NeTS+NOSS: Communication Patterns for Collaborative Reasoning in Sensor Networks

摘要：本项目研究用于组织、组织和部署传感器网络的分布式算法，以便它们能够完成各种高级全局估计任务。特别关注的是可以处理传感器噪声、信号干扰和测量不准确的概率方法。总体目标是封装传感器协作、信息聚合和分布式推理的少量范例，这些范例可以服务于各种应用程序，并减轻每次重新实施此类联网软件的负担。本文探讨了通信模式，这些模式将感知、信息交换和处理操作结合在一起，以轻量级、健壮和可感知不确定性的方式共同执行所需的估计。其最终效果是在数据链路层之上的网络堆栈上增加了另一个层，该层是数据驱动的，执行协作推理，利用感知的信息及其对网络任务的价值。这种任务驱动的通信模式一旦被确定和实施，将促进传感器网络针对新任务的快速部署，并为更多的应用提供种子。该项目的研究将结合设计、仿真、理论分析和在大学大楼内的实验传感器网络试验台的实现来探索和验证这些想法。

Abstract: This project investigates distributed algorithms for organizing, structuring, and deploying sensor networks so that they can accomplish a variety of high-level global estimation tasks. Special attention is given to probabilistic methods that can deal with sensor noise, signal interference, and measurement inaccuracies. The overall goal is to encapsulate a small number of paradigms for sensor collaboration, information aggregation, and distributed reasoning that can serve a wide variety of applications and ease the burden of implementing this type of networked software anew each time. Communication patterns are explored that combine sensing, information exchange, and processing actions that jointly perform the required estimation in a lightweight, robust, and uncertainty-aware manner. The net effect is to augment the network stack above the data link layer with another layer that is data-driven and performs collaborative reasoning, exploiting sensed information and its value to the network task. Such task-driven communication patterns, once they have been identified and implemented, will facilitate the quick deployment of sensor networks for new tasks and seed additional applications. The collaboration and reasoning problems addressed are important as well for other distributed systems, including distributed data-bases and peer-to-peer networks.Research on this project will combine design, simulation, theoretical analysis, and the implementation of an experimental sensor network testbed within a university building for exploring and validating these ideas.