Characterizing Mobility and Network Usage in a Corporate Wireless Local-Area Network Export

@inproceedings{balazinska:wireless, abstract = {Wireless local-area networks are becoming increasingly popular. They are commonplace on university campuses and inside corporations, and they have started to appear in public areas. It is thus becoming increasingly important to understand user mobility patterns and network usage characteristics on wireless networks. Such an understanding would guide the design of applications geared toward mobile environments (e.g., pervasive computing applications), would help improve simulation tools by providing a more representative workload and better user mobility models, and could result in a more effective deployment of wireless network components. Several studies have recently been performed on wireless university campus networks and public networks. In this paper, we complement previous research by presenting results from a four week trace collected in a large corporate environment. We study user mobility patterns and introduce new metrics to model user mobility. We also analyze user and load distribution across access points. We compare our results with those from previous studies to extract and explain several network usage and mobility characteristics. <p> We find that average user transfer-rates follow a power law. Load is unevenly distributed across access points and is influenced more by which users are present than by the number of users. We model user mobility with persistence and prevalence . Persistence reflects session durations whereas prevalence reflects the frequency with which users visit various locations. We find that the probability distributions of both measures follow power laws.}, address = {San Francisco, CA}, author = {Balazinska, Magdalena and Castro, Paul}, booktitle = {Proceedings of the First International Conference on Mobile Systems, Applications, and Services (MobiSys)}, citeulike-article-id = {816407}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1066127}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1066116.1066127}, citeulike-linkout-2 = {http://www.usenix.org/events/mobisys03/tech/balazinska.html}, doi = {10.1145/1066116.1066127}, keywords = {crawdad, ibm\_watson, measurement, wireless}, location = {San Francisco, California}, month = {May}, pages = {303--316}, posted-at = {2009-07-07 12:09:48}, priority = {2}, publisher = {USENIX Association}, title = {{Characterizing Mobility and Network Usage in a Corporate Wireless Local-Area Network}}, url = {http://dx.doi.org/10.1145/1066116.1066127}, year = {2003} }

TY - CONF ID - balazinska:wireless L3 - citeulike-article-id:816407 N2 - Wireless local-area networks are becoming increasingly popular. They are commonplace on university campuses and inside corporations, and they have started to appear in public areas. It is thus becoming increasingly important to understand user mobility patterns and network usage characteristics on wireless networks. Such an understanding would guide the design of applications geared toward mobile environments (e.g., pervasive computing applications), would help improve simulation tools by providing a more representative workload and better user mobility models, and could result in a more effective deployment of wireless network components. Several studies have recently been performed on wireless university campus networks and public networks. In this paper, we complement previous research by presenting results from a four week trace collected in a large corporate environment. We study user mobility patterns and introduce new metrics to model user mobility. We also analyze user and load distribution across access points. We compare our results with those from previous studies to extract and explain several network usage and mobility characteristics. <p> We find that average user transfer-rates follow a power law. Load is unevenly distributed across access points and is influenced more by which users are present than by the number of users. We model user mobility with persistence and prevalence . Persistence reflects session durations whereas prevalence reflects the frequency with which users visit various locations. We find that the probability distributions of both measures follow power laws. CY - San Francisco, California AD - San Francisco, CA EP - 316 TI - {Characterizing Mobility and Network Usage in a Corporate Wireless Local-Area Network} PB - USENIX Association T2 - Proceedings of the First International Conference on Mobile Systems, Applications, and Services (MobiSys) SP - 303 KW - crawdad KW - ibm_watson KW - measurement KW - wireless AU - Balazinska, Magdalena AU - Castro, Paul PY - 2003/May// UR - http://dx.doi.org/10.1145/1066116.1066127 ER -