ACM Home Page
Please provide us with feedback. Feedback
Energy-efficient multihop reprogramming for sensor networks
Full text PdfPdf (1.76 MB)
Source
ACM Transactions on Sensor Networks (TOSN) archive
Volume 5 ,  Issue 2  (March 2009) table of contents
Article No. 16  
Year of Publication: 2009
ISSN:1550-4859
Authors
Sandeep Kulkarni  Michigan State University, East Lansing, MI
Limin Wang  VMware, Inc., Palo Alto, CA
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 30,   Downloads (12 Months): 251,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1498915.1498922
What is a DOI?

ABSTRACT

Reprogramming of sensor networks is an important and challenging problem, as it is often necessary to reprogram the sensors in place. In this article, we propose MNP, a multihop reprogramming service designed for sensor networks. One of the problems in reprogramming is the issue of message collision. To reduce the problem of collision, we propose a sender selection algorithm that attempts to guarantee that in a given neighborhood there is at most one source transmitting the program at a time. Furthermore, our sender selection is greedy in that it tries to select the sender that is expected to have the most impact. We use pipelining to enable fast data propagation. MNP is energy efficient because it reduces the active radio time of a sensor node by putting the node into “sleep” state when its neighbors are transmitting a segment that is not of interest. We call this type of sleep contention sleep. To further reduce the energy consumption, we add noreq sleep, where sensor node goes to sleep if none of its neighbors is interested in receiving the segment it is advertising. We also introduce an optional init sleep to reduce the energy consumption in the initial phase of reprogramming. Finally, we investigate the performance of MNP in different network settings.


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
 
2
Crossbow Technology, Inc. 2003. Mote In-Network Programming User Reference Version 20030315. Crossbow Technology, Inc. http://webs.cs.berkeley.edu/tos/tinyos-1.x/doc/Xnp.pdf.
 
3
 
4
 
5
 
6
7
8
 
9
 
10
Kulkarni, S. S. and Arumugam, M. 2005. SS-TDMA: A self-stabilizing MAC for sensor networks. In Sensor Network Operations. IEEE Press.
 
11
Kulkarni, S. S. and Arumugam, M. 2006. Infuse: A TDMA based data dissemination protocol for sensor networks. Int. J. Distrib. Sensor Netw.
 
12
13
14
15
 
16
17
 
18
19
20
 
21
Shen, C.-C., Srisathapornphat, C., and Jaikaeo, C. 2001. Sensor information networking architecture and applications. IEEE Personel Commun. Mag. 8, 4, 52--59.
 
22
Stathopoulos, T., Heidemann, J., and Estrin, D. 2003. A remote code update mechanism for wireless sensor networks. Tech. rep., University of California at Los Angeles.
 
23
Team, T. O. S. U. N. 2004. ExScal: Extreme scaling in sensor networks for target detection, classification, tracking. DARPA, http://www.cse.ohio-state.edu/exscal.
 
24
van Hoesel, L. F. W., Nieberg, T., Kip, H. J., and Havinga, P. J. M. 2004. Advantages of a tdma-based, energy-efficient, self-organizing mac protocol for wsns. IEEE VTC (spring).
 
25
Ye, W., Heidemann, J., and Estrin, D. 2002. An energy-efficient MAC protocol for wireless sensor networks. In Proceedings of the 21st International Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), 1567--1576.

Collaborative Colleagues:
Sandeep Kulkarni: colleagues
Limin Wang: colleagues