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Adaptive File Transfers for Diverse Environments. Himabindu Pucha, Purdue University. David G. Andersen, Carnegie Mellon University Michael Kaminsky, Intel Research Pittsburgh Michael Kozuch, Intel Research Pittsburgh. Goal.
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Adaptive File Transfers for Diverse Environments Himabindu Pucha, Purdue University David G. Andersen,Carnegie Mellon University Michael Kaminsky,Intel Research Pittsburgh Michael Kozuch,Intel Research Pittsburgh
Goal Correctly and efficiently transfer files in wide range of scenarios
Network peers Goal Correctly and efficiently transfer files in wide range of scenarios • Data backup, code update • Software synchronization • Different network speeds Scenario: Data backup, code update Scenario: Software synchronization file in-place Gigabit LAN –DSL links Network Search for similar files Receiver Sender Different disk loads
Challenges • Resources have widely varying performance • Resource performance changes dynamically • Support receivers with different initial state • Do not require resources to be set up in advance
dsync: Design dsync uses all available resources effectively dsync scheduler Network Disk
dsync: Design • Discovers available resources using exposed backpressure information • From disk: “I’m busy writing, don’t read from me.” • From network: “I have lots of incoming packets, don’t spend time doing IO or computation.” • Schedules intelligently across available resources • Disk: use a pre-computed index and/or search entire disk using heuristics • Network:Schedule remaining chunks, least likely to be found on disk
dsync: Preliminary Results Throughput for 1 GB file on a 1 Gbps link dsync defers disk operations when network is faster than disk Bonus: dsync provides best of BitTorrent, rsync, scp …
dsync: Preliminary Results Average download time across 45 receivers, 50% similar file in-place dsync speedup: 5x vs. rsync 2x vs. SET dsync rapidly locates similar files and effectively combines them with peering dsync correctly uses backpressure to defer disk operations when network is faster than disk
dsync: Preliminary Results dsync correctly uses backpressure to defer disk operations when network is faster than disk
Network peers Goal Correctly and efficiently transfer files in wide range of scenarios • Data backup • Code update • Software synchronization • Different network speeds Scenario: Software synchronization Scenario: Data backup Scenario: Code update file in-place Gigabit LAN –DSL links Network Search for similar files Receiver Sender Different disk loads
dsync: Design • Discovers available resources using exposed backpressure information • From disk: “I’m busy writing, don’t read from me.” • From network: “I have lots of incoming packets, don’t spend time doing IO or computation.” • Schedules intelligently across available resources • Disk: use a pre-computed index and/or search entire disk using heuristics • Network:Schedule remaining chunks, least likely to be found on disk
Challenges • Correctly use resources with widely varying performance characteristics • Dynamically adapt to changes in resource performance • Support receivers with different initial state • Do not require resources to be set up in advance