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Set k-cover algorithms for energy efficient monitoring in wireless sensor networks
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Source Information Processing In Sensor Networks archive
Proceedings of the 3rd international symposium on Information processing in sensor networks table of contents
Berkeley, California, USA
SESSION: Oral presentation session VI: coverage and connectivity table of contents
Pages: 424 - 432  
Year of Publication: 2004
ISBN:1-58113-846-6
Authors
Zoë Abrams  Stanford University
Ashish Goel  Stanford University
Serge Plotkin  Stanford University
Sponsor
SIGBED: ACM Special Interest Group on Embedded Systems
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 8,   Downloads (12 Months): 88,   Citation Count: 21
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ABSTRACT

Wireless sensor networks (WSNs) are emerging as an effective means for environment monitoring. This paper investigates a strategy for energy efficient monitoring in WSNs that partitions the sensors into covers, and then activates the covers iteratively in a round-robin fashion. This approach takes advantage of the overlap created when many sensors monitor a single area. Our work builds upon previous work in [13], where the model is first formulated. We have designed three approximation algorithms for a variation of the SET K-COVER problem, where the objective is to partition the sensors into covers such that the number of covers that include an area, summed over all areas, is maximized. The first algorithm is randomized and partitions the sensors, in expectation, within a fraction 1-1<over>e (~.63) of the optimum. We present two other deterministic approximation algorithms. One is a distributed greedy algorithm with a 1<over>2 approximation ratio and the other is a centralized greedy algorithm with a 1-1<over>e approximation ratio. We show that it is NP-Complete to guarantee better than 15<over>16 of the optimal coverage, indicating that all three algorithms perform well with respect to the best approximation algorithm possible in polynomial time, assuming PNP. Simulations indicate that in practice, the deterministic algorithms perform far above their worst case bounds, consistently covering more than 72% of what is covered by an optimum solution. Simulations also indicate that the increase in longevity is proportional to the amount of overlap amongst the sensors. The algorithms are fast, easy to use, and according to simulations, significantly increase the longevity of sensor networks. The randomized algorithm in particular seems quite practical.


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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CITED BY  21
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Collaborative Colleagues:
Zoë Abrams: colleagues
Ashish Goel: colleagues
Serge Plotkin: colleagues

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