On-demand multipath protocol with adaptive routing method by back propagation neural networks

Authors:
Fang Jing;R. S. Bhuvaneswaran;Yoshiaki Katayama;Naohisa Takahashi
Affiliations:
Department of Computer Science and Engineering Graduate School of Engineering, Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, 466-8555, Japan.;Ramanujan Computing Centre College of Engineering Guindy, Anna University, Chennai, Chennai-600 025, India.;Department of Computer Science and Engineering Graduate School of Engineering, Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, 466-8555, Japan.;Department of Computer Science and Engineering Graduate School of Engineering, Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, 466-8555, Japan
Venue:
International Journal of Communication Networks and Distributed Systems
Year:
2009

Citing 5
Cited 1

Multilayer feedforward networks are universal approximators

Neural Networks
Performance of multipath routing for on-demand protocols in mobile ad hoc networks

Mobile Networks and Applications
A Highly Adaptive Distributed Routing Algorithm for Mobile Wireless Networks

INFOCOM '97 Proceedings of the INFOCOM '97. Sixteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Driving the Information Revolution
The Rigorous Evaluation of Enterprise Java Bean Technology

ICOIN '01 Proceedings of the The 15th International Conference on Information Networking
A Reliability Layer for Ad-Hoc Wireless Sensor Network Routing

HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 9 - Volume 9

Back propagation neural network-based energy efficient routing protocols for mobile ad-hoc networks

International Journal of Intelligent Engineering Informatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Two representative multipath routing protocol strategies have been utilised currently, one is described as primary routing protocol and the other is load-balancing protocol. In the former routing protocol, the source selects the pre-computed shortest or fastest route as the primary one for the following data transmission. On the other hand, the latter routing protocol utilises multiple routes in rotation to equalise transmission load in the network. However, these solutions suffer during high mobility since they are lacking in global perspective for the following data transmission, resulting in low packet delivery ratio and prolonged delay time. Hence, to find the optimum routing protocol strategy, we present an adaptive multipath routing protocol by means of applying golden section search and back propagation neural networks. We evaluated our protocol using Omnet simulator. Simulation results show that the proposed solution has a good real-time performance than those of other protocols.