WN: Collaboration of Networked Nodes through Belief Propagation: Where Computing Meets Communications

WN：通过信念传播进行网络节点的协作：计算与通信的结合

• 批准号: 0721815
• 负责人: Huaiyu Dai
• 金额: $ 19.6万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0721815&HistoricalAwards=false
• 关键词: WN; Collaboration; Networked; Nodes; through

Wireless ad hoc/sensor networks are playing an increasingly important role in our lives, for which collaboration among distributed nodes is crucial for their success. While most existing approaches for node collaboration are restricted to local and link behavior, this research takes a new, network-wide view: a general methodology, belief propagation (BP), is employed to provide a systematic, accurate, and yet flexible framework for collaborative information processing and dissemination in wireless networks. Belief propagation is a computing algorithm operating on graphical models, while in wireless networks there is a communication graph reflecting connectivity topology. This research investigates the synergy of the two: where the computing graph meets the communication graph. First, it provides design guidelines and analytical tools to facilitate application of BP in wireless networks, leading to distributed, robust, scalable, and energy-efficient communication and network protocols. Meanwhile, the impact of real communication constraints on the design and analysis is explicitly studied. Extension to generalized BP and hybrid architectures is also addressed. Throughout this research, application-specific and data-centric approaches, and cross-layer approaches, are actively explored to facilitate design and analysis and improve performance. This research lies in the interface of networking, communications, and computing, and relies heavily on tools from information theory, communication theory, Bayesian inference, graphical theory and models, and communication/computation/information complexity. Its outcome may advance the theory and practice of these areas, and contribute to the evolution of next-generation wireless networks. The multi-disciplinary nature of this research also lends itself to cross-disciplinary education and well-rounded training of students.

无线自组织/传感器网络在我们的生活中扮演着越来越重要的角色，其中分布式节点之间的协作是其成功的关键。 虽然大多数现有的节点协作方法仅限于本地和链路行为，本研究采取了一种新的，网络范围内的观点：一般的方法，信念传播（BP），是用来提供一个系统的，准确的，但灵活的框架，在无线网络中的协作信息处理和传播。置信传播是一种基于图模型的计算算法，而在无线网络中，存在反映连通性拓扑的通信图。本研究探讨了两者的协同作用：计算图与通信图相遇的地方。首先，它提供了设计指南和分析工具，以促进BP在无线网络中的应用，从而实现分布式，鲁棒性，可扩展性和节能的通信和网络协议。同时，明确研究了真实的通信约束对设计和分析的影响。广义BP和混合架构的扩展也得到了解决。在整个研究过程中，积极探索特定于应用程序和以数据为中心的方法以及跨层方法，以促进设计和分析并提高性能。 这项研究在于网络，通信和计算的接口，并在很大程度上依赖于信息理论，通信理论，贝叶斯推理，图形理论和模型，以及通信/计算/信息复杂性的工具。其成果将推动这些领域的理论和实践，并有助于下一代无线网络的发展。这项研究的多学科性质也有助于跨学科教育和全面培养学生。