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TRB 2014 - Performance Evaluation of Transit Data Formats on a Mobile Device


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Presented at Transportation Research Board 2014 - Over the last decade mobile devices have changed how we access transportation information. However, many past data formats used in information services have been designed without the processing and energy constraints of mobile devices in mind. Newer standards, such as the Service Interface for Real-time Information (SIRI) v2.0, are including mobile-friendly features that reduce the processing overhead on mobile devices. Coupled with the advances in mobile device processing capabilities, many believe that performance is no longer an issue of concern in modern mobile phones. This paper presents an evaluation of the SIRI data format on a mobile device, which indicates that not only is performance still an issue, but that app developers should carefully consider certain software design choices to avoid exposing mobile users to extensive wait times (e.g., wait for real-time transit arrival information). The results also demonstrate that information service providers should always offer mobile-friendly interfaces (i.e., RESTful web services with JSON encoding) when possible. The benchmarking software is made available as an open-source application so that others can perform their own experiments, and so that app developers can use this library as a foundation for building new applications based on the SIRI format.

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TRB 2014 - Performance Evaluation of Transit Data Formats on a Mobile Device

  1. 1. PERFORMANCE EVALUATION OF TRANSIT DATA FORMATS ON A MOBILE DEVICE Sean J. Barbeau Tatu Saloranta University of South Florida FasterXML, LLC Challenges Mobile device performance is still an issue in terms of processing power, wireless communications, and energy constraints. New data standards should recognize the importance, and limitations, of mobile devices. Slow performance has significant implications on app usability, including user wait times for refreshing real-time info. {Siri: { ServiceDelivery: { ResponseTimestamp: "2012-08-21T12:06:21.485-04:00", VehicleMonitoringDelivery: [ { VehicleActivity: [ { MonitoredVehicleJourney: { LineRef: "MTA NYCT_S40", DirectionRef: "0", FramedVehicleJourneyRef: { DataFrameRef: "2012-08-21", DatedVehicleJourneyRef: "MTA NYCT_20120701CC_072000_S40_0031_S4090_302" }, JourneyPatternRef: "MTA NYCT_S400031", PublishedLineName: "S40", OperatorRef: "MTA NYCT", OriginRef: "MTA NYCT_200001" }} ]} ] } } XML - Cold vs. Pseudo-Warm Starts - Summary JSON - Cold vs. Pseudo-Warm Starts - Summary (n = 30) (n = 30) 6000 25000 5000 20000 Elapsed Time (ms) <Siri xmlns:ns2="" xmlns:ns4= xmlns:ns3="" xmlns=""> <ServiceDelivery> <ResponseTimestamp>2012-09-12T09:28:17.21304:00</ResponseTimestamp> <VehicleMonitoringDelivery> <VehicleActivity> <MonitoredVehicleJourney> <LineRef>MTA NYCT_S40</LineRef> <DirectionRef>0</DirectionRef> <FramedVehicleJourneyRef> <DataFrameRef>2012-09-12</DataFrameRef> <DatedVehicleJourneyRef>MTA NYCT_20120902EE_054000_S40_0031_MISC_437</DatedVehicleJourneyRef> </FramedVehicleJourneyRef> <JourneyPatternRef>MTA NYCT_S400031</JourneyPatternRef> <PublishedLineName>S40</PublishedLineName> <OperatorRef>MTA NYCT</OperatorRef> <OriginRef>MTA NYCT_200001</OriginRef> </MonitoredVehicleJourney> </VehicleActivity> </VehicleMonitoringDelivery> <ServiceDelivery> </Siri> Elapsed Time (ms) Mobile devices and apps have created new opportunities to access real-time transportation information that can save travelers time and money. 15000 4000 3000 10000 2000 5000 1000 0 0 Min. Max. Avg. Cold Starts XML (822 char) 50th percentile 68th percentile 95th percentile Min. Std dev. Max. Avg. 50th percentile 68th percentile 95th percentile Cold Starts Pseudo-Warm Starts Std dev. Pseudo-Warm Starts Pseudo-warm starts produce a 44% performance increase when using XML (due to a large initial overhead), and a 3.96% improvement for JSON JSON (421 char) Typical test response was approx. 5KB Typical test response was approx. 4KB Results JSON - Cold vs. Pseudo-Warm Starts without cache read time (n = 30) 6000 XML vs. JSON Parsing Time - All Requests XML vs. JSON Parsing Time - Summary 18000 16000 16000 14000 14000 Elapsed Time (ms) 20000 18000 Elapsed Time (ms) 20000 12000 10000 8000 6000 5000 4000 12000 10000 JSON 8000 XML Elapsed Time (ms) Evaluation European Committee for Standardization (CEN) is evaluating v2.0 of the Service Interface for Real Time Information (SIRI) (CEN/TS 15531) standard, including new “mobile-friendly” features, including a Representational State Transfer (REST) interface and Javascript Object Notation (JSON) encoding for realtime transit arrival info. Pseudo-Warm Start Results Sample Responses Opportunities 3000 6000 2000 4000 4000 2000 2000 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 JSON 1000 0 Min. Max. Avg. XML 50th percentile 68th percentile 95th percentile Std dev. 0 XML cold start response is almost 18 seconds, over 4 times as long as the JSON cold start response (approx. 4 seconds) Optimizations Improving cold starts is important, since mobile apps are often restarted. Possible optimizations were examined. Min. Max. Avg. 50th percentile Cold Starts 68th percentile 95th percentile Std dev. Pseudo-Warm Starts Pseudo-warm starts significantly improve user wait times by hiding initialization time (cache read time) while the user performs other activities Conclusions • Mobile app performance is important for user experience (e.g., waiting for new real-time info) • Use JSON instead of XML. Cold starts with JSON were avg. of 4 times (14s) faster than XML, with JSON warm starts avg. of 224ms faster SIRIRestClient Android app used to benchmark performance An open-source mobile app was created to benchmark real-time information transfer and processing times between a SIRI interface (MTA Bus Time in NYC) and a mobile device (Samsung Galaxy S3 with Android 4.1.1, 1.5 GHz dual core processor, 2GB RAM and Jackson JSON/XML processor v2.1.2). • Hiding initialization latency from user (via pseudowarm starts) can significantly reduce user wait time Acknowledgements Pseudo-warm starts can improve performance via caching Jackson objects This research was funded by the National Center for Transit Research at the University of South Florida. Scan for full paper