NeTS: Small: Adaptive Network Coding for Wireless Relay Networks

NeTS：小型：无线中继网络的自适应网络编码

• 批准号: 1117831
• 负责人: Jian Ren
• 金额: $ 41.66万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1117831&HistoricalAwards=false
• 关键词: NeTS; Small; Adaptive; Network; Coding

Network coding has demonstrated to be very effective in increasing wireless network capacity and reliability. However, the benefits of network coding are only applicable in networks consisting of reliable and trustworthy nodes. Non-negligible network coding (NC) noise and network pollution can cause substantial performance decrease. There is a cogent need for adaptive network coding schemes that can optimize network level throughput by exploiting NC noise and NC pollution. This research develops efficient adaptive model that can provide optimal network level throughput by designing of adaptive network coding schemes, pollution detection model, and joint treatment of coding and dynamic routing. The overall objective is threefold. First, it develops adaptive characteristic model and efficient estimation on the NC noise and NC pollution. Based on this, novel on-the-fly adaptive network coding schemes are developed. Second, this research develops theoretical characterization and effective pollution detection and immunization schemes in relay networks through source privacy protection. Third, this research establishes the mathematical structure for the wireless relay node, and designs cost function for optimal throughput computation. Based on this, provably optimal algorithms with polynomial time complexity are developed under the given pollution constraint and security requirement. In addition, this project also includes a significant education component aimed at integrating frontier research with undergraduate and graduate curricula.

网络编码已被证明在增加无线网络容量和可靠性方面非常有效。然而，网络编码的好处仅适用于由可靠和可信节点组成的网络。不可忽视的网络编码（NC）噪声和网络污染会导致性能大幅下降。存在对自适应网络编码方案的迫切需要，所述自适应网络编码方案可以通过利用NC噪声和NC污染来优化网络级吞吐量。本研究开发了有效的自适应模型，可以提供最佳的网络级吞吐量的自适应网络编码方案的设计，污染检测模型，编码和动态路由的联合处理。总体目标有三个方面。首先，提出了数控噪声和数控污染的自适应特征模型和有效估计方法。在此基础上，开发了新的动态自适应网络编码方案。其次，本研究发展理论表征和有效的污染检测和免疫方案在中继网络通过源隐私保护。第三，建立了无线中继节点的数学结构，并设计了计算最优吞吐量的代价函数。在此基础上，在给定的污染约束和安全要求下，得到了多项式时间复杂度的可证明最优算法。此外，该项目还包括一个重要的教育部分，旨在将前沿研究与本科和研究生课程相结合。