Improving energy efficiency of location sensing on smartphones Z. Zhuang et al., in Proc. of ACM MobiSys 2010, pp , 2010.

S FT YONSEI UNIV. KOREA 16 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 1

S FT YONSEI UNIV. KOREA 16 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) 2

S FT YONSEI UNIV. KOREA 16 Energy consumption of GPS 3 Drop to 94% : GPS disabled Drop to 79% : GPS enabled

S FT YONSEI UNIV. KOREA 16 Energy consumption of GPS and NET 4 Drop to 93% : NET only Drop to 83% : GPS only

S FT YONSEI UNIV. KOREA 16 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 5 GPSNETACC

S FT YONSEI UNIV. KOREA 16 Sensing Substitution(SS) Tradeoff in Power, accuracy, and availability Static selection Assume GPS is always better than NET 6

S FT YONSEI UNIV. KOREA 16 Sensing suppRession(SR) Continuous sensing might be wasteful Use of low-power sensor for state detection False positive or negative on movement 7

S FT YONSEI UNIV. KOREA 16 Sensing Piggybacking(SP) Multiple LBAs cause duplicate GPS sensing One-time registration can be monitored Multi-time registration matters 8

S FT YONSEI UNIV. KOREA 16 Sensing Adaptation(SA) Users might prefer longer operating time Adjust sensing parameters (time, distance) Adaptation degree (e.g., 200%: 30s -> 1min) 9

S FT YONSEI UNIV. KOREA 16 Integrated operation SS : GPS or NET SR : Using other sensor(low-power sensor ) SP : Duplicate GPS sensing(multiple LBAs) SA : Adjust sensing parameters 10

S FT YONSEI UNIV. KOREA 16 Software architecture and system implementation Android framework –Middleware solution Implement overview –OS version 1.5 Cupcake –Inside the default “Security & location” 11

S FT YONSEI UNIV. KOREA 16 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 12 Performance evaluation

S FT YONSEI UNIV. KOREA 16 Static and moving Using accelerometer 13 Sensing SuppRession (SR) Performance evaluation

S FT YONSEI UNIV. KOREA 16 Using two LBAs with different starting time 14 Sensing Piggybacking (SP) Performance evaluation

S FT YONSEI UNIV. KOREA 16 Two scenarios with different battery levels Sensing updates every 1minute -> every 2 minutes 15 Sensing Adaptation (SA) Performance evaluation

S FT YONSEI UNIV. KOREA 16 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 16 Integrated results Performance evaluation

S FT YONSEI UNIV. KOREA 16 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 sensing (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% 17

S FT YONSEI UNIV. KOREA 16 Performance evaluation Sensing Substitution Sensing Suppression Sensing Piggybacking Sensing Adaptation 18Appendix