Adaptive Sampling Strategies with Application to Water Resource Management

ECCS-0725441称自适应采样策略及其在水资源管理中的应用无线传感器网络既包括静态设备，也包括驱动设备，为从监测各种环境现象到监视国家安全提供了一种很有前途的解决方案。在许多应用中，这些网络被部署来监控时间和空间上的潜在物理现象，例如估计水中的污染物通量。由于传感器设备无人值守，并且具有受限的能量存储，因此能效变得至关重要，并直接决定系统的寿命。为了同时实现感知保真度和能源效率的目标，有必要制定策略来选择那些对期望的监控保真度做出最有效贡献的传感器设备，并选择其他节点处于非活动和低功率待机状态。拟议研究的目标和知识优势有三个方面：(I)开发分布式方法来选择能够满足预期估计精度的传感器节点和传感器测量位置的子集；(Ii)通过实验测试所开发的方法；以及(Iii)将这些方法应用于水资源管理中的关键应用，例如准确地测量水中的污染物通量。这项研究通过提高无线网络从受能量、通信和时间限制的地理上分散的节点采样和提取信息的能力，对国家的信息技术基础设施产生了影响。这项研究还解决了水资源管理系统中对准确传感复盖的需求。它还有助于在与未来网络系统基本相关的领域培训学生。

ECCS-0725441SayedAdaptive Sampling Strategies with Application to Water Resource ManagementIntellectual Merit. Wireless sensor networks include both static and actuated devices and offer a promising solution for applications ranging from monitoring of diverse environmental phenomena to surveillance for national security. In many applications, these networks are deployed to monitor an underlying physical phenomenon over time and space, such as estimating a contaminant flux in water. Since the sensor devices operate unattended and with constrained energy reservoirs, energy efficiency becomes critical and directly determines the system lifetime. In order to achieve the simultaneous objectives of sensing fidelity and energy efficiency, it is necessary to develop strategies for selecting those sensor devices that contribute most effectively to the desired monitoring fidelity and to select other nodes for an inactive and low power standby state. The goals and intellectual merits of the proposed research are threefold: (i) to develop distributed methodologies to select a subset of sensor nodes and sensor measurement locations that can meet desired estimation accuracies; (ii) to test the developed methods experimentally; and (iii) to apply the methods to a critical application in water resource management such as accurately measuring contaminant flux in water.Broader Impact. The research has implications on the information technology infrastructure of the nation by enhancing the ability of wireless networks to sample and extract information from geographically scattered nodes subject to energy, communication, and time constraints. The research also addresses the demand for accurate sensing coverage in water resource management systems. And it helps train students in an area of fundamental relevance to future networking systems.