1 / 16

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

hovan
Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related