ACM Home Page
Please provide us with feedback. Feedback
Digital Library logoTake a look at the new version of this page: [ beta version ]. Tell us what you think.
Programming sensor networks using abstract regions
Source Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1 table of contents
San Francisco, California
Pages: 3 - 3  
Year of Publication: 2004
Authors
Matt Welsh  Harvard University
Geoff Mainland  Harvard University
Sponsor
USENIX: USENIX Association
Publisher
USENIX Association  Berkeley, CA, USA
Bibliometrics
Downloads (6 Weeks): n/a,   Downloads (12 Months): n/a,   Citation Count: 35
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Review this Article  

ABSTRACT

Wireless sensor networks are attracting increased interest for a wide range of applications, such as environmental monitoring and vehicle tracking. However, developing sensor network applications is notoriously difficult, due to extreme resource limitations of nodes, the unreliability of radio communication, and the necessity of low power operation. Our goal is to simplify application design by providing a set of programming primitives for sensor networks that abstract the details of low-level communication, data sharing, and collective operations.

We present abstract regions, a family of spatial operators that capture local communication within regions of the network, which may be defined in terms of radio connectivity, geographic location, or other properties of nodes. Regions provide interfaces for identifying neighboring nodes, sharing data among neighbors, and performing efficient reductions on shared variables. In addition, abstract regions expose the trade-off between the accuracy and resource usage of communication operations. Applications can adapt to changing network conditions by tuning the energy and bandwidth usage of the underlying communication substrate. We present the implementation of abstract regions in the TinyOS programming environment, as well as results demonstrating their use for building adaptive sensor network applications.


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.

 
1
[1] S. Adlakha, S. Ganeriwal, C. Schurgers, and M. B. Srivastava. Density, accuracy, latency and lifetime tradeoffs in wireless sensor networks - a multidimensional design perspective. In review, 2003.
 
2
 
3
 
4
[4] A. Boulis, S. Ganeriwal, and M. B. Srivastava. Aggregation in sensor networks: An energy - accuracy tradeoff. In Proc. IEEE workshop on Sensor Network Protocols and Applications, 2003.
 
5
[5] R. Brooks, P. Ramanathan, and A. Sayeed. Distributed target classification and tracking in sensor networks. Proceedings of the IEEE, November 2003.
 
6
[6] Center for Embedded Network Sensing. Contaminant transport monitoring. http://cens.ucla.edu/Research/ Applications/ctm.htm.
 
7
[7] Center for Information Technology Research in the Interest of Society. Smart buildings admit their faults. http: //www.citris.berkeley.edu/applications/ disaster_response/smartbuil%dings.html, 2002.
8
 
9
[9] R. X. Cringely. Chase Cringely: Finding Meaning in a Lost Life. http://www.pbs.org/cringely/pulpit/ pulpit20020425.html.
 
10
[10] D. Ganesan, B. Greenstein, D. Perelyubskiy, D. Estrin, and J. Heidemann. An evaluation of multi-resolution search and storage in resource-constrained sensor networks. In Proc. the First ACM Conference on Embedded Networked Sensor Systems (Sen-Sys 2003), November 2003.
11
 
12
[12] B. Greenstein, D. Estrin, R. Govindan, S. Ratnasamy, and S. Shenker. DIFS: A distributed index for features in sensor networks. In Proc. the First IEEE International Workshop on Sensor Network Protocols and Applications, May 2003.
 
13
[13] W. Gropp, E. Lusk, and A. Skjellum. Using MPI: Portable Parallel Programming with the Message Passing Interface. MIT Press, Cambridge, Massachusetts, 1994.
14
15
 
16
[16] J. M. Hellerstein, W. Hong, S. Madden, and K. Stanek. Beyond average: Towards sophisticated sensing with queries. In Proc. the 2nd International Workshop on Information Processing in Sensor Networks (IPSN '03), March 2003.
17
18
19
 
20
[20] V. A. Kottapalli, A. S. Kiremidjian, J. P. Lynch, E. Carryer, T. W. Kenny, K. H. Law, and Y. Lei. Two-tiered wireless sensor network architecture for structural health monitoring. In Proc. the SPIE 10th Annual International Symposium on Smart Structures and Materials, San Diego, CA, March 2000.
21
 
22
[22] D. Li, K. Wong, Y. H. Hu, and A. Sayeed. Detection, classification and tracking of targets in distributed sensor networks. IEEE Signal Processing Magazine, 19(2), March 2002.
 
23
[23] X.-Y. Li, P.-J. Wan, Y. Wang, and O. Frieder. Sparse power efficient topology for wireless networks. In Proc. 35th Annual Hawaii International Conference on System Sciences, January 2002.
24
 
25
[25] 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.
26
27
 
28
[28] S. Nath, Y. Ke, P. B. Gibbons, B. Karp, and S. Seshan. Iris-Net: An architecture for enabling sensor-enriched Internet service. Technical Report IRP-TR-03-04, Intel Research Pittsburgh, June 2003.
 
29
[29] K. S. Pister. Tracking vehicles with a uav-delivered sensor network. http://robotics.eecs.berkeley.edu/ ~pister/29Palms0103/, March 2001.
30
 
31
[31] J. Shewchuk. Delaunay refinement algorithms for triangular mesh generation. Computational Geometry: Theory and Applications , 22(1-3):21-74, May 2002.
32
 
33
[33] M. Welsh. Exposing resource tradeoffs in region-based communication abstractions for sensor networks. In Proc. the 2nd ACM Workshop on Hot Topics in Networks (HotNets-II), November 2003.
 
34
[34] M. Welsh, D. Myung, M. Gaynor, and S. Moulton. Resuscitation monitoring with a wireless sensor network. In Supplement to Circulation: Journal of the American Heart Association, October 28, 2003.
35
36
 
37
38

CITED BY  35

Collaborative Colleagues:
Matt Welsh: colleagues
Geoff Mainland: colleagues