration phase and a deterministic approach for the backward phase. We adopt a unified framework of online learning to develop a cost function. We evaluated the performance of our QoS-routing algorithm and the simulation results demonstrate substantial performance improvements for networks with dynamically changing traffic.

Keywords

learning (artificial intelligence); quality of service; stochastic processes; telecommunication computing; telecommunication network routing; bio-inspired quality of service routing algorithm; continuous adaptive function; cost function; dynamic end-to-end delay; online learning; residual bandwidth; static cumulative cost path; stochastic planned pre-navigation; trial-error paradigm; Bandwidth; Biology; Delay; Heuristic algorithms; Learning; Quality of service; Routing; Quality of service routing; bio-inspired reinforcement learning; optimization; performance evaluation;

fLanguage

English

Journal_Title

Communications Letters, IEEE

Publisher

ieee

ISSN

1089-7798

Type

jour

DOI

10.1109/LCOMM.2011.071211.110741

Filename

5959254