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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
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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
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Outline System Characterization Design Principles Software Architecture Evaluation Results Conclusion 3
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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.
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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.
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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.
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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.
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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
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Outline System Characterization Design Principles Software Architecture Evaluation Results Conclusion 9
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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
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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
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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
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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
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Outline System Characterization Design Principles Software Architecture Evaluation Results Conclusion 14
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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
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Outline System Characterization Design Principles Software Architecture Evaluation Results Conclusion 16
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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.
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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
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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.
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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%))
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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.
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Q&A Thank You Contact Information: kyu-han.kim@telekom.com 22
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