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Bit Allocation in Spatially Correlated Sensor Fields: A Comparative Study of Contribution-Aware and Heuristic
1Department of Computer Engineering, Catholic University of Pusan, Busan 46252, Republic of Korea.
Sensors (Basel, Switzerland)
|July 15, 2026
Summary
Optimizing bit allocation in sensor networks is crucial for data quality. Geometry-aware strategies excel under tight budgets, while Shapley-value-based methods are best for small fields, showing context-dependent performance.
Area of Science:
- Sensor networks
- Information theory
- Data compression
Background:
- Limited communication resources necessitate efficient bit allocation in sensor fields.
- Per-sensor bit depth directly impacts quantization fidelity and data quality.
- Effective bit allocation strategies are vital for maximizing information acquisition.
Purpose of the Study:
- To investigate and compare various regime-dependent bit allocation strategies.
- To analyze performance under different deployment geometries, bit budgets, and metrics.
- To address the integer bit-allocation problem in sensor networks.
Main Methods:
- Compared five strategies: Shapley-value-based, uniform, Voronoi-based, greedy mutual information-driven, and conditional variance-based.
- Developed a two-stage Shapley-value-based framework quantifying sensor contribution via cooperative game theory.
- Approximated Shapley values using Neyman stratified sampling for larger networks.
Main Results:
- Reconstruction performance is context-dependent, influenced by allocation strategy and network conditions.
- Geometry-aware allocation performs best under tight budgets, especially for boundary/tail errors.
- Shapley-value-based allocation excels in small-scale fields and is competitive under high budgets.
Conclusions:
- Bit allocation strategies exhibit trade-offs based on network regimes and performance objectives.
- Mutual information and weighted posterior trace offer complementary insights into data-driven trade-offs.
- The choice of bit allocation strategy significantly impacts sensor network performance and data fidelity.
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