Abstract | ||
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The growing trend of wireless devices and WiFi networks poses significant management challenges to network administrators. Characterizing WiFi user behavior and understanding WiFi network usage pattern are helpful to identify the management challenges so that network administrators could manage WiFi networks more efficiently. In this work, we collect comprehensive datasets, i.e., DHCP dataset, AAA dataset, SNMP dataset of ACs in a large campus WiFi network. We provide a detailed measurement study from multiple dimensions, i.e., server plane, temporal plane, spatial plane and traffic plane. We observe that the WiFi network under study is far from optimal. First, the phenomenon of IP waste is severe due to the isolation between DHCP server and AAA server. Second, current deployment of network infrastructure resources is based on network administrators' experience and it results in that the WiFi performance varies a lot across different areas. Furthermore, we also study the user behavior with different types of devices and in different kinds of buildings. Our observations indicate that the WiFi network could be improved and managed more efficiently from multiple dimensions. We believe that this measurement study is helpful for network administrators and researchers to understand more about large scale WiFi networks. |
Year | DOI | Venue |
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2018 | 10.1109/LCN.2018.8638246 | LCN |
Keywords | Field | DocType |
Wireless fidelity,IP networks,Servers,Buildings,Wireless communication,Internet,Authentication | Authentication,Wireless,Software deployment,Computer science,Server,Computer network,Dynamic Host Configuration Protocol,Multiple time dimensions,The Internet,Distributed computing,Simple Network Management Protocol | Conference |
ISBN | Citations | PageRank |
978-1-5386-4413-3 | 1 | 0.37 |
References | Authors | |
0 | 6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Congcong Miao | 1 | 31 | 4.69 |
Jilong Wang | 2 | 57 | 19.88 |
Jessie Hui Wang | 3 | 118 | 20.10 |
Jun Zhang | 4 | 1102 | 188.11 |
Weiwei Zhou | 5 | 1 | 3.07 |
Shengchao Liu | 6 | 1 | 0.71 |