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1 CPSC 601.38: Project Brainstorming Session Carey Williamson Department of Computer Science University of Calgary.

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Presentation on theme: "1 CPSC 601.38: Project Brainstorming Session Carey Williamson Department of Computer Science University of Calgary."— Presentation transcript:

1 1 CPSC 601.38: Project Brainstorming Session Carey Williamson Department of Computer Science University of Calgary

2 2 PROJECT OVERVIEW H A “typical” course project might involve: –design/build/obtain appropriate testbed, environment, or platform for your project –extend/customize as needed –obtain relevant data/measurements needed –design suitable experiment: clear goal, identify factors, levels, performance metrics –obtain and present (new/interesting) results

3 3 Some Data Sets and Traces H Web server access logs (1996) H Web proxy access logs (1998) H MPEG video traces (20 x 40,000 frames) H ISP measurements (4 traces, 1-2 minutes) H FrameRelay/ATM traces (5 traces) H Bellcore Ethernet LAN trace (1989) H TCP/IP packet traces (LBL, 24 hours, 1.8M) H See also the “Internet Traffic Archive”

4 4 Some Available Simulators H ATM-TN simulator (ATM cell-level) H Clustered Web server simulator (dws) H Web proxy caching hierarchies (Muda) H Distributed Web proxy simulator H IP-TN simulator (U of C) H IP-TNE (emulator) (U of C) H LBL’s ns-2 simulator (TCP packet level)

5 5 Some Useful Tools H Synthetic Web proxy workload generation H Web client traffic model (mosaic, 1995) H LRD traffic analysis (R/S, V-T, AC, etc) H GUI for traffic modeling/analysis (synTraff) H Wavelet-based traffic model (Ram) H Synthetic MPEG video trace generation H SimKit programming language (UofC)

6 6 Issues and Ideas H Improving/extending ProWGen –temporal locality; document mods; scaling H Web proxy caching hierarchies H Hierarchical vs distributed caching H Web response time modeling H Improving network TCP flow model (dws) H Wavelet-based traffic forecasting H Wavelength assignment in WDM networks

7 1. ATM-TN System Overview ATM-T SimKit ESS ATM MF UNIX Hardware SPARC, KSR, SGI ATM-N WarpKit SMTW Report Generation Scripts TMF workstation Input Data Set Output Data Set Report

8 TMF Traffic Models SimKit ESS ATM MF UNIX Operating System Sequential: UNIX Workstations (SGI, SPARC, DEC, HP) Parallel: SGI Power Challenge, SPARC 1000 Switch and Network Models X SMTW WarpKitWaiKit CBR Poisson Ethernet JPEG/MPEG Web TCP/IP/AAL5 ABR

9 9 2. Distributed Web Server Model 1 2 3 N Web Clients Cache Manager Server Nodes Dispatcher (Front End) Object Store File Server

10 10 Server Parameters H Num server nodes H Mem cache size H Disk cache size H Cache replacement policy for each (LRU, LFU, SIZE, DUAL) H Comm. latency H Cache consistency H Dispatch policy (DNS, RR, Redirect, Load) H Request distribution policy (requests, bw, conns, affinity,...) H Server bandwidth H Per-request bandwidth H BW scaling model

11 11 Performance Metrics H Load balancing –requests –bytes –bandwidth –connections –clients H Relative improvement versus RR, Rand, etc H Cache performance –document hit rate –byte hit rate H Comm. overhead H Avg response time H Avg inflation factor H Others...

12 12 Web Clients Web Servers Proxy server Aggregate Workload 3. Web Proxy Caching Model

13 13 Hierarchical Proxy Caching Simulation Model Proxy server Web Servers Web Clients Proxy server Upper Level (Parent) Complete Overlap No Overlap Partial Overlap (50%) Lower Level (Children)

14 14 Factors and Levels H Cache size H Cache Replacement Policy –Recency-based LRU –Frequency-based LFU-Aging –Size-based GD-Size H Workload Characteristics –One-timers, Zipf slope, tail index, correlation, temporal locality model

15 15 ProWGen Conceptual View ProWGen Software 1ZacL P r Zipf F s LLCD -1 0 +1 Correlation Input Parameters Synthetic Workload

16 16 Key Workload Characteristics H “One-timers” (60-70% useless!!!) H Zipf-like document referencing popularity H Heavy-tailed file size distribution (i.e., most files small, but most bytes are in big files) H Correlations (if any) between document size and document popularity (debate!) H Temporal locality (temporal correlation between recent past and near future references) [Mahanti et al. 2000]


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