improving energy efficiency of location sensing on smartphones 이시혁[email protected] z....

Improving energy efficiency of location sens-ing on smartphones

이시혁

[email protected]

Z. Zhuang et al., in Proc. of ACM MobiSys 2010, pp. 315-330, 2010.

S FT COMPUTING @ YONSEI UNIV . KOREA16

Contents

• Introduction– Motivation– Energy consumption of GPS– Energy consumption of GPS and NET– Problem characterization

• Design principles– Sensing Substitution(SS)– Sensing suppRession(SR)– Sensing Piggybacking(SP)– Sensing Adaptation(SA)– Integrated operation

• Software architecture and system implement• Performance evaluation• Conclusion

2


Motivation

• Location-based applications(LBAs) have become increasingly popular

• Most smartphones have two location sensing mechanisms– GPS(Global Positioning System)– NET(Network-based Triangulation : reachable cell tower, Wi-Fi AP)

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Energy consumption of GPS

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Drop to 94% : GPS disabled

Drop to 79% : GPS enabled


Energy consumption of GPS and NET

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Drop to 93% : NET only

Drop to 83% : GPS only


Problem characterization

• Static use of location sensing mechanisms

• Absence of use of power-efficient sensors to optimize location sensing

• Lack of cooperation among multiple LBAs

• Unawareness of battery level

6GPS NET ACC


Sensing Substitution(SS)

• Tradeoff in Power, accuracy, and availability• Static selection• Assume GPS is always better than NET

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Sensing suppRession(SR)

• Continuous sensing might be wasteful

• Use of low-power sensor for state detection

• False positive or negative on movement

8


Sensing Piggybacking(SP)

• Multiple LBAs cause duplicate GPS sensing

• One-time registration can be monitored

• Multi-time registration matters

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Sensing Adaptation(SA)

• Users might prefer longer operating time

• Adjust sensing parameters (time, distance)

• Adaptation degree (e.g., 200%: 30s -> 1min)

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Integrated operation

• SS : GPS or NET• SR : Using other sensor(low-power sensor )• SP : Duplicate GPS sensing(multiple LBAs)• SA : Adjust sensing parameters

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Software architecture and system implementation

• Android framework– Middleware solution

• Implement overview– OS version 1.5 Cupcake– Inside the default “Security & location”

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Sensing Substitution (SS)

• Area 1, both GPS and Net are available– accuracy: GPS>Net

• Area 2, both GPS and Net are available – accuracy: GPS = Net (similar)

• Area 3, only GPS is available

• Area 4, only Net is available

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Performance evaluation


• Static and moving

• Using accelerometer

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Sensing SuppRession (SR)Performance evaluation


• Using two LBAs with different starting time

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Sensing Piggybacking (SP)Performance evaluation


• Two scenarios with different battery levels

• Sensing updates every 1minute -> every 2 minutes

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Sensing Adaptation (SA)Performance evaluation


• Trace from particular user– Commuter– Route in Silicon Valley, California

• Setup – Running two LBAs concurrently at low battery level (SA, SP)– Adaptation degree : 200%– Same GPS sensing frequency of every 30 seconds– Starting with 15-second difference

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Integrated resultsPerformance evaluation


Conclusion

• We consider the problem of energy efficient location sensing on smartphones

• Four critical factors – static use of location sensing mechanisms (SS)– absence of use of power-efficient sensors to optimize location sens-

ing (SR)– lack of sensing cooperation among multiple LBAs (SP)– unawareness of battery level (SA)

• Prototype– Android OS : modified the application framework– Reduce the GPS usage by up to 98% (static state)– Improve battery life by up to 75%

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Performance evaluation

• Sensing Substitution

• Sensing Suppression

• Sensing Piggybacking

• Sensing Adaptation

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Appendix

improving energy efficiency of location sensing on smartphones 이시혁[email protected] z....

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