Fast Channel Selection Strategy in Cognitive Wireless Sensor Networks | Zendy

Yong Sun | Zendy; Jiansheng Qian | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Fast Channel Selection Strategy in Cognitive Wireless Sensor Networks

Author(s) -

Yong Sun,

Jiansheng Qian

Publication year - 2015

Publication title -

international journal of distributed sensor networks

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.324

H-Index - 53

eISSN - 1550-1477

pISSN - 1550-1329

DOI - 10.1155/2015/171357

Subject(s) - computer science , selection (genetic algorithm) , channel (broadcasting) , wireless sensor network , attraction , wireless , cognition , cognitive radio , selection algorithm , energy (signal processing) , machine learning , artificial intelligence , computer network , telecommunications , philosophy , linguistics , statistics , mathematics , neuroscience , biology

In order to meet the practical requirement for Cognitive Wireless Sensor Networks applications, this paper proposes innovative fast channel selection algorithm to solve the shortcomings of original Experience-Weighted Attraction algorithm's complexity, higher energy consuming, and the nodes’ hardware restrictions of real-time data processing capabilities. Research is conducted by comparing channel selection differences and timeliness with traditional Experience-Weighted Attraction learning. Though not as stable as traditional Experience-Weighted Attraction learning, fast channel selection algorithm has effectively reduced the complexity of the original algorithm and has superior performance than Q learning.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research