Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics

Multi-channel distribution mechanism based on BP neural network

Authors
Xue Ming Zhai, Jia Wang, Jin Ze Li
Corresponding Author
Xue Ming Zhai
Available Online October 2015.
DOI
10.2991/icmii-15.2015.65How to use a DOI?
Keywords
BP neural network; Multi-channel distribution; NS2; MDMAC;
Abstract

In order to make better use of wireless channel resources and improve the reliability and throughput of network and reduce network latency, multi-channel MAC protocol is becoming a hot topic to solve the problem. But the existing multi-channel MAC protocols for wireless network have their own restrictions. Due to the characteristics of the WSNs we propose a channel allocation algorithm based on BP neural network. And we compared with the MMAC protocol and the SMAC protocol on NS2. The MAC protocol we proposed in this paper performed better in terms of network throughput and network delay.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics
Series
Advances in Computer Science Research
Publication Date
October 2015
ISBN
10.2991/icmii-15.2015.65
ISSN
2352-538X
DOI
10.2991/icmii-15.2015.65How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xue Ming Zhai
AU  - Jia Wang
AU  - Jin Ze Li
PY  - 2015/10
DA  - 2015/10
TI  - Multi-channel distribution mechanism based on BP neural network
BT  - Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics
PB  - Atlantis Press
SP  - 358
EP  - 361
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmii-15.2015.65
DO  - 10.2991/icmii-15.2015.65
ID  - Zhai2015/10
ER  -