CAREER: Traffic Differentiation in Multihop Wireless Networks

职业：多跳无线网络中的流量差异化

• 批准号: 0644033
• 负责人: Shigang Chen
• 金额: $ 31.37万
• 依托单位: University of Florida
• 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: 2007-05-01 至 2012-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0644033&HistoricalAwards=false
• 关键词: CAREER; Traffic; Differentiation; Multihop; Wireless

After WLAN's phenomenal commercial success, multihop wireless networks, including wireless sensor networks, wireless mesh networks, and mobile ad-hoc networks, are expected to lead in the next wave of deployment. From a user's perspective, not only do these networks enable ubiquitous communication, but also they should provide means to support diverse application requirements, particularly, the ability to differentiate various types of data flows and ensure quality of service. The objective of this project is to design distributed algorithms and network protocols to solve several fundamental problems in multihop wireless networks, including end-to-end weighted bandwidth allocation, bandwidth assurance, and performance/overhead tradeoff in traffic differentiation. The study covers a variety of network conditions, including single-commodity or multi-commodity flows, single-path or multi-path routing, and static or highly-dynamic wireless networks. The research focuses on two hop-by-hop, routing-independent, light-weight approaches based on aggregate state and packet labels, respectively. Without maintaining any per-flow state, these approaches are able to implement traffic differentiation under aggregate or weighted maxmin models and have great flexibility in adaptation based on network/traffic conditions. The research results are expected to have significant intellectual and practical impact. Wireless sensor networks, mesh networks, and mobile ad-hoc networks will provide a pervasive communication infrastructure for modern societies and dramatically change the way people interact with cyberspace and physical environment. Traffic-differentiation capability allows these networks to meet diverse application requirements, which will promote their entrance into the marketplace. As an educational effort, this project actively involves senior undergrads and minority students.

在 WLAN 取得巨大商业成功之后，多跳无线网络（包括无线传感器网络、无线网状网络和移动自组织网络）预计将引领下一波部署。从用户的角度来看，这些网络不仅能够实现无处不在的通信，而且还应该提供支持多样化应用需求的手段，特别是能够区分各种类型的数据流并保证服务质量。该项目的目标是设计分布式算法和网络协议，以解决多跳无线网络中的几个基本问​​题，包括端到端加权带宽分配、带宽保证以及流量差异化的性能/开销权衡。该研究涵盖了各种网络条件，包括单一商品或多商品流、单路径或多路径路由以及静态或高度动态的无线网络。该研究重点关注两种分别基于聚合状态和数据包标签的逐跳、独立于路由的轻量级方法。在不维护任何每个流状态的情况下，这些方法能够在聚合或加权最大最小模型下实现流量区分，并且在基于网络/流量条件的适应方面具有很大的灵活性。研究结果预计将产生重大的学术和实践影响。无线传感器网络、网状网络和移动自组织网络将为现代社会提供普遍的通信基础设施，并极大地改变人们与网络空间和物理环境交互的方式。流量差异化能力使这些网络能够满足不同的应用需求，这将促进它们进入市场。作为一项教育工作，该项目积极吸引高年级本科生和少数民族学生。