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Gary M. Weiss and Jeffrey Lockhart Fordham University, New York, NY

A Comparison of Alternative Client/Server Architectures for Ubiquitous Mobile Sensor-Based Applications. Gary M. Weiss and Jeffrey Lockhart Fordham University, New York, NY. Motivation. Mobile sensors becoming ubiquitous Especially via smartphones

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Gary M. Weiss and Jeffrey Lockhart Fordham University, New York, NY

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  1. A Comparison of Alternative Client/Server Architectures for Ubiquitous Mobile Sensor-Based Applications Gary M. Weiss and Jeffrey Lockhart Fordham University, New York, NY UbiMI Workshop @ UBICOMP Sept. 8 2012

  2. Motivation • Mobile sensors becoming ubiquitous • Especially via smartphones • Various architectures are possible ranging from “smart client” to “dumb client” • Each architecture has pros and cons • Worthwhile to enumerate and compare alternative architectures UbiMI Workshop @ UBICOMP Sept. 8 2012

  3. Client/Server Responsibilities • Sensor Collection • Data Processing and Transformation • Decision Analysis/Model Application • Data and Knowledge Reporting Learning/model generation Only step 1 is required UbiMI Workshop @ UBICOMP Sept. 8 2012

  4. ActiTracker: an Illustrative Example • Main focus of WISDM lab • Monitors smartphone accelerometer and uses the data to perform activity recognition • Activities: walk, jog, stairs, sit, stand, lie down • Results available via the Web UbiMI Workshop @ UBICOMP Sept. 8 2012

  5. Client Configuration 1: Dumb Client • Sensor Collection: • Actitracker client collects raw accelerometer data for 3 axes 20 times per second and transmits to server • Data Processing and Transformation • Every 10 sec. server aggregates raw samples into a single example described by several dozen features • Decision Analysis/Model Application • Server applies predictive model to examples; activity classified and saved to database • Data and Knowledge Reporting • User queries server DB any time via web interface UbiMI Workshop @ UBICOMP Sept. 8 2012

  6. Four Basic Client Configurations UbiMI Workshop @ UBICOMP Sept. 8 2012

  7. Model Generation/Data Mining • Mobile devices have CPU power to build models • Only makes sense to build a model on the client device if will apply it on the client • Thus model construction on device only for CC-3 or CC-4 • In CC-1 and CC-2 either model hardcoded into client or downloaded from server • Data mining not always required • Can be done dynamically (on client or server) or statically • Our research shows dynamically generated personal models outperform general (impersonal) models1 1 Gary M. Weiss and Jeffrey W. Lockhart. The Impact of Personalization on Smartphone-Based Activity Recognition, Papers from the AAAI-12 Workshop on Activity Context Representation: Techniques and Languages, AAAI Technical Report WS-12-05, Toronto, Canada, 98-104. UbiMI Workshop @ UBICOMP Sept. 8 2012

  8. Factors for Architectural Comparison • Resource usage • battery, CPU, memory, transmission bandwidth • Scalability • Support for many mobile devices • Access to data • Researchers and others may want raw data • Transformed data loses information • With raw data can alter features for data mining and regenerate results UbiMI Workshop @ UBICOMP Sept. 8 2012

  9. Factors for Architectural Comparison • Privacy/Security • Users will want to keep data secure and/or private • User Interface • Users want aesthetics (screen size) & accessibility • Crowdsourcing • Some applications will require a central server in order to aggregate data from multiple users/devices • Navigation software that tracks traffic UbiMI Workshop @ UBICOMP Sept. 8 2012

  10. Analysis of CC-1 Dumb Client • Resource Usage • Unclear. Resource usage minimized except heaviestuse of transmission bandwidth (power drain) • Scalability • Poor since maximizes server work • Actitracker’s server can handle 942 simult. users • Access to Data • Best since all raw data can be preserved on server • But Actitracker requires 791 MB/month per user. UbiMI Workshop @ UBICOMP Sept. 8 2012

  11. Analysis of CC-1 Dumb Client • Privacy/Security: • Poor: The more data sent the greater the risk • User Interface: • Good: data and results on server and can be viewed over Internet • Crowdsourcing • Best: All data available on server UbiMI Workshop @ UBICOMP Sept. 8 2012

  12. Analysis of CC-2 (client transforms data) • Similar to CC-1 except: • Less data to transmit so bandwidth/energy savings • For Actitracker 95% reduction in data • But more processing which takes up CPU and power • More scalable (less server work) • Less access to data (raw data not available) • Slight improvement in privacy/security (no raw data) • Minimal impact on user interface (results still on server) • Crowdsourcing only on aggregated data UbiMI Workshop @ UBICOMP Sept. 8 2012

  13. Analysis of CC-3 (client applies model) • Resource usage: • more processing on the client (more CPU and power); but only need to transmit results • Much more scalable: server only collects results • Access to data: only results available • Much improved security/privacy • results may not be nearly as sensitive • Can still view results via web-based interface • Can only crowdsource on results UbiMI Workshop @ UBICOMP Sept. 8 2012

  14. Analysis of CC-4 (client does it all) • About same as CC-3 • not sending results saves little power • Perfectly scalable: no server • No access to data • Good security/privacy: nothing leaves device • Can only view results on the device • Not accessible from other places and small screens • Cannot even crowdsource results UbiMI Workshop @ UBICOMP Sept. 8 2012

  15. Summary • Resource usage: unclear • Scalability: smart client best • Access to data: dumb client best • Security/Privacy: smart client best • User Interface: smart client worst • Centralized Data: dumb client best • One approach: support multiple architectures • approach taken by our research group UbiMI Workshop @ UBICOMP Sept. 8 2012

  16. More Info on WISDM • Go to wisdmproject.com • Actitracker should be ready for beta in 1 month • Actitracker.com • Papers available from: • http://www.cis.fordham.edu/wisdm/publications.php • My contact info: • gweiss@cis.fordham.edu UbiMI Workshop @ UBICOMP Sept. 8 2012

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