Enhancing mobile apps to use sensor hubs without programmer effort

UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Volumn , Issue , 2015, Pages 227-238

  Shen, Haichen ^a   Balasubramanian, Aruna ^b   Lamarca, Anthony ^c   Wetherall, David ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

^b STONY BROOK UNIVERSITY   (United States)

^c INTEL CORPORATION   (United States)

Author keywords

Dynamic taint tracking; Energy efficiency; Machine learning; Mobile sensing; Sensor hub

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SYSTEMS PROGRAMMING; ENERGY EFFICIENCY; LEARNING SYSTEMS; SEMANTICS;

APPLICATION SEMANTICS; AVR MICROCONTROLLERS; CONTINUOUS SENSING; DYNAMIC TAINT TRACKING; GOOGLE PLAYS; MOBILE APPS; MOBILE SENSING;

UBIQUITOUS COMPUTING;

EID: 84960940771     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2750858.2804260     Document Type: Conference Paper

References (45)

1. Activity recognitionclient: http://developer.android.com/reference/com/google/android.
2. Apple M7. http://en.wikipedia.org/wiki/Apple-M7.
3. BeWell Mobile Application. https://play.google.com/store/apps/details?id=org.bewellapp&hl=en.
4. Intel Context Sensing SDK. https://software. intel.com/en-us/context-sensing-sdk.
5. ios core motion framework reference: https://developer.apple.com/library/ios.
6. Physicaloid : Physical computing with a smartphone. http://www.physicaloid.com/?lang=en.
7. RF, Wi-Fi and Other Wireless Microcontroller-Based Solutions. http://www.atmel.com/products/wireless/.
8. XMega-A3BU XPlained. http://www.atmel.com/tools/XMEGA-A3BUXPLAINED.aspx.
9. Atmel: USB Device CDC Application. http://www.atmel.com/Images/doc8447.pdf, 2011.
10. TivaWare Sensor Library User Guide. http://www.ti.com/lit/ug/spmu371/spmu371.pdf, 2015.
11. Agarwal, Y., Hodges, S., Chandra, R., Scott, J., Bahl, P., and Gupta, R. Somniloquy: Augmenting network interfaces to reduce pc energy usage. In Proceedings of the 6th USENIX symposium on Networked systems design and implementation, NSDI09, USENIX Association (Berkeley, CA, USA, 2009), 365-380.
12. Arzt, S., Rasthofer, S., Fritz, C., Bodden, E., Bartel, A., Klein, J., Le Traon, Y., Octeau, D., and McDaniel, P. Flowdroid: Precise context, flow, field, object-sensitive and lifecycle-Aware taint analysis for android apps. In Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 14, ACM (New York, NY, USA, 2014), 259-269.
13. Austin, T. H., and Flanagan, C. Permissive dynamic information flow analysis. In Proceedings of the 5th ACM SIGPLAN Workshop on Programming Languages and Analysis for Security, PLAS 10, ACM (New York, NY, USA, 2010), 3:1-3:12.
14. Bao, T., Zheng, Y., Lin, Z., Zhang, X., and Xu, D. Strict control dependence and its effect on dynamic information flow analyses. In Proceedings of the 19th international symposium on Software testing and analysis, ACM (2010), 13-24.
15. Bo, C., Li, X.-Y., Jung, T., Mao, X., Tao, Y., and Yao, L. Smartloc: Push the limit of the inertial sensor based metropolitan localization using smartphone. In Proceedings of the 19th Annual International Conference on Mobile Computing & Networking, MobiCom 13, ACM (New York, NY, USA, 2013), 195-198.
16. Cao, Y., Fratantonio, Y., Bianchi, A., Egele, M., Kruegel, C., Vigna, G., and Chen, Y. Automatically detecting implicit control flow transitions through the android framework. In In Proceeding of the Network and Distributed System Security Symposium (NDSS15 (2015).
17. Clause, J., Li, W., and Orso, A. Dytan: A generic dynamic taint analysis framework. In Proceedings of the 2007 international symposium on Software testing and analysis, ACM (2007), 196-206.
18. DATASHEET, A. 8-bit avr® microcontroller with 4/8/16/32k bytes in-system programmable flash, 2010.
19. Denning, D. E., and Denning, P. J. Certification of programs for secure information flow. Commun. ACM 20, 7 (July 1977), 504-513.
20. Enck, W., Gilbert, P., Chun, B.-G., Cox, L. P., Jung, J., McDaniel, P., and Sheth, A. N. Taintdroid: An information-flow tracking system for realtime privacy monitoring on smartphones. In OSDI (2010).
21. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., and Witten, I. H. The WEKA data mining software: An update. ACM SIGKDD explorations newsletter 11, 1 (2009), 10-18.
22. Hao, S., Liu, B., Nath, S., Halfond, W. G., and Govindan, R. Puma: Programmable ui-Automation for large-scale dynamic analysis of mobile apps. In Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 14, ACM (New York, NY, USA, 2014), 204-217.
23. Hill, J., Szewczyk, R., Woo, A., Hollar, S., Culler, D., and Pister, K. System architecture directions for networked sensors. In ACM SIGOPS operating systems review, vol. 34, ACM (2000), 93-104.
24. Jeff, B. Advances in big. little technology for power and energy savings. ARM White Paper (2012).
25. Kang, M. G., McCamant, S., Poosankam, P., and Song, D. Dta++: Dynamic taint analysis with targeted control-flow propagation. In NDSS (2011).
26. Kansal, A., Saponas, T. S., Brush, A. J. B., McKinley, K. S., Mytkowicz, T., and Ziola, R. The latency, accuracy, and battery (lab) abstraction: programmer productivity and energy efficiency for continuous mobile context sensing. In OOPSLA, ACM (2013), 661-676.
27. Lin, F. X., Wang, Z., and Zhong, L. K2: A mobile operating system for heterogeneous coherence domains. In ASPLOS (2014).
28. Lin, X. F., Wang, Z., LiKamWa, R., and Zhong, L. Reflex: Using low-power processors in smartphones without knowing them. In ASPLOS (2012).
29. Lisa, E. Intel Unveils New Merrifield Smartphone Chip With Integrated Sensor Hub. http://blog.laptopmag.com/intel-merrifield-smartphone-chip.
30. Liu, J., Priyantha, B., Hart, T., Ramos, H. S., Loureiro, A. A. F., and Wang, Q. Energy efficient gps sensing with cloud offloading. In Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems, SenSys 12, ACM (New York, NY, USA, 2012), 85-98.
31. Morales, M. An Introduction to the Tiva C Series Platform of Microcontrollers. Tech. rep., Texas Instruments, April 2013.
32. Nath, S. Ace: Exploiting correlation for energy-efficient and continuous context sensing. In Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services, MobiSys 12, ACM (New York, NY, USA, 2012), 29-42.
33. Priyantha, B., Lymberopoulos, D., and Liu, J. Littlerock: Enabling energy-efficient continuous sensing on mobile phones. In IEEE Pervasive Computing (2011).
34. Ra, M.-R., Priyantha, B., Kansal, A., and Liu, J. Improving energy efficiency of personal sensing applications with heterogeneous multi-processors. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing, UbiComp 12, ACM (New York, NY, USA, 2012), 1-10.
35. Ravindranath, L., Nath, S., Padhye, J., and Balakrishnan, H. Automatic and scalable fault detection for mobile applications. In Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 14, ACM (New York, NY, USA, 2014), 190-203.
36. Rosen, S., Qian, Z., and Mao, Z. M. Appprofiler: A flexible method of exposing privacy-related behavior in android applications to end users. In Proceedings of the Third ACM Conference on Data and Application Security and Privacy, CODASPY 13, ACM (New York, NY, USA, 2013), 221-232.
37. Shih, E., Bahl, P., and Sinclair, M. J. Wake on wireless: An event driven energy saving strategy for battery operated devices. In Proceedings of the 8th annual international conference on Mobile computing and networking, MobiCom 02, ACM (New York, NY, USA, 2002), 160-171.
38. Sorber, J., Banerjee, N., Corner, M. D., and Rollins, S. Turducken: hierarchical power management for mobile devices. In Proceedings of the 3rd international conference on Mobile systems, applications, and services, MobiSys 05, ACM (New York, NY, USA, 2005), 261-274.
39. Stankovic, J. A., Wood, A. D., and He, T. Realistic applications for wireless sensor networks. In Theoretical Aspects of Distributed Computing in Sensor Networks. Springer, 2011, 835-863.
40. Stone, M. Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society. Series B (Methodological) (1974), 111-147.
41. Valĺee-Rai, R., Co, P., Gagnon, E., Hendren, L., Lam, P., and Sundaresan, V. Soot: A java bytecode optimization framework. In CASCON First Decade High Impact Papers, IBM Corp. (2010), 214-224.
42. Vallee-Rai, R., and Hendren, L. J. Jimple: Simplifying java bytecode for analyses and transformations.
43. Vogt, P., Nentwich, F., Jovanovic, N., Kirda, E., Kruegel, C., and Vigna, G. Cross-site scripting prevention with dynamic data tainting and static analysis. In In Proceeding of the Network and Distributed System Security Symposium (NDSS07 (2007).
44. Zhang, L., Gordon, M. S., Dick, R. P., Mao, Z. M., Dinda, P., and Yang, L. Adel: An automatic detector of energy leaks for smartphone applications. In Proceedings of the Eighth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis, CODES+ISSS 12, ACM (New York, NY, USA, 2012), 363-372.
45. Zhuang, Z., Kim, K.-H., and Singh, J. P. Improving energy efficiency of location sensing on smartphones. In Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, MobiSys 10, ACM (New York, NY, USA, 2010), 315-330.