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Performance aware tasking for environmentally powered sensor networks
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Source Joint International Conference on Measurement and Modeling of Computer Systems archive
Proceedings of the joint international conference on Measurement and modeling of computer systems table of contents
New York, NY, USA
SESSION: P2P and sensor networks table of contents
Pages: 223 - 234  
Year of Publication: 2004
ISBN:1-58113-873-3
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Authors
Aman Kansal  University of California, Los Angeles, CA
Dunny Potter  University of California, Los Angeles, CA
Mani B. Srivastava  University of California, Los Angeles, CA
Sponsors
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 34,   Downloads (12 Months): 169,   Citation Count: 16
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ABSTRACT

The use of environmental energy is now emerging as a feasible energy source for embedded and wireless computing systems such as sensor networks where manual recharging or replacement of batteries is not practical. However, energy supply from environmental sources is highly variable with time. Further, for a distributed system, the energy available at its various locations will be different. These variations strongly influence the way in which environmental energy is used. We present a harvesting theory for determining performance in such systems. First we present a model for characterizing environmental sources. Second, we state and prove two harvesting theorems that help determine the sustainable performance level from a particular source. This theory leads to practical techniques for scheduling processes in energy harvesting systems. Third, we present our implementation of a real embedded system that runs on solar energy and uses our harvesting techniques. The system adjusts its performance level in response to available resources. Fourth, we propose a localized algorithm for increasing the performance of a distributed system by adapting the process scheduling to the spatio-temporal characteristics of the environmental energy in the distributed system. While our theoretical intuition is based on certain abstractions, all the scheduling methods we present are motivated solely from the experimental behavior and resource constraints of practical sensor networking systems.


REFERENCES

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CITED BY  16
 
 
 
 
 
 
 
 

Collaborative Colleagues:
Aman Kansal: colleagues
Dunny Potter: colleagues
Mani B. Srivastava: colleagues

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