CAREER: Capacity-Driven Design of Large-Scale Wireless Sensor Networks

拟议的研究集中在用于数据收集的大规模无线传感器网络的设计方法上，该方法以基本容量限制研究为指导。其动机是一个大型传感器网络可能由数千或数万个密集分布的传感器组成，具有严格的能量和复杂性限制。因此，任何协议或算法的设计都应该具有精确度和可量化的衡量标准，并基于对最终可伸缩性极限的良好理解。这一建议旨在弥合基本极限研究和实际协议设计之间的差距。这项研究的目标是：(1)推导出对大类数据收集传感器网络应用至关重要的容量限制；(2)开发实用的分布式算法，将这些限制作为指导并能够接近这些限制；以及(3)在真实的传感器试验台设置中检查这些算法的实际可实现性能。因此，本文的研究分为三个部分：基本容量限制、分布式算法和试验台实验。拟议研究的一个中心主题是弥合基本极限的理论可达性和实际网络设计的最佳性之间的差距。因此，建议的设计方法是通过新的建模技术进行容量极限研究。它为研究网络的可扩展性和可行性提供了一种新颖而有力的工具。在基本容量限制下，将研究两个容量概念：吞吐量容量，在多对一通信的背景下，定义为当所有节点通过单跳或多跳与单个接收器通信时可实现的最大吞吐量；以及寿命容量，定义为传感器网络在第一个传感器死亡(由于能量耗尽)或直到预定百分比的传感器死亡之前可传输的最大数据量。对这两个容量概念的研究对组织网络内的通信具有直接影响，例如，是否应该使用集群以及集群应该有多大，应该有多少数据收集基站以及它们应该放置在哪里。这项研究将从简单的理想化情景向越来越现实和复杂的情景迈进。在分布式算法下，将容量分析应用于设计能量高效的数据分发、最优分簇和高效的传感器睡眠调度的分布式算法。这些算法将设计为接近或接近网络容量。根据拟议的研究，还将开发一台无线传感器试验台，用于实施和测量目的。这项拟议的研究具有很强的教育意义，涉及与密歇根大学的两个研究中心合作。将寻求与无线集成微系统(WIMS)中心、密歇根大学的NSF ERC和密歇根大学的Wu制造研究中心(Wu MRC)密切合作。将把WIMS目前正在开发的最先进的MEMS传感器和Wu MRC正在为自动化系统开发的智能信息电子代理传感器纳入我们的传感器试验台。与他们的合作将允许PI将设计方法应用于具有逼真物理设备的不同应用环境。

The proposed research centers on a design methodology for large-scale wireless sensor networks used for data gathering that uses fundamental capacity limit studies as guidelines. The motivation is that a large sensor network can potentially consist of thousands or tens of thousands of sensors densely populated, with strict energy and complexity constraints. Therefore the design of any protocol or algorithm should come with precision and a quantifiable measure, and be based on a good understanding of the ultimate scalability limit. This proposal aims at bridging the gap between the fundamental limit studies and practical protocol design. The goal of the proposed research is to (1) derive capacity limits critical to the large class of data gathering sensor network applications; (2) develop practical distributed algorithms that use these limits as guidelines and can approach these limits; and (3) examine the actual achievable performance of these algorithms in a real sensor testbed setting. Consequently, there are three parts to the proposed research: fundamental capacity limits, distributed algorithms, and testbed experiments. A central theme of the proposed research is to bridge the gap between the theoretical achievability of fundamental limits and the optimality of practical network designs. The proposed design methodology is thus driven by capacity limit studies via novel modeling techniques. It provides a novel and powerful tool in the study of network scalability and feasibility. Under fundamental capacity limits, will study two capacity notions: the throughput capacity, defined within the context of many-to-one communication as the maximum achievable throughput when all nodes are communicating with a single receiver via either a single hop or multiple hops; and the lifetime capacity, defined as the maximum amount of data deliverable by a sensor network until the first sensor dies (due to energy depletion) or till a pre-specified percentage of sensors die. The study of these two capacity notions has direct implications on organizing communications within a network, e.g., whether clustering should be used and how big a cluster should be, how many data collecting base stations should there be and where should they be placed. This study will progress from simple idealized scenarios to increasingly more realistic and complex. Under distributed algorithms, will apply the capacity analysis to the design of distributed algorithms of energy efficient data dissemination, optimal clustering and efficient sensor sleep schedules. These algorithms will be designed to approach or approximate network capacities. Under the proposed research will also develop an experimental wireless sensor testbed for implementation and measurement purposes. The proposed research has a strong education aspect and involves collaboration with two research centers at the University of Michigan. Will seek close collaboration with the Wireless Integrated Micro-systems (WIMS) Center, an NSF ERC at the University of Michigan, and University of Michigan's Wu Manufacturing Research Center (WuMRC). Will incorporate state-of-the-art MEMS sensors currently being developed at WIMS and intelligent infotronics agent sensors being developed for automation systems by WuMRC into our sensor testbed. Collaboration with them will allow the PI to apply design methodology to different application contexts with realistic physical devices.