The latency, accuracy, and battery (LAB) abstraction: Programmer productivity and energy efficiency for continuous mobile context sensing

ACM SIGPLAN Notices

Volumn 48, Issue 10, 2013, Pages 661-676

  Kansal, Aman ^a   Saponas, Scott ^a   Bernheim Brush, A J ^a   McKinley, Kathryn S ^a   Mytkowicz, Todd ^a   Ziola, Ryder ^a  

^a MICROSOFT RESEARCH   (United States)

Author keywords

Mobile sensing; Sensor API

Indexed keywords

DIVERSE APPLICATIONS; ENERGY OPTIMIZATION; INFERENCE ALGORITHM; MOBILE APPLICATIONS; MOBILE SENSING; PROGRAMMER PRODUCTIVITY; SENSING ALGORITHMS; SENSOR API; CONTEXT SENSING; CURRENT SENSING; MOBILE CONTEXT; PHONE BATTERIES; SOCIAL CONNECTION;

ABSTRACTING; ALGORITHMS; APPLICATION PROGRAMMING INTERFACES (API); DRAIN CURRENT; ENERGY EFFICIENCY; HARDWARE; INFERENCE ENGINES; OPTIMIZATION; PRODUCTIVITY; SENSORS; BLUEPRINTS; ELECTRIC BATTERIES; LABORATORIES;

LABORATORIES; ENERGY EFFICIENCY;

EID: 84888814402     PISSN: 15232867     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (40)

1. N. Banerjee, A. Rahmati, M. D. Corner, S. Rollins, and L. Zhong. Users and batteries: Interactions and adaptive energy management in mobile systems. In Ubicomp, 2007.
2. G. Challen and M. Hempstead. The case for power-agile computing. In HotOS, 2011.
3. Y. Chon, E. Talipov, H. Shin, and H. Cha. Mobility predictionbased smartphone energy optimization for everyday location monitoring. In Sensys, 2011. ISBN 978-1-4503-0718-5.
4. D. Chu, N. D. Lane, T. T.-T. Lai, C. Pang, X. Meng, Q. Guo, F. Li, and F. Zhao. Balancing energy, latency and accuracy for mobile sensor data classification. In ACM SenSys, 2011.
5. M. Cohen, H. S. Zhu, E. E. Senem, and Y. D. Liu. Energy types. SIGPLAN Not., 47(10):831-850, Oct. 2012. ISSN 0362-1340.
6. S. Consolvo, D. W. McDonald, T. Toscos, M. Y. Chen, J. Froehlich, B. Harrison, P. Klasnja, A. LaMarca, L. LeGrand, R. Libby, I. Smith, and J. A. Landay. Activity sensing in the wild: A field trial of ubifit garden. In CHI, 2008.
7. I. Constandache, S. Gaonkar, M. Sayler, R. Choudhury, and L. Cox. Enloc: Energy-efficient localization for mobile phones. In IEEE Infocom, pages 2716-2720, April 2009.
8. J. Dean and S. Ghemawat. MapReduce: Simplified data processing on large clusters. In OSDI, 2004.
9. E. Ertin, N. Stohs, S. Kumar, A. Raij, M. al'Absi, and S. Shah. AutoSense: Unobtrusively wearable sensor suite for inferring the onset, causality, and consequences of stress in the field. In SenSys, 2011.
10. M. Haridasan, I. Mohomed, D. Terry, C. A. Thekkath, and L. Zhang. Startrack next generation: A scalable infrastructure for track-based applications. In OSDI, 2010.
11. Y. Ju, Y. Lee, J. Yu, C. Min, I. Shin, and J. Song. Symphoney: A coordinated sensing flow execution engine for concurrent mobile sensing applications. In Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems, SenSys'12, pages 211-224, New York, NY, USA, 2012. ACM. ISBN 978-1-4503-1169-4.
12. S. Kang, J. Lee, H. Jang, H. Lee, Y. Lee, S. Park, T. Park, and J. Song. SeeMon: Scalable and energy-efficient context monitoring framework for sensor-rich mobile environments. In Proceedings of the 6th international conference on Mobile systems, applications, and services, MobiSys'08, pages 267-280, New York, NY, USA, 2008. ACM. ISBN 978-1-60558-139-2.
13. S. Kang, Y. Lee, C. Min, Y. Ju, T. Park, J. Lee, Y. Rhee, and J. Song. Orchestrator: An active resource orchestration framework for mobile context monitoring in sensor-rich mobile environments. In Pervasive Computing and Communications (PerCom), 2010 IEEE International Conference on, pages 135-144, 2010.
14. D. H. Kim, Y. Kim, D. Estrin, and M. B. Srivastava. Sensloc: Sensing everyday places and paths using less energy. In ACM SenSys, 2010.
15. M. B. Kjaergaard, J. Langdal, T. Godsk, and T. Toftkjaer. Entracked: Energy-efficient robust position tracking for mobile devices. In MobiSys, 2009.
16. N. D. Lane, E. Miluzzo, H. Lu, D. Peebles, T. Choudhury, and A. T. Campbell. A survey of mobile phone sensing. Comm. Mag., 48:140-150, September 2010.
17. F. X. Lin, Z. Wang, R. LiKamWa, and L. Zhong. Reflex: Using low-power processors in smartphones without knowing them. In ASPLOS, 2012.
18. K. Lin, A. Kansal, D. Lymberopoulos, and F. Zhao. Energyaccuracy trade-off for continuous mobile device location. In MobiSys, pages 285-298, 2010.
19. H. Lu, J. Yang, Z. Liu, N. D. Lane, T. Choudhury, and A. T. Campbell. The Jigsaw continuous sensing engine for mobile phone applications. In SenSys, 2010.
20. H. Lu, A. J. B. Brush, B. Priyantha, A. K. Karlson, and J. Liu. Speakersense: Energy efficient unobtrusive speaker identification on mobile phones. Pervasive Computing, 6696:188-205, 2011.
21. M. Mun, D. Estrin, J. Burke, and M. Hansen. Parsimonious mobility classification using gsm and wifi traces. In HotEm-Nets, 2008.
22. S. Nath. Ace: exploiting correlation for energy-efficient and continuous context sensing. In Mobisys, 2012.
23. T. Nick, E. Coersmeier, J. Geldmacher, and J. Goetze. Classifying means of transportation using mobile sensor data. In The 2010 International Joint Conference on Neural Networks (IJCNN), 2010.
24. J. Paek, J. Kim, and R. Govindan. Energy-efficient rateadaptive gps-based positioning for smartphones. In MobiSys, New York, NY, USA, 2010.
25. A. Popescu. Geolocation api specification. http://www.w3.org/TR/ geolocation-API/.
26. B. Priyantha, D. Lymberopoulos, and J. Liu. LittleRock: Enabling energy-efficient continuous sensing on mobile phones. IEEE Pervasive Computing, 10(2), 2011.
27. M. Rabbi, S. Ali, T. Choudhury, and E. Berke. Passive and in-situ assessment of mental and physical well-being using mobile sensors. In Ubicomp, 2011.
28. K. K. Rachuri, M. Musolesi, C. Mascolo, P. J. Rentfrow, C. Longworth, and A. Aucinas. Emotionsense: a mobile phones based adaptive platform for experimental social psychology research. In Ubicomp, 2010.
29. L. Ravindranath, A. Thiagarajan, H. Balakrishnan, and S. Madden. Code in the air: simplifying sensing and coordination tasks on smartphones. In Proceedings of the Twelfth Workshop on Mobile Computing Systems 38; Applications, HotMobile'12, pages 4:1-4:6, New York, NY, USA, 2012. ACM. ISBN 978-1-4503-1207-3.
30. S. Reddy, M. Mun, J. Burke, D. Estrin, M. Hansen, and M. Srivastava. Using mobile phones to determine transportation modes. ACM Trans. Sen. Netw., 6(2):13:1-13:27, Mar. 2010. ISSN 1550-4859.
31. D. Salber, A. K. Dey, and G. D. Abowd. The context toolkit: aiding the development of context-enabled applications. In Proceedings of the SIGCHI conference on Human Factors in Computing Systems, CHI'99, pages 434-441, New York, NY, USA, 1999. ACM. ISBN 0-201-48559-1.
32. T. Sohn, A. Varshavsky, A. Lamarca, M. Y. Chen, T. Choudhury, I. Smith, S. Consolvo, J. Hightower, W. G. Griswold, and E. D. Lara. Mobility detection using everyday gsm traces. In Ubicomp, 2006.
33. J. Sorber, A. Kostandinov, M. Garber, M. Brennan, M. D. Corner, and E. D. Berger. Eon: A language and runtime system for perpetual systems, In SenSys, 2007.
34. S. P. Tarzia, R. P. Dick, P. A. Dinda, and G. Memik. Sonarbased measurement of user presence and attention. In Ubicomp, 2009.
35. A. Thiagarajan, L. Ravindranath, K. LaCurts, S. Madden, H. Balakrishnan, S. Toledo, and J. Eriksson. Vtrack: Accurate, energy-aware road traffic delay estimation using mobile phones. In SenSys, 2009.
36. TI. OMAP 5 mobile application platform, 2011.
37. A. B. Waluyo, W.-S. Yeoh, I. Pek, Y. Yong, and X. Chen. Mobisense: Mobile body sensor network for ambulatory monitoring. ACM Trans. Embed. Comput. Syst., 10(1):13:1-13:30, Aug. 2010. ISSN 1539-9087.
38. Y. Wang, J. Lin, M. Annavaram, Q. A. Jacobson, J. Hong, B. Krishnamachari, and N. Sadeh. A framework of energy efficient mobile sensing for automatic user state recognition. In MobiSys, 2009.
39. T. Yan, D. Chu, D. Ganesan, A. Kansal, and J. Liu. Fast app launching for mobile devices using predictive user context. In Mobisys, 2012.
40. Z. Zhuang, K.-H. Kim, and J. P. Singh. Improving energy efficiency of location sensing on smartphones. In MobiSys, 2010.