Open AccessArtificial neural network based antenna sensitivity assignments for chaotic internet service provider network architecture
Author(s) -
Lolit Villanueva,
Reggie C. Gustilo
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.3.9958
Subject(s) - the internet , computer science , sensitivity (control systems) , artificial neural network , antenna (radio) , internet access , computer network , service (business) , service provider , signal (programming language) , process (computing) , wireless , real time computing , chaotic , data mining , telecommunications , artificial intelligence , electronic engineering , engineering , world wide web , economy , economics , programming language , operating system
The connectivity and grade of service of an Internet Service Provider (ISP) in the Philippines is observed and analysed in this research. Traditionally, the sensitivity of the antennas for wireless access points are done manually by monitoring the signal levels onsite during the installation process. Ten subscriber locations are randomly selected as test points. The connectivity of these subscribers is observed given that their sensitivities are set manually. Finally, a proposed artificial neural network algorithm is presented to improve the availability of the internet link. The proposed algorithm incorporates the random variations of the received signal levels of the internet access points and possible degradation of signals from attenuation due to rain. Experiment results show that at least 75% increase in availability is observed using the proposed algorithm during rainy events.