Modularity analysisof users’mobile behavior in campus wireless network
Choosing a better and easily computed similarity metric is a challenge task,and the problem how the formedmodularity can help network operation attracts less attention.By introducing sparse linked interval(SLI) to represent wireless nodes' mobile trajectory,mobile nodes' modularity relatio...
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Format: | Article |
Language: | zho |
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Editorial Department of Journal on Communications
2013-09-01
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Series: | Tongxin xuebao |
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Online Access: | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.Z2.022/ |
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author | Chang-ling ZHOU Qun QIAN Yi-qiu ZHAO Qun SHANG |
author_facet | Chang-ling ZHOU Qun QIAN Yi-qiu ZHAO Qun SHANG |
author_sort | Chang-ling ZHOU |
collection | DOAJ |
description | Choosing a better and easily computed similarity metric is a challenge task,and the problem how the formedmodularity can help network operation attracts less attention.By introducing sparse linked interval(SLI) to represent wireless nodes' mobile trajectory,mobile nodes' modularity relations via social network analysis methods were effectively revealed.Using real operational datasets of Peking University campus wireless network and public dataset as validation,three common motifs in modularity level,and their formation reasonsand relations to network managements were demonstrated. |
format | Article |
id | doaj-art-c88475bca0564c3bb8be5aeff6e33996 |
institution | Kabale University |
issn | 1000-436X |
language | zho |
publishDate | 2013-09-01 |
publisher | Editorial Department of Journal on Communications |
record_format | Article |
series | Tongxin xuebao |
spelling | doaj-art-c88475bca0564c3bb8be5aeff6e339962025-01-14T06:42:17ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2013-09-013411111659678197Modularity analysisof users’mobile behavior in campus wireless networkChang-ling ZHOUQun QIANYi-qiu ZHAOQun SHANGChoosing a better and easily computed similarity metric is a challenge task,and the problem how the formedmodularity can help network operation attracts less attention.By introducing sparse linked interval(SLI) to represent wireless nodes' mobile trajectory,mobile nodes' modularity relations via social network analysis methods were effectively revealed.Using real operational datasets of Peking University campus wireless network and public dataset as validation,three common motifs in modularity level,and their formation reasonsand relations to network managements were demonstrated.http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.Z2.022/wireless networkmobile trajectorysparse linked intervalsocial network analysissimilarity |
spellingShingle | Chang-ling ZHOU Qun QIAN Yi-qiu ZHAO Qun SHANG Modularity analysisof users’mobile behavior in campus wireless network Tongxin xuebao wireless network mobile trajectory sparse linked interval social network analysis similarity |
title | Modularity analysisof users’mobile behavior in campus wireless network |
title_full | Modularity analysisof users’mobile behavior in campus wireless network |
title_fullStr | Modularity analysisof users’mobile behavior in campus wireless network |
title_full_unstemmed | Modularity analysisof users’mobile behavior in campus wireless network |
title_short | Modularity analysisof users’mobile behavior in campus wireless network |
title_sort | modularity analysisof users mobile behavior in campus wireless network |
topic | wireless network mobile trajectory sparse linked interval social network analysis similarity |
url | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.Z2.022/ |
work_keys_str_mv | AT changlingzhou modularityanalysisofusersmobilebehaviorincampuswirelessnetwork AT qunqian modularityanalysisofusersmobilebehaviorincampuswirelessnetwork AT yiqiuzhao modularityanalysisofusersmobilebehaviorincampuswirelessnetwork AT qunshang modularityanalysisofusersmobilebehaviorincampuswirelessnetwork |