Timecard: Controlling User-Perceived Delays in Server-based Mobile Applications

1. Timecard: Controlling User-Perceived Delays in Server-based Mobile Applications Lenin Ravindranath, Jitendra Padhye, Ratul Mahajan, Hari Balakrishnan Instrumented App Servers should adapt to external delays to control user-perceived delay Timecard provides two APIs for server developers Mobile apps becoming dominant mode of data access Developer App Service Timecard.dll PredictRemainingTime (responseSize); GetElapsedTime(); config Cloud Services App Instrumenter GetElapsedTime(); PredictRemainingTime (responseSize); Desired end-to-end delay Predicted downlink delay and app processing delay for a given data size Time elapsed since the user initiated the request App Store Adapt processing time Mobile Apps Overhead Adapt response Compute Memory Network Battery Significant variability in external delays 0.1% <1% <1% low Server Deployment Tradeoff between response time and quality of result Server processing • Modified two services and two apps to use Timecard Request Response Server TCP state Phone model Uplink Downlink Phone model Reading sensors Datasize Link quality (3G, HSPA+, LTE, Wifi) MobileAds Service App App DNS and TCP connect App App User click Parsing and Rendering Radio State (Radio wakeup) Highly variable User perceived delay Within 50ms of the target delay 90% of the time User perceived delay Track Transaction Time Synchronization Predict Downlink Delay Predict Processing Delay Track transaction across asynchronous threads and between mobile device and server • 90% percentile data size: 37KB • RTT matters than throughput • Predict RTT • TCP window state matters • Multiple RTTs • Estimate TCP Window & number of RTTs • Complicated by middleboxes • Periodic time sync probes from app to server • Find drift and offset between clocks • Use server clock as reference clock • Client maps local time to server time • Parsing and rendering delay depends on data size • Processing delay dependent on the phone hardware Server Data size Send response Request handler Spawn workers Server Threads Server TC Middlebox TC Efficient technique for probing • Aware of the radio state and traffic • Minimal extra delays • Energy efficient Model downlink delay • Recent RTT • Response size • Bytes already transferred • Network provider& client OS App App TC Facebook TC Background Thread GPS callback Web callback Web request Model processing delay • Response size • Phone model UI dispatcher Event handler GPS start UI Thread Thread start Triggered by transaction tracking TC Pass around transaction context TC