Comparative Performance Analysis of AODV Parameter for ZigBee Network using Artificial Neural Network | Zendy

P. Prativa | Zendy; Jaymin Bhalani | Zendy; Sandhya Sharma | Zendy

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Comparative Performance Analysis of AODV Parameter for ZigBee Network using Artificial Neural Network

Author(s) -

P. Prativa,

Jaymin Bhalani,

Sandhya Sharma

Publication year - 2016

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/ijca2016909331

Subject(s) - computer science , artificial neural network , ad hoc on demand distance vector routing , artificial intelligence , computer network , routing (electronic design automation) , routing protocol , optimized link state routing protocol

This paper emphasizes on the signal transmission range of Zigbee network based on IEEE 802.15.4 standard using Simulink-based simulator called TRUE TIME 2.1. Ad hoc On-Demand Distance Vector (AODV) Routing is implemented in TRUE TIME 2.1. Here a comparison is made between the three Artificial Neural Network Architectures such as Feed forward neural network, Cascade forward neural network and Layered Recurrent Neural Network for various training functions like Levenberg-Marquardt back propagation (trainlm), Bayesian regularization back propagation (trainbr) and BFGS quasi-Newton back propagation (trainbfg) for Feed Forward Neural Network.

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