AF : Small : The Theory and Practice of Hash-Based Algorithms and Data Structures

基于散列的数据结构和算法目前是互联网中蓬勃发展的行业，特别是与测量、监控和安全相关的应用。 哈希表和相关结构（如Bloom过滤器）每天被使用数十亿次，新的用途不断增加。 然而，在这些结构的理论设计和分析与实际使用和执行之间仍存在巨大差距。 本研究旨在弥合利用哈希算法和数据结构的理论与实践之间的差距，重点是网络应用。 这项研究的成果将包括将理论结果转化为现实世界环境的工具和框架，更好地分析和实现现有的算法和数据结构，以及开发和分析新的算法和数据结构。 相关的教育工作将集中在使本科生、研究生和专业网络社区更了解基于哈希方法的潜力和力量的方法上，从而扩大该领域理论工作的范围和影响力。

Hash-based data structures and algorithms are currently a booming industry in the Internet, particularly for applications related to measurement, monitoring, and security. Hash tables and related structures such as Bloom filters are used billions of times a day, and new uses keep proliferating. There remain, however, large gaps between the theoretical design and analysis of these structures and their use and implementation in practice. This research aims to bridge the gap between the theory and practice of algorithms and data structures that utilize hashing, with an emphasis on networking applications. The outcomes of this research will include tools and frameworks for translating theoretical results into real-world settings, better analyses and implementations of existing algorithms and data structures, and the development and analysis of new algorithms and data structures. Related educational efforts will focus on methods to make undergraduate students, graduate students, and the professional networking community more aware of the potential and power of hash-based approaches, thereby expanding the reach and influence of theoretical work in the area.