1 Wireless Internet Performance Research Carey Williamson iCORE Professor Department of Computer Science University of Calgary

2 Internet Protocol Stack r Application: supporting network applications and end-user services m FTP, SMTP, HTTP, DNS, NTP r Transport: end to end data transfer m TCP, UDP r Network: routing of datagrams from source to destination m IPv4, IPv6, BGP, RIP, routing protocols r Data Link: hop by hop frames, channel access, flow/error control m PPP, Ethernet, IEEE b r Physical: raw transmission of bits Application Transport Network Data Link Physical

3 The Wireless Web r The emergence and convergence of these technologies enable the “wireless Web” m the wireless classroom m the wireless workplace m the wireless home r My iCORE mandate: design, build, test, and evaluate wireless Web infrastructures r Holy grail: “anything, anytime, anywhere” access to information (when we want it, of course!)

4 Research Interests r Wireless Internet Technologies r MAC Protocol Design r Network Traffic Measurement r Workload Characterization r Traffic Modeling r Network Simulation r Web Performance

5 Wireless Internet Technologies r Mobile devices (e.g., notebooks, laptops, PDAs, cell phones, wearable computers) r Wireless network access m Bluetooth (1 Mbps, up to 3 meters) m IEEE b (11 Mbps, up to 100 meters) m IEEE a (55 Mbps, up to 20 meters) r Operating modes: m Infrastructure mode (access point) m Ad hoc mode

6 Example: Infrastructure Mode Carey Internet Access Point (AP) cnn.com

7 Example: Ad Hoc Mode r Multi-hop “ad hoc” networking Carey Sean

8 Example: Ad Hoc Mode r Multi-hop “ad hoc” networking Carey Sean

9 Example: Ad Hoc Mode r Multi-hop “ad hoc” networking Carey Sean

10 Example: Ad Hoc Mode r Multi-hop “ad hoc” networking Carey Sean

11 MAC Protocol Design r Identify performance problems in wireless Medium Access Control (MAC) protocols r Examples: IEEE b WLANs m Unfairness problems [Xiao MSc 2004] m Effects of node mobility [Bai 2004] m “Bad Apple” phenomenon [Cao 2004] m TCP on multi-hop ad hoc networks [Gupta 2004] m Multi-channel MAC protocols [Kuang 2004] m Multi-rate multi-channel protocols [Wu 2005]

12 Network Traffic Measurement r Collect and analyze packet-level traces from a live network, using special equipment r Process traces, statistical analysis r Diagnose performance problems (network, protocol, application)

13 Example: tcpdump Trace > TCP : win: 5840 S > TCP : win: 5792 SA > TCP : win: 5840 A > TCP : win: 5840 PA > TCP : win: 5792 A > TCP : win: 5792 A > TCP : win: 5792 A > TCP : win: 8688 A > TCP : win: A > TCP : win: 5792 PA > TCP : win: 5792 A > TCP : win: A > TCP : win: 5792 A > TCP : win: 5792 A > TCP : win: 5792 A > TCP : win: A > TCP : win: A > TCP : win: 5792 FPA > TCP : win: A > TCP : win: FA > TCP : win: 5792 A

14 Example: TELUS Mobility Project r Data Template and Example – XYZ Platform Code Definition ============== 20FSCH Data Rate 21FSCH Data Burst Start Time 22FSCH Data Burst End Time 200FSCH Active Set Report Time 21x FSCH Active Set Cell ID ('x' is a number) 22x FSCH Active Ste Sector ID ('x' is a number) 30 RSCH Data Rate 31RSCH Data Burst Start Time 32 RSCH Data Burst End Time 300RSCH Active Set Report Time 31xRSCH Active Set Cell ID ('x' is a number) 32xRSCH Active Ste Sector ID ('x' is a number) 40FCH Data Start Time 41FCH Data End Time 100FCH Active Set Report Time 11xFCH Active Set Cell ID ('x' is a number) 12x FCH Active Ste Sector ID ('x' is a number) 50IMSI 60Frequency 70SID x804ce0401aa

15 Workload Characterization r Try to understand the salient features of network, protocol, application, and user behaviour on the Internet r Example: Web server workloads [Arlitt96] m Zipf-like document referencing behaviour m Lots of “one-time” referencing of documents m Heavy-tailed file size distributions m Self-similar network traffic profile m Session duration and call arrival process

16 Traffic Modeling r Construct programs and statistical models that capture the empirically-observed network traffic behaviours r Allows flexible, controlled, repeatable generation of workloads for experiments r Examples: m Web client workload model m MPEG compressed video model m Self-similar Ethernet LAN traffic model m WebTraff GUI: Web proxy workload generator

17 Example: Web Workload Generation

18 Network Simulation r Use computer simulation to study the packet-level behaviour of the Internet, its protocols, its applications, and its users r Examples: m Improving Web performance over ADSL m Understanding the effects of user mobility on Mobile IP routing and protocol performance m Studying the design, scalability, and performance of Web server and Web proxy caching architectures

19 Web Performance r Explore techniques to improve the performance and scalability of the Web r Examples: m Clustered Web servers m Load balancing policies m Web prefetching strategies m Web proxy caching architectures m Improvements to HTTP and TCP protocols

20 Web Server Client 1 Client 2 Client 3 Client C... Example: Web Server Benchmarking

21 Summary r Wireless Internet Performance Lab (UofC) r Experimental Laboratory for Internet Systems and Applications (UofS/UofC,CFI) r iCORE Research Team: m Five full-time research staff (Web, perf. eval., simulation, wireless, traffic modeling, network measurement) plus 8 graduate students r Research Collaborations: m UofC, UofA, UofS, TRLabs, CS/ECE m HP, TELUS Mobility, SaskTel, Nortel… r Industrially-relevant experimental research on network protocol performance