A GA-SSO Based Intelligent Channel Assignment Approach for MR-MC Wireless Sensors Networks - Details

author：

Xu, Zhiping (Xu, Zhiping.) ^[1] | Chen, Zhicong (Chen, Zhicong.) ^[2] (Scholars：陈志聪) | Wu, Lijun (Wu, Lijun.) ^[3] (Scholars：吴丽君) | Lin, Peijie (Lin, Peijie.) ^[4] (Scholars：林培杰) | Cheng, Shuying (Cheng, Shuying.) ^[5] (Scholars：程树英)

Indexed by：

CPCI-S EI Scopus

Abstract：

In　this　paper,　based　on　the　simplified　swarm　optimization　(SSO)　algorithm　and　genetic　algorithm　(GA),　a　novel　GA-SSO　hybrid　optimization　algorithm　is　proposed　to　solve　the　NP-hard　channel　assignment　problem　of　multi-radio　multi-channel　(MR-MC)　wireless　sensors　networks　(WSN)　which　is　promising　for　data　intensive　application.　The　aim　of　channel　assignment　is　to　minimize　total　network　interference　so　as　to　maximize　network　throughput.　In　the　GA-SSO　based　channel　assignment,　an　improved　channel　merging　method　is　proposed　to　satisfy　the　interface　constraint　condition.　Matlab　based　simulation　results　show　that　the　proposed　GA-SSO　features　better　global　search　capacity　and　can　reduce　the　total　network　interference　more　effectively,　compared　to　the　SSO　and　DPSO-CA　algorithms.

Keyword：

Channel merging GA-SSO Multi-radio multi-channel Wireless sensors network

Community：

[ 1 ] [Xu, Zhiping]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350116, Peoples R China
[ 2 ] [Chen, Zhicong]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350116, Peoples R China
[ 3 ] [Wu, Lijun]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350116, Peoples R China
[ 4 ] [Lin, Peijie]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350116, Peoples R China
[ 5 ] [Cheng, Shuying]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350116, Peoples R China

Reprint 's Address：

陈志聪程树英
[Chen, Zhicong]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350116, Peoples R China;;[Cheng, Shuying]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou 350116, Peoples R China

Email：

zhicong.chen@fzu.edu.cn |
sycheng@fzu.edu.cn

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