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Removing the memory limitations of sensor networks with flash-based virtual memory
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Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007 table of contents
Lisbon, Portugal
SESSION: Sensor networks table of contents
Pages: 131 - 144  
Year of Publication: 2007
ISBN ~ ISSN:0163-5980 , 978-1-59593-636-3
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Authors
Andreas Lachenmann  Universität Stuttgart, Germany
Pedro José Marrón  Universität Stuttgart, Germany
Matthias Gauger  Universität Stuttgart, Germany
Daniel Minder  Universität Stuttgart, Germany
Olga Saukh  Universität Stuttgart, Germany
Kurt Rothermel  Universität Stuttgart, Germany
Sponsor
SIGOPS: ACM Special Interest Group on Operating Systems
Publisher
ACM  New York, NY, USA
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ABSTRACT

Virtual memory has been successfully used in different domains to extend the amount of memory available to applications. We have adapted this mechanism to sensor networks, where, traditionally, RAM is a severely constrained resource. In this paper we show that the overhead of virtual memory can be significantly reduced with compile-time optimizations to make it usable in practice, even with the resource limitations present in sensor networks.

Our approach, ViMem, creates an efficient memory layout based on variable access traces obtained from simulation tools. This layout is optimized to the memory access patterns of the application and to the specific properties of the sensor network hardware.

Our implementation is based on TinyOS. It includes a pre-compiler for nesC code that translates virtual memory accesses into calls of ViMem's runtime component. ViMem uses flash memory as secondary storage. In order to evaluate our system we have modified nontrivial existing applications to make use of virtual memory. We show that its runtime overhead is small even for large data sizes.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Atmel Corporation. 4-megabit DataFlash AT45DB041B Datasheet, 2005.
 
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J. Beutel, O. Kasten, F. Mattern, K. Römer, F. Siegemund, and L. Thiele. Prototyping wireless sensor network applications with BTnodes. In Proc. of the 1st European Workshop on Sensor Networks, pp. 323--338, 2004.
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D. Gay, P. Levis, D. Culler, and E. Brewer. nesC 1.2 Language Reference Manual, 2005.
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14
 
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D. J. Hatfield and J. Gerald. Program restructuring for virtual memory. IBM Systems Journal, 10(3):168--192, 1971.
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J. Koshy and R. Pandey. Remote incremental linking for energy-efficient reprogramming of sensor networks. In Proc. of the 2nd European Workshop on Wireless Sensor Networks, pp. 354--365, 2005.
 
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P. J. Marrón, M. Gauger, A. Lachenmann, D. Minder, O. Saukh, and K. Rothermel. FlexCup: A flexible and efficient code update mechanism for sensor networks. In Proc. of the Third European Workshop on Wireless Sensor Networks, pp. 212--227, 2006.
 
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Maté web page. http://www.cs.berkeley.edu/~pal/mate-web/.
 
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TinyOS CVS repository. http://tinyos.cvs.sourceforge.net/tinyos/.
 
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Collaborative Colleagues:
Andreas Lachenmann: colleagues
Pedro José Marrón: colleagues
Matthias Gauger: colleagues
Daniel Minder: colleagues
Olga Saukh: colleagues
Kurt Rothermel: colleagues