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Wireless Internet Performance Research Carey Williamson iCORE Professor Department of Computer Science University of Calgary www.cpsc.ucalgary.ca/~carey carey@cpsc.ucalgary.ca Internet Protocol Stack Application: supporting network applications and end-user services FTP, SMTP, HTTP, DNS, NTP Transport: end to end data transfer TCP, UDP Network: routing of datagrams from source to destination IPv4, IPv6, BGP, RIP, routing protocols Data Link: hop by hop frames, channel access, flow/error control PPP, Ethernet, IEEE 802.11b Physical: raw transmission of bits Application Transport Network Data Link Physical 001101011 The Wireless Web The emergence and convergence of these technologies enable the “wireless Web” the wireless classroom the wireless workplace the wireless home My iCORE mandate: design, build, test, and evaluate wireless Web infrastructures Holy grail: “anything, anytime, anywhere” access to information (when we want it, of course!) Research Interests Wireless Internet Technologies MAC Protocol Design Network Traffic Measurement Workload Characterization Traffic Modeling Network Simulation Web Performance Wireless Internet Technologies Mobile devices (e.g., notebooks, laptops, PDAs, cell phones, wearable computers) Wireless network access Bluetooth (1 Mbps, up to meters) IEEE 802.11b (11 Mbps, up to 100 meters) IEEE 802.11a (55 Mbps, up to 20 meters) Operating modes: Infrastructure mode (access point) Ad hoc mode Example: Infrastructure Mode cnn.com Internet Access Point (AP) Carey Example: Ad Hoc Mode Multi-hop “ad hoc” networking Sean Carey Example: Ad Hoc Mode Multi-hop “ad hoc” networking Sean Carey Example: Ad Hoc Mode Multi-hop “ad hoc” networking Sean Carey Example: Ad Hoc Mode Multi-hop “ad hoc” networking Sean Carey MAC Protocol Design Identify performance problems in wireless Medium Access Control (MAC) protocols Examples: IEEE 802.11b WLANs Unfairness problems [Xiao MSc 2004] Effects of node mobility [Bai 2004] “Bad Apple” phenomenon [Cao 2004] TCP on multi-hop ad hoc networks [Gupta 2004] Multi-channel MAC protocols [Kuang 2004] Multi-rate multi-channel protocols [Wu 2005] Network Traffic Measurement Collect and analyze packet-level traces from a live network, using special equipment Process traces, statistical analysis Diagnose performance problems (network, protocol, application) 101 101 Example: tcpdump Trace 0.000000 192.168.1.201 -> 192.168.1.200 60 TCP 4105 80 1315338075 : 1315338075 win: 5840 S 0.003362 192.168.1.200 -> 192.168.1.201 60 TCP 80 4105 1417888236 : 1417888236 1315338076 win: 5792 SA 0.009183 192.168.1.201 -> 192.168.1.200 52 TCP 4105 80 1315338076 : 1315338076 1417888237 win: 5840 A 0.010854 192.168.1.201 -> 192.168.1.200 127 TCP 4105 80 1315338076 : 1315338151 1417888237 win: 5840 PA 0.014309 192.168.1.200 -> 192.168.1.201 52 TCP 80 4105 1417888237 : 1417888237 1315338151 win: 5792 A 0.049848 192.168.1.200 -> 192.168.1.201 1500 TCP 80 4105 1417888237 : 1417889685 1315338151 win: 5792 A 0.056902 192.168.1.200 -> 192.168.1.201 1500 TCP 80 4105 1417889685 : 1417891133 1315338151 win: 5792 A 0.057284 192.168.1.201 -> 192.168.1.200 52 TCP 4105 80 1315338151 : 1315338151 1417889685 win: 8688 A 0.060120 192.168.1.201 -> 192.168.1.200 52 TCP 4105 80 1315338151 : 1315338151 1417891133 win: 11584 A 0.068579 192.168.1.200 -> 192.168.1.201 1500 TCP 80 4105 1417891133 : 1417892581 1315338151 win: 5792 PA 0.075673 192.168.1.200 -> 192.168.1.201 1500 TCP 80 4105 1417892581 : 1417894029 1315338151 win: 5792 A 0.076055 192.168.1.201 -> 192.168.1.200 52 TCP 4105 80 1315338151 : 1315338151 1417892581 win: 14480 A 0.083233 192.168.1.200 -> 192.168.1.201 1500 TCP 80 4105 1417894029 : 1417895477 1315338151 win: 5792 A 0.096728 192.168.1.200 -> 192.168.1.201 1500 TCP 80 4105 1417896925 : 1417898373 1315338151 win: 5792 A 0.103439 192.168.1.200 -> 192.168.1.201 1500 TCP 80 4105 1417898373 : 1417899821 1315338151 win: 5792 A 0.103780 192.168.1.201 -> 192.168.1.200 52 TCP 4105 80 1315338151 : 1315338151 1417894029 win: 17376 A 0.106534 192.168.1.201 -> 192.168.1.200 52 TCP 4105 80 1315338151 : 1315338151 1417898373 win: 21720 A 0.133408 192.168.1.200 -> 192.168.1.201 776 TCP 80 4105 1417904165 : 1417904889 1315338151 win: 5792 FPA 0.139200 192.168.1.201 -> 192.168.1.200 52 TCP 4105 80 1315338151 : 1315338151 1417904165 win: 21720 A 0.140447 192.168.1.201 -> 192.168.1.200 52 TCP 4105 80 1315338151 : 1315338151 1417904890 win: 21720 FA 0.144254 192.168.1.200 -> 192.168.1.201 52 TCP 80 4105 1417904890 : 1417904890 1315338152 win: 5792 A Example: TELUS Mobility Project Data Template and Example – XYZ Platform Code ==== 20 21 22 200 21x 22x 30 31 32 300 31x 32x 40 41 100 11x 12x 50 60 70 Definition ========== FSCH Data Rate FSCH Data Burst Start Time FSCH Data Burst End Time FSCH Active Set Report Time FSCH Active Set Cell ID ('x' is a number) FSCH Active Ste Sector ID ('x' is a number) RSCH Data Rate RSCH Data Burst Start Time RSCH Data Burst End Time RSCH Active Set Report Time RSCH Active Set Cell ID ('x' is a number) RSCH Active Ste Sector ID ('x' is a number) FCH Data Start Time FCH Data End Time FCH Active Set Report Time FCH Active Set Cell ID ('x' is a number) FCH Active Ste Sector ID ('x' is a number) IMSI Frequency SID 50 51 70 60 40 41 200 211 221 20 21 22 20 21 22 20 21 22 000006048421781 0x804ce0401aa89666 16422 384 2004041375333.680 2004041375443.020 2004041375337.940 32 16 2004041375338.200 2004041375339.200 2004041375357.860 2004041375357.880 16 2004041375371.720 2004041375372.700 Workload Characterization Try to understand the salient features of network, protocol, application, and user behaviour on the Internet Example: Web server workloads [Arlitt96] Zipf-like document referencing behaviour Lots of “one-time” referencing of documents Heavy-tailed file size distributions Self-similar network traffic profile Session duration and call arrival process Traffic Modeling Construct programs and statistical models that capture the empirically-observed network traffic behaviours Allows flexible, controlled, repeatable generation of workloads for experiments Examples: Web client workload model MPEG compressed video model Self-similar Ethernet LAN traffic model WebTraff GUI: Web proxy workload generator Example: Web Workload Generation Network Simulation Use computer simulation to study the packet-level behaviour of the Internet, its protocols, its applications, and its users Examples: Improving Web performance over ADSL Understanding the effects of user mobility on Mobile IP routing and protocol performance Studying the design, scalability, and performance of Web server and Web proxy caching architectures Web Performance Explore techniques to improve the performance and scalability of the Web Examples: Clustered Web servers Load balancing policies Web prefetching strategies Web proxy caching architectures Improvements to HTTP and TCP protocols Example: Web Server Benchmarking Client Client Web Server Client Client C Summary Wireless Internet Performance Lab (UofC) Experimental Laboratory for Internet Systems and Applications (UofS/UofC,CFI) iCORE Research Team: Five full-time research staff (Web, perf eval., simulation, wireless, traffic modeling, network measurement) plus graduate students Research Collaborations: UofC, UofA, UofS, TRLabs, CS/ECE HP, TELUS Mobility, SaskTel, Nortel… Industrially-relevant experimental research on network protocol performance