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Department of Computer Science Southern Illinois University Edwardsville Dr. Hiroshi Fujinoki and Kiran Gollamudi E-mail: {hfujino, kgollam}@siue.edu Problem Definition Response Time The elapsed time between the end of an inquiry on a computer system and the beginning of a response Problem • Long response time • Transmission time • Operating system overhead Due to high web traffic load FAT look-up, following a sector-chain, multiple clients etc Delay Causes We have 3 different causes of delay Operating system overhead RECEIVER SENDER Internet Internet Routing Overhead + Error/Flow control Overhead Network Protocol Processing Overhead HTTP Client/Server model Terms Defined HTTP Client HTTP Server TCP Sync TCP Sync ACK • Response time HTTP Get • Transmission time Transmittingrequested file Requested file starts arriving. Time Existing work for Client/Server model The following are the existing techniques to reduce response time and transmission delay Existing Methods Caching Mirroring Server Clustering Object Packaging Objective To improve response time and transmission time by : • Single request for the multiple files • Reduced network protocol overhead during the transmission at routers CRC calculation overhead Memory copies • Reduced number of packets by minimizing fragmentation • Reduced OS overhead at a web server Reduced FAT lookups Flow control and error control Concept Of Object Packaging Object Packaging: • Is a collection of web files in a web site • Files are sequentially packed without compression Number of objects Pointer File #1 Object Offset Fields File header Object Package File #n Packaging Format Of Object Packaging Object Information Field File name subfield sub File size subfield sub File attribute subfield sub Number of objects (files) subfield sub • Object Information Field: Contains the information of the packed files • Data Field: Contains the contents of the requested files Sub field •A collection of the the sizes names of the files Number of objects: Tells how many packed filesorare there • •File Attribute Subfield: Each file is contained a binary, text, executable •A collection of of the contained files Experiment Modeling Test-Bed Requested Files Requests Hub Client Web Server Local Disk Traffic Monitor • Client Machine: The host that requests the server for the data • Hub : Broadcasts every packet to every port • Traffic Monitor: Monitors the all the traffic (packets) that are passing Experiment Design Experimental Setup • Files with 1K, 4K and 10K bytes are placed in the server machine • Factors measured for both the existing method and object Packaging 1. Average response time 2. Average bytes transferred 3. Number of Transferred packets 4. Transmission time Experimental Output • The figures represent all factors measured with different file sizes. File 4K Existing Method Percentage 100% Object Packaging 80% 60% 40% 20% 0% Avg. Time No.Of Pkts Bytes transferred File 10K Time Existing Method 100% Object Packaging Percentage 80% 60% 40% 20% 0% Avg. Time No.Of Pkts Bytes transferred •Percentage to the existing method Experimental Output •100% •Transferred bytes •80% •Response time •60% •40% •Transferred packets •20% •0% •1K •4K •10K •Average file size (in bytes) File size = 4K Percentage to the existing method 100% File size = 10K 80% File size = 1K 60% Number of transferred packets relative to the existing method 40% 20% 0% 0 25 50 Number of transferred files 75 100 Summary • Multiple file transmissions by object packaging proposed • No modification of an operating system at the server side nor transmission protocol at routers required • Object packaging is efficient in reducing response time and transmission load and time Future work There are two on-going activities and future works On Going Activities 1. Measuring the CPU load, response time and propagation delay on the server 2. Measuring all the above but for multiple clients Future Works 1. Perform the experiments using a Gigabit Ethernet cable 2. To observe the scalability References 1. M. Arlitt and C. Williamson, “Web Server Workload Characterization: The Search for Invariants,” Proceedings of the 1996 ACM SIGMETRICS Conference on the Measurement and Modeling of Computer Systems,” May 1996, pp. 126-137 2. GVU’s WWW User Surveys, Georgia Institute of Technology URL: http://www.gvu.gatech.edu/user_surveys 3. J. Ousterhout, “Why Aren't Operating Systems Getting Faster As Hardware?,” Proceedings of Summer 1990 USENIX Conference, June 1990, pp. 247-256 4. P. Druschel, “Operating System Support for High-Speed Networking,” Communications of the ACM, vol. 39, no. 2, September 1996, pp. 41-51 5. P. Markatos, “Speeding-up TCP/IP: Faster Processors Are not Enough,” Proceedings of the 21st IEEE International Performance, Computing, and Communications Conference, April 2002, pp. 341-345 References 6. M. Busari and C. Williamson, “On the Sensitivity of Web Proxy Cache Performance to Workload Characteristics,” Proceedings of IEEE INFOCOM,April 2001, pp. 1225-1234 7. J. Dilley, “The Effect of Consistency on Cache Response Time,” IEEE Network, vol. 14, no. 3, May/June 2000, pp. 24-28 8. S. Glassman, “A caching relay for the Worldwide Web,” Computer Networks and ISDN Systems, vol. 27, no. 2, October 1994, pp. 165-173 9. D. Lee, “PreFetch Document Caching to Improve Worldwide Web User Response Time,” Master's Thesis. Virginia Polytechnic Institute and State University, March 1996 10. J. Mogul, “Squeezing More Bits Out of HTTP Caches,” IEEE Network, vol. 14, no.3, May/June 2000, pp. 6-14 11. Figures of Red hat and Windows from the internet sites. The End Thank you !!! Client Side Caching Advantages • Reduced latency • Reduced server load • Reduced bandwidth consumption in a network Disadvantages • Effective only when same files are repeatedly requested • Additional hardware or expertise is required • No benefit if object is not cached • May be unable to cache multimedia content • Unable to cache dynamically generated content Go To Previous Slide Mirroring Technique Advantages • Improves throughput • Complete redundancy of data • Fast recovery from a disk failure Disadvantages • Expensive • Low capacity • No improvement in data access speed Go To Previous Slide Server Clustering Advantages • Fail over • Scalability • Fault resilience • Load balancing Disadvantages • Requires investment for hardware • Request dispatcher may be a bottleneck Go To Previous Slide