Fast Channel Selection Strategy in Cognitive Wireless Sensor Networks
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’ ha...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-07-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/171357 |
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| _version_ | 1832547312147103744 |
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| author | Yong Sun Jian-sheng Qian |
| author_facet | Yong Sun Jian-sheng Qian |
| author_sort | Yong Sun |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-b05c164c041442d8921cbb94a66b288d |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-b05c164c041442d8921cbb94a66b288d2025-02-03T06:45:24ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-07-011110.1155/2015/171357171357Fast Channel Selection Strategy in Cognitive Wireless Sensor NetworksYong SunJian-sheng QianIn 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.https://doi.org/10.1155/2015/171357 |
| spellingShingle | Yong Sun Jian-sheng Qian Fast Channel Selection Strategy in Cognitive Wireless Sensor Networks International Journal of Distributed Sensor Networks |
| title | Fast Channel Selection Strategy in Cognitive Wireless Sensor Networks |
| title_full | Fast Channel Selection Strategy in Cognitive Wireless Sensor Networks |
| title_fullStr | Fast Channel Selection Strategy in Cognitive Wireless Sensor Networks |
| title_full_unstemmed | Fast Channel Selection Strategy in Cognitive Wireless Sensor Networks |
| title_short | Fast Channel Selection Strategy in Cognitive Wireless Sensor Networks |
| title_sort | fast channel selection strategy in cognitive wireless sensor networks |
| url | https://doi.org/10.1155/2015/171357 |
| work_keys_str_mv | AT yongsun fastchannelselectionstrategyincognitivewirelesssensornetworks AT jianshengqian fastchannelselectionstrategyincognitivewirelesssensornetworks |