Lecture 9

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Unformatted text preview: ary –  Sequen8al request/responses, even when to different servers –  Mul8ple TCP connec8on setups to the same server –  Mul8ple TCP slow- start phases •  Network is not used effec8vely –  Worse with many small resources / page 136 Parallel Connec8ons •  One simple way to reduce PLT –  Browser runs mul8ple (8, say) HTTP instances in parallel –  Server is unchanged; already handled concurrent requests for many clients •  How does this help? –  Single HTTP wasn’t using network much … –  So parallel connec8ons aren’t slowed much –  Pulls in comple8on 8me of last fetch 137 22 11/26/13 Persistent Connec8ons •  Parallel connec8ons compete with each other for network resources –  1 parallel client ≈ 8 sequen8al clients? –  Exacerbates network bursts, and loss •  Persistent connec8on alterna8ve –  Make 1 TCP connec8on to 1 server –  Use it for mul8ple HTTP requests 138 Persistent Connec8ons (2) One request per connec8on Sequen8al requests per connec8on Pipelined requests per connec8on 139 23 11/26/13 Persistent Connec8ons (3) •  Widely used as part of HTTP/1.1 –  Supports op8onal pipelining –  PLT benefits depending on page structure, but easy on network •  Issues with persistent connec8ons –  How long to keep TCP connec8on? –  Can it be slower? (Yes. But why?) 140 Web Caching •  Users ohen revisit web pages –  Big win from reusing local copy! –  This is caching Local copies Cache Network Server •  Key ques8on: –  When is it OK to reuse local copy? 141 24 11/26/13 Web Caching (2) •  Locally determine copy is s8ll valid –  Based on expiry informa8on such as “Expires” header from server –  Or use a heuris8c to guess (cacheable, freshly valid, not modified recently) –  Content is then available right away Cache Network Server 142 Web Caching (3) •  Revalidate copy with...
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This document was uploaded on 04/04/2014.

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