Operating System Design Sensor Networks Using Artificial Intelligence
Lots of technical issues that affect the sensor networks focusing on management, optimization and management. Many applications such as video conferencing, distance education etc., require to send a timely message from one end to the other selected base stations. These applications have stringent Quality-of-Service (QoS) needs including loss rate, insufficient bandwidth and delay. The objective of the work is to provide a reliable data-transmission by applying Artificial Intelligence (AI) mechanism from source to sink. Machine learning algorithm is applied to improve the routing facilities by monitoring the network traffic. Threshold management is difficult to maintain in operating system design sensor networks (OSDSN) since the network configuration changes often. Therefore supervised learning algorithm is applied for finding node fitness rate that involves the route with high link quality
Year of publication: |
2019
|
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Authors: | V, Kavitha |
Other Persons: | A, Bhuvanesh (contributor) ; J, Joshuva Arputharaj (contributor) ; M, Joshua Mani (contributor) ; K, Ajay Subbiah (contributor) |
Publisher: |
[2019]: [S.l.] : SSRN |
Subject: | Künstliche Intelligenz | Artificial intelligence | Expertensystem | Expert system | Betriebssystem | Operating system |
Saved in:
freely available
Extent: | 1 Online-Ressource (4 p) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments August 5, 2019 erstellt |
Other identifiers: | 10.2139/ssrn.3432214 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012865261
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