Heavy Hitters over Interval Queries

arXiv: Data Structures and Algorithms(2018)

引用 23|浏览18
暂无评分
摘要
Heavy hitters and frequency measurements are fundamental in many networking applications such as load balancing, QoS, and network security. This paper considers a generalized sliding window model that supports frequency and heavy hitters queries over an interval given at query time. This enables drill-down queries, in which the behavior of the network can be examined in finer and finer granularities. For this model, we asymptotically improve the space bounds of existing work, reduce the update and query time to a constant, and provide deterministic solutions. When evaluated over real Internet packet traces, our fastest algorithm processes packets 90–250 times faster, serves queries at least 730 times quicker and consumes at least 40% less space than the known method.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要