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Simulating the power consumption of large-scale sensor network applications

Published:03 November 2004Publication History

ABSTRACT

Developing sensor network applications demands a new set of tools to aid programmers. A number of simulation environments have been developed that provide varying degrees of scalability, realism, and detail for understanding the behavior of sensor networks. To date, however, none of these tools have addressed one of the most important aspects of sensor application design: that of power consumption. While simple approximations of overall power usage can be derived from estimates of node duty cycle and communication rates, these techniques often fail to capture the detailed, low-level energy requirements of the CPU, radio, sensors, and other peripherals.

In this paper, we present, a scalable simulation environment for wireless sensor networks that provides an accurate, per-node estimate of power consumption. PowerTOSSIM is an extension to TOSSIM, an event-driven simulation environment for TinyOS applications. In PowerTOSSIM, TinyOS components corresponding to specific hardware peripherals (such as the radio, EEPROM, LEDs, and so forth) are instrumented to obtain a trace of each device's activity during the simulation runPowerTOSSIM employs a novel code-transformation technique to estimate the number of CPU cycles executed by each node, eliminating the need for expensive instruction-level simulation of sensor nodes. PowerTOSSIM includes a detailed model of hardware energy consumption based on the Mica2 sensor node platform. Through instrumentation of actual sensor nodes, we demonstrate that PowerTOSSIM provides accurate estimation of power consumption for a range of applications and scales to support very large simulations.

References

  1. Agilent 54832B Infiniium Oscilloscope. http://www.agilent.com.Google ScholarGoogle Scholar
  2. A. C. Amit Sinha. Jouletrack - a web based tool for software energy profiling. In Proceedings of the 38th Design Automation Conference, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Analog Devices AD620 Instrumentation Ampifier. http://www.analog.com.Google ScholarGoogle Scholar
  4. Atmel Corp. ATmega128(L) Datasheet. http://www.atmel.com/dyn/resources/prod_documents/2467S.pdf.Google ScholarGoogle Scholar
  5. D. Brooks, V. Tiwari, and M. Martonosi. Wattch: a framework for architectural-level power analysis and optimizations. In ISCA, pages 83--94, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. K. Fall and K. Varadhan. The ns manual. http://www.isi.edu/nsnam/ns/doc/index.html.Google ScholarGoogle Scholar
  7. J. Flinn and M. Satyanarayanan. Powerscope: a tool for profiling the energy usage of mobile applications. In Second IEEE Workshop on Mobile Computing Systems and Applications, pages 2--10, Feb. 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. D. Gay, P. Levis, R. von Behren, M. Welsh, E. Brewer, and D. Culler. The nesC language: A holistic approach to networked embedded systems. In Proc. Programming Language Design and Implementation (PLDI), June 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. L. Girod, J. Elson, A. Cerpa, T. Stathopoulos, N. Ramanathan, and D. Estrin. EmStar: A software environment for developing and deploying wireless sensor networks. In Proc. USENIX'04, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. E. Culler, and K. S. J. Pister. System architecture directions for networked sensors. In Architectural Support for Programming Languages and Operating Systems, pages 93--104, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. M. Karir. atemu - Sensor Network Emulator / Simulator / Debugger. http://www.isr.umd.edu/CSHCN/research/atemu/.Google ScholarGoogle Scholar
  12. C. Karlof, N. Sastry, and D. Wagner. Tinysec. http://www.cs.berkeley.edu/ nks/tinysec/.Google ScholarGoogle Scholar
  13. P. Levis, N. Lee, M. Welsh, and D. Culler. TOSSIM: Accurate and scalable simulation of entire TinyOS applications. In Proceedings of the First ACM Conference on Embedded Networked Sensor Systems (SenSys) 2003, Nov. 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. J. Liu, D. Nicol, F. Perrone, M. Liljenstam, C. Elliot, and D. Pearson. Simulation modeling of large-scale ad-hoc sensor networks. In Proc. European Interoperability Workshop 2001, London, England, June 2001.Google ScholarGoogle Scholar
  15. S. Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong. TAG: A Tiny AGgregation Service for Ad-Hoc Sensor Networks. In Proc. the 5th OSDI, December 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. G. C. Necula, S. McPeak, S. Rahul, and W. Weimer. CIL: Intermediate language and tools for analysis and transformation of C programs. In Proceedings of Conference on Compilier Construction, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. S. Park, A. Savvides, and M. B. Srivastava. SensorSim: A simulation framework for sensor networks. In Proc. MSWIM 2000, Boston, MA, August 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. S. Park, A. Savvides, and M. B. Srivastava. Simulating networks of wireless sensors. In Proc. the 2001 Winter Simulation Conference, Arlington, VA, December 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. L. F. Perrone and D. M. Nicol. A scalable simulator for TinyOS applications. In Proc. the 2002 Winter Simulation Conference, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. T. A. Roth. Simulavr: an AVR simulator. http://www.nongnu.org/simulavr/.Google ScholarGoogle Scholar
  21. G. Simon, P. Vülgyesi, M. Maróti, and A. Lédeczi. Simulation-based optimization of communication protocols for large-scale wireless sensor networks. In Proc. 2003 IEEE Aerospace Conference, Big Sky, MT, March 2003.Google ScholarGoogle ScholarCross RefCross Ref
  22. T. Stathopoulos. EmTOS: TinyOS/NesC Emulation for EmStar. http://cvs.cens.ucla.edu/emstar/ref/emtos.html.Google ScholarGoogle Scholar
  23. S. Sundresh, W.-Y. Kim, and G. Agha. SENS: A sensor, environment and network simulator. In Proc. 37th Annual Simulation Symposium (ANSS '04), 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. R. Szewczyk, J. Polastre, A. Mainwaring, and D. Culler. Lessons from a sensor network expedition. In Proc. the First European Workshop on Wireless Sensor Networks (EWSN), January 2004.Google ScholarGoogle ScholarCross RefCross Ref
  25. A. R. T. K. Tan and N. Jha. Emsim: An energy simulation framework for an embedded operating system. In Proceedings of the International Conference on Circuits and Systems, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  26. T. K. Tan, A. Raghunathan, G. Lakshminarayana, and N. K. Jha. High-level software energy macro-modeling. In Design Automation Conference, pages 605--610, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library

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              cover image ACM Conferences
              SenSys '04: Proceedings of the 2nd international conference on Embedded networked sensor systems
              November 2004
              338 pages
              ISBN:1581138792
              DOI:10.1145/1031495

              Copyright © 2004 ACM

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              Publication History

              • Published: 3 November 2004

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