Structures of User Association Patterns in Wireless LAN

Structures of User Association Patterns in Wireless LAN

CEN4500C: Wireless Experiments Background Wireless Measurements: Shao-Cheng Wang ( [email protected] ) Encounter-based Networks: Sapon Tanachaiwiwat ( [email protected] ) Instructor: Dr. Helmy 9/13/2007 1 Part I: Wireless Measurements Agenda Introduction Wireless measurement fundamentals

Tools Potential Topics Reference 2 How does a coverage map look like? http://www.ittc.ku.edu/wlan/images.shtml 3 coverage maps (contd)

4 Wireless fundamentals: SNR v.s. Distance 5 Wireless fundamentals: SNR v.s. Performance SNR v.s. Delivery ratio (emulator) SNR v.s. Delivery ratio (real measurement)

SNR v.s. TCP Tput (real measurement) 6 Tools Site-surveyer: Netstumbler (www.netstumbler.com) Signal (in dbm), SNR AP MAC, SSID 7 8

Tools (contd) HP iPAQ 9 Tools (contd) Bandwidth test NDT @ UF: http://ndt.server.ufl.edu:7123/ TCP uplink/dnlink speed Myspeed: http://myvoipspeed.visualware.com/ UDP loss rate, jitter 10

Potential experiment topics Coverage Map: Create a coverage map of your choice: SNR (enhanced with levels, dbm #s) SNR variations (weather, day/night) Performance map Find holes, additions, tech heterogeneity (11a/b/g/e/n) etc. (please coordinate between groups for the area of interest)

Reason about your choice and the implications of practicability Observations/Surprises? AP Hunting/Coverage/Handover Locate APs in some specific areas/buildings Create an AP-specific coverage map AP-coverage/handover map for routes on campus Observations and discussions about the AP planning (evaluation of

planning, tradeoffs, applications, etc.) 11 Reference Simon Byers and Dave Kormann, 802.11b access point mapping, Communications of the ACM, May 2003. Daniel Aguayo, John Bicket, Sanjit Biswas, Glenn Judd, Robert Morris, Link-level Measurements from an 802.11b Mesh Network, SIGCOMM 2004, August 2004

Hiroto Aidal, Yosuke Tamura2, Yoshito Tobe2, Hideyuki Tokudal, Wireless Packet Scheduling with Signal-to-Noise Ratio Monitoring, LCN 2000 12 Part II: Encounter-based Networks Agenda Introduction Examples of Encounter based networking Encounter-based worm interactions Experiment for our class Reference

13 Introduction What is Encounter-based networking Discontinuous path (Intermittent connection) Store-and-forward (Bundles) Similar to delay-and-disruption-tolerantnetworking Large delay Low data rate High loss rate Networking relying on encounter or relationships between nodes (Social networking)

D E A B F C Basic assumptions of each node

Persistent storage Willing to participate Limitation of Power Short Radio Range 14 Examples of encounter-based networks

Military tactical networks Disaster relief ZebraNet Interplanetary networks Underwater acoustic networks Rural village networks Other? 15 http://www.cs.rice.edu/~animesh/comp620/presentations/JFP04_D.pdf

16 Encounter-based worms Future direction on worm attacks!! (Cabir, ComWar) Rely on encounter pattern/relationships between users. Close to flooding, i.e. Epidemic routing. Propagate via Bluetooth connection (10-meter range) Question: How can we alleviate this problem? Traditional prevention at gateway such as firewall not effective against fully distributed attacks Disconnected networks No centralized update Inspired by War of the Worms : CodeGreen worms

launched to terminate CodeRed worms Approach: Deploy automated generated predator worm to terminate prey worm worm interaction 17 Encounter-based worm interaction Susceptible Predator Prey Prey and predators infection rate rely only on encounter characteristics 18

Experiment Goal: To answer the following questions Is the UF campus the good target for worm propagation, given that it propagate via Bluetooth? If so, what places are most vulnerable? If you want to stop the propagation with other worm, how can you do it effectively?

Equipments: iPAQs, your laptops, your strategies Software: Modified Bluechat, Netstumbler, AirSnort, etc. 19 Bluetooth device discovery Distribution of Bluetooth devices that you encounter during the day E.g. Type of devices such as cell phone or lap top, brand of such devices such as Nokia, Motorola, etc. Bluetooth game Design the strategies for

Largest of encounter rate per day Largest number of unique devices Largest number of stable devices Different roles between teams e.g. Cops and Cons Bluetooth and WLAN relationships Can you derive the correlation between them? Bluetooth worm interactions To test the real worm propagation/ interaction with static/mobility Parameters Type of worm: one or two

Static or Mobile (human mobility) Topology (for static): line, star, random With/Without the super node, i.e., super mobile node which is our radiocontrolled truck 20 Reference

E. Anderson, K. Eustice, S. Markstrum, M. Hansen, P. L. Reiher , Mobile Contagion: Simulation of Infection and Defense PADS 2005: 80-87 S. Capkun, J. P. Hubaux, and L. Buttyan "Mobility Helps Security in Ad Hoc Networks" Fourth ACM Symposium on Mobile Networking and Computing (MobiHoc), June 2003 F. Castaneda, E.C. Sezer, J. Xu, WORM vs. WORM: preliminary study of an active counter-attack mechanism, ACM workshop on Rapid malcode, 2004 A. Chaintreau, P. Hui, J. Crowcroft, C. Diot, R. Gass and J. Scott, Impact of Human Mobility on the Design of Opportunistic Forwarding Algorithms IEEE INFOCOM, April 2006 W. Hsu, A. Helmy, "On Nodal Encounter Patterns in Wireless LAN Traces", The 2nd IEEE Int.l Workshop on Wireless Network Measurement (WiNMee), April 2006

S.Tanachaiwiwat, A. Helmy, "Encounter-based Worms: Analysis and Defense", IEEE Conference on Sensor and Ad Hoc Communications and Networks (SECON) 2006 Poster/Demo Session, VA, September 2006 A. Vahdat and D. Becker. Epidemic routing for partially connected ad hoc networks. Technical Report CS-2000. 21

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