Network data compression: fundamental limits and practical schemes

网络数据压缩：基本限制和实用方案

• 批准号: 355601-2008
• 负责人: Chen, Jun
• 金额: $ 1.7万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2011
• 资助国家: 加拿大
• 起止时间: 2011-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=482774
• 关键词: Network; data; compression; fundamental; limits

Network data compression, also known as Slepian-Wolf coding, is a far-reaching generalization of Shannon's point-to-point lossless source coding to the distributed network scenario. However, the impact of the fundamental theory of Slepian-Wolf coding on practical network data compression techniques is still very limited. Most existing network data compression schemes are direct combinations of conventional point-to-point data compression methods, and cannot fully exploit the potential as promised by the theory of Slepian-Wolf coding.

网络数据压缩，也被称为Slepian-Wolf编码，是Shannon的点对点无损信源编码到分布式网络场景的深远概括。然而，Slepian-Wolf编码的基本理论对实际网络数据压缩技术的影响仍然非常有限。现有的大多数网络数据压缩方案是传统点到点数据压缩方法的直接组合，不能充分发挥Slepian-Wolf编码理论所承诺的潜力。