Cross layer design of distributed sensing-estimation with quality feedback— part i optimal schemes
This document summarizes a two-part paper that presents a feedback-based cross-layer framework for distributed sensing and estimation of a dynamic process by a wireless sensor network. The framework considers cross-layer factors such as packet collisions and sensing-transmission costs. Each sensor node adapts its sensing-transmission action based on local observation quality and estimation quality feedback from the fusion center under cost constraints. The first part reduces optimization complexity by exploiting statistical symmetry and large network approximations. Structural properties of optimal coordinated and decentralized schemes are derived, proving that only the best sensing nodes need to activate despite fluctuations. The optimal policy dictates that the best nodes activate when estimation quality is poor, otherwise all nodes remain idle to preserve energy.
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Cross layer design of distributed sensing-estimation with quality feedback— part i optimal schemes
- 1. Cross-Layer Design of Distributed Sensing-Estimation With Quality Feedback— Part I: Optimal Schemes Abstract: This two-part paper presents a feedback-based cross-layer framework for distributed sensing and estimation of a dynamic process by a wireless sensor network (WSN). Sensor nodes wirelessly communicate measurements to the fusion center (FC). Cross-layer factors such as packet collisions and the sensing-transmission costs are considered. Each SN adapts its sensing-transmission action based on its own local observation quality and the estimation quality feedback from the FC under cost constraints for each SN. In this first part, the optimization complexity is reduced by exploiting the statistical symmetry and large network approximation of the WSN. Structural properties of the optimal policy are derived for a coordinated and a decentralized scheme. It is proved that a dense WSN provides sensing diversity, so that only a few SNs with the best local observation quality need to be activated, despite the fluctuations of the WSN. The optimal policy dictates that, when the estimation quality is poor, only the best SNs activate, otherwise all SNs remain idle to preserve energy. The costs of coordination and feedback are evaluated, revealing the scalability of the decentralized scheme to large WSNs, at the cost of performance degradation. Simulation results
- 2. demonstrate cost savings from 30% to 70% over a non-adaptive scheme, and significant gains over a previously proposed estimator which does not consider these cross-layer factors.