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Improving Energy Efficiency of Location Sensing on Smartphones
Kyu-Han Kim and Jatinder Pal SinghDeutsche Telekom Inc. R&D Lab USA
Zhenyun ZhuangGeorgia Institute of Technology
June 18, 2010
ACM MobiSys 2010 © Kyu-Han Kim
MotivationLocation 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 ConsumptionPower-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 MechanismsDifferent 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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Sensing ParametersCritical 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 CharacterizationFour 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
LBA1 LBA2 LBA3
GPS NET ACC
8
Outline
System Characterization Design Principles Software Architecture Evaluation Results Conclusion
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Sensing Substitution (SS)Adaptive selection of GPS and NET
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LBA1 LBA2 LBA3
GPS NET ACC
Tradeoff in power, accuracy, and availability Static selection (compile time) Assume GPS is always better than NET
N
Y
N
YUse NET
Is NET accurate?
LBA requirement
Is NET available?
Area profiles
RequestGPS
Use GPS
Sensing suppRession (SR)Leverage user mobility information from low-power sensors
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LBA1 LBA2 LBA3
GPS NET ACC
Continuous sensing might be wasteful Use of low-power sensor for state detection False positive or negative on movement
time
SuppressionGPS
Sensorreading Moving
Stationary
Sensing Piggybacking (SP)Exploit existing location sensing requests
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LBA1 LBA2 LBA3
GPS NET ACC
Multiple LBAs cause duplicate GPS sensing One-time registration can be monitored Multi-time registration matters
time
GPS GPS
NET NET
GPS
t0 t1
LBA1
LBA2
LBA3
Sensing Adaptation (SA) & Integrated OperationExpose a control knob for location sensing parameters to users
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LBA1 LBA2 LBA3
GPS NET ACC
Users might prefer longer operating time Adjust sensing parameters (time, distance) Adaptation degree (e.g., 200%: 30s1min)
time
Substitution
Piggybacking
Suppression
Adaptation
t0
LBA1 Starts
t1
LBA2 Starts
t2
User Stationary
t3
BatteryLow
t4
User Moving
t5
LBA1 Stops
Outline
System Characterization Design Principles Software Architecture Evaluation Results Conclusion
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Software Architecture and Deployment ModelUse 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
SS SP
SR SA
Location Sensing
SensorManager
LocationManager
BroadcastReceiver
Outline
System Characterization Design Principles Software Architecture Evaluation Results Conclusion
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Performance EvaluationMethodology
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
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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
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SR reduces the number of GPS invocations with the help of sensor.
Integrated Operations Enabled All Four Design Principles
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Energy saving of up to 58% after one hour.
Setup: P-1 (Two LBAs w/ 30 sec interval, adaptation degree (200%))
ConclusionImproving 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)
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Four design principles have been proposed to conserve energy: substitution, suppression, piggybacking, and adaptation.
