Improving Energy Efficiency of Location Sensing on Smartphones Kyu-Han Kim and Jatinder Pal Singh Deutsche Telekom Inc. R&D Lab USA Zhenyun Zhuang Georgia Institute of Technology June 18, 2010 ACM MobiSys 2010 © Kyu-Han Kim

Motivation Location sensing is a core but power-intensive component  Location-sensing is a core component on smartphones  Location-Based Service (LBS), social networking, health monitoring, etc.  However, location-sensing is a power-intensive component.  Energy efficiency on sensing mechanisms [Paek’10, Lin’10]  Lacking system-level support on smartphones w/ rich applications! Location-Based Applications OS/Hardware (GPS, NET, etc.) Location Sensing

Outline  System Characterization  Design Principles  Software Architecture  Evaluation Results  Conclusion 3

4 GPS Energy Consumption Power-hungry operation  Setup: P-1 (1 LBA w/ GPS disabled) and P-2 (1 LBA w/ GPS enabled) 15% GPS DOES consume a large amount of energy on smartphones.

5 Multiple Location-Based Applications (LBAs) More power consumption  Setup: P-1 (w/ 1 LBA, 2 min interval) and P-2 (w/ 2 LBAs, 2 min) 5% Multiple LBAs further increases location-sensing overheads.

6 Multiple Location-Sensing Mechanisms Different energy consumption  Setup: P-1 (1 LBA w/ NET) and P-2 (1 LBA w/ GPS) 10% Different location-sensing methods have performance tradeoff.

7 Sensing Parameters Critical when battery level is low  Setup: P-1 (1 LBA w/ GPS 15 sec interval) and P-2 (1 LBA w/ 2min) 9% Sensing parameters are critical to conserve energy on smartphones.

System Characterization Four key limitations of energy-efficient location sensing  Static selection of multiple location sensing mechanisms  No use of less power-intensive sensors (e.g., Accelerometer)  Lack of sensing cooperation among multiple LBAs  Unawareness of battery level and sensing parameters LBA1LBA2LBA3 GPSNETACC 8

Outline  System Characterization  Design Principles  Software Architecture  Evaluation Results  Conclusion 9

Sensing Substitution (SS) Adaptive selection of GPS and NET 10 LBA1LBA2LBA3 GPSNETACC  Tradeoff in power, accuracy, and availability  Static selection (compile time)  Assume GPS is always better than NET N Y N Y Use NET Is NET accurate? LBA requirement Is NET available? Area profiles Request GPS Use GPS

Sensing suppRession (SR) Leverage user mobility information from low-power sensors 11 LBA1LBA2LBA3 GPSNETACC  Continuous sensing might be wasteful  Use of low-power sensor for state detection  False positive or negative on movement time Suppression GPS Sensor reading Moving Stationary

Sensing Piggybacking (SP) Exploit existing location sensing requests 12 LBA1LBA2LBA3 GPSNETACC  Multiple LBAs cause duplicate GPS sensing  One-time registration can be monitored  Multi-time registration matters time GPS NET GPS t0t0 t1t1 LBA1 LBA2 LBA3

Sensing Adaptation (SA) & Integrated Operation Expose a control knob for location sensing parameters to users 13 LBA1LBA2LBA3 GPSNETACC  Users might prefer longer operating time  Adjust sensing parameters (time, distance)  Adaptation degree (e.g., 200%: 30s  1min) time Substitution Piggybacking Suppression Adaptation t0t0 LBA1 Starts t1t1 LBA2 Starts t2t2 User Stationary t3t3 Battery Low t4t4 User Moving t5t5 LBA1 Stops

Outline  System Characterization  Design Principles  Software Architecture  Evaluation Results  Conclusion 14

15 Software Architecture and Deployment Model Use open Android Operating Systems (OS)  Within open Android framework  Application transparency  Rich API and open platforms  Deployment model  A new system image or periodic image upgrade in various smartphones  Application-level API for LBA developers Applications Android Platform Linux Kernel SSSP SRSA Location Sensing Sensor Manager Location Manager Broadcast Receiver

Outline  System Characterization  Design Principles  Software Architecture  Evaluation Results  Conclusion 16

Performance Evaluation Methodology  Used the trace collected from a particular user  Silicon valley areas  Walking from home to office (~30 min)  Analysis  Derived the number of GPS invocations reduced by each design principle  Translated the number into the energy  Confirmed the saving using the real-time traffic LBA.

Sensing Substitution (SS) Energy-efficient selection of sensing mechanisms 18 One LBA w/GPS  Setup SS reduces the number of GPS invocations up to 50%.  Results Area 1: GPS/NET available (Gps > Net) Area 2: GPS/NET available (Gps ≈ Net) Area 3: GPS Only Area 4: NET Only 0 min

Sensing Suppression (SR) Periodic use of low-power sensor reduces no. of GPS invocations  Setup: One hour (50% stationary: 50% moving) location sensing 19 SR reduces the number of GPS invocations with the help of sensor.

Integrated Operations Enabled All Four Design Principles 20 Energy saving of up to 58% after one hour.  Setup: P-1 (Two LBAs w/ 30 sec interval, adaptation degree (200%))

Conclusion Improving energy efficiency of location sensing on smartphones  Location sensing on smartphones is extremely power-hungry.  Key energy factors have been identified, including multiple sensing mechanisms, multiple LBAs, use of low-power sensor, and sensing parameters.  A prototype of the proposed design using Android OS and the improvement in energy efficiency have been demonstrated.  Future work  Application-aware tuning of location-sensing parameters  Indoor location-sensing (e.g., use of WiFi networks) 21  Four design principles have been proposed to conserve energy: substitution, suppression, piggybacking, and adaptation.

Q&A Thank You Contact Information: 22