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The Rise of Smart Devices on Mobility in Wireless Networks Daniel Ramos CS 790G Fall 2010
Definitions • Wired Network • Structure is fixed and rarely changes. • Network topology is the physical connection between devices and access points (APs). • Wireless Network • Structure is dynamic and changes often. • Network topology is the radio connection between devices and APs.
Wireless Networks Difficulties • Typically lower bandwidth and quality of service than wired networks. • The environment can effect the radio signal to the AP. • Even if the connection is stable now the user might move! • If a user moves out of range of an AP, they have to be associated to a new one.
Mobile Smart Devices • Highly portable devices becoming increasingly popular:
Mobile Smart Devices • Examples: • Personal Digital Assistants (PDAs) • iPhone and other “smartphones” • iPad and other tablet PCs • Portable game consoles with wireless connectivity (e.g. Nintendo DS and Sony PSP)
Why are Mobility Studies Important? • Quality of Service • Resource Reservation • Load Balancing • Bandwidth Utilization • Capacity Planning
Roaming • Definition: Extension of connectivity service in a location that is different from the home location where the service was registered. • Cellular Networks • Moving between cell sites • Handoff or Handover • Cells are typically on the scale of kilometers • Computer Networks • Moving between access points • Typically on the scale meters
Roaming Problems • Maximum number of clients already reached • Different providers own different access points • Different or worse capabilities between access points
Previous Studies • Some focused on simulated mobility models • Random Walks • Unrealistic movements • Totally opposite directions • No real-world obstacles • Some focused on real data • Low mobility devices • Laptops
Modeling Roaming in Large-scale Wireless Networks using Real Measurements  • Did not focus on any one device type • Modeled roaming as a graph • Analyzed the degree of connectivity • Focused on the access points
Data Collection • 3 phases over 7 months • Recorded syslog events from APs • Authentications/Deauthentications • Associations/Dissociations • Roam between APs • Mostly laptops, but a few PDAs
Modeling Roaming as a Graph • GT = (VT, ET) • Named a “roaming graph” • Node is an APs • Edge is at least one client transition between i and j • “Crosspoint” APs • Accounting for “wiggling”
Degree of Connectivity • Only 24% of clients were “mobile” • Can be modeled as a negative binomial distribution
Other Results • Negative correlation between AP distance and transitions • New APs decrease “crosspoints” • New APs might make wiggling worse
Problems • Only low mobility devices were captured • Meaningful stastics for future devices?
Access and mobility of wireless PDA users • Focused on PDA devices • Characterized PDA mobility and access patterns • Developed 2 topology models for mobile studies
Data Collection • Collected over a single semester • Background application • Sent AP association information and signal strengh of all detected APs.
Mobility • Over twice as mobile as than laptops
Evolutionary Topology Model • Based on observed network proximity • Nodes are users • Edges are if users could “communicate” • If they both could connect a common AP.
Campus Waypoint Model • Based on the Random waypoint model • Used trace data for mobility vectors instead of relying on random or synthetic models. • Based on evolving set of sensed APs. • Determines velocity and direction.
Results • Evolutionary • Users created “islands” of disconnected graphs • Average degree of 4 • Waypoint • Only an average 11% are mobile at the same time • Users only move a 2.2 MPH • Appear and disappear frequently
Problems • Higher then normal drop-out rate • Drained batteries erased trace application • Wireless card was bulky • Non-volunteer sample group • Median of one wireless session per day
Conclusion • Studying mobility is important to network protocol evolution • Highly mobile devices are already changing both computer and cellular network usage • More actual data and realistic models are needed
References •  M. Papadopouli, M. Moudatsos, and M. Karaliopoulos, “Modeling Roaming in Large-scale Wireless Networks using Real Measurements,” Proceedings of the 2006 International Symposium on on World of Wireless, Mobile and Multimedia Networks, pp. 536-541, June 2006 •  M. McNett and G. M. Voelker, “Access and mobility of wireless PDA users,” ACM SIGMOBILE Mobile Computing and Communications Review, Volume 9, Issue 2 (April 2005).