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A method for coordinating the distributed transmission of imagery
Joseph C Dagher1, Michael W Marcellin, Mark A Neifeld
1Department of Electrical and Computer Engineering and the Optical Sciences Center, The University of Arizona, Tucson 85721, USA. joseph@ece.arizona.edu
Summary
This study introduces an efficient algorithm for distributed sensor networks to reduce data load and extend network lifetime by exploiting sensor data correlation. Significant gains in network longevity were achieved, especially with lossy compression.
Area of Science:
- Computer Science
- Electrical Engineering
- Signal Processing
Background:
- Distributed imaging sensor networks face challenges with large data loads.
- Data transmission constraints (power, bandwidth) limit sensor network lifetime.
- Efficient data handling is crucial for the viability of these networks.
Purpose of the Study:
- To develop an algorithm for power-constrained distributed transmission of sensor network imagery.
- To exploit inter- and intrasensor correlation for efficient data compression.
- To enhance sensor network lifetime under transmission limitations.
Main Methods:
- An algorithm was developed to exploit inter- and intrasensor data correlation.
- The algorithm was tested with both lossless and lossy compression techniques.
- Network lifetime gains were quantified under different compression scenarios.
Main Results:
- Lossless compression using the algorithm achieved up to 114% increase in network lifetime.
- Lossy compression yielded significantly larger gains, with a 2.8x increase in network lifetime at a normalized root-mean-squared error of 0.78% compared to lossless compression.
- The algorithm effectively reduces data load, thereby extending network operational duration.
Conclusions:
- The proposed algorithm offers substantial improvements in sensor network lifetime for distributed imaging.
- Exploiting data correlation is a key strategy for overcoming transmission bottlenecks.
- Lossy compression provides a viable trade-off for maximizing network lifetime in power-constrained applications.