Network measurement probes the underlying network to support upper-level decisions such as network management, network update, network maintenance, network defense and beyond. Due to the massive, speedy, unpredictable features of network flows, sketches are widely implemented in measurement nodes to approximately record the frequency or estimate the cardinality of flows. At their cores, sketches usually maintain one or multiple counter array(s), and rely on hash functions to select the counter(s) for each flow. Then the space-efficient sketches from the distributed measurement nodes are aggregated to provide statistics of the undergoing flows. Currently, tremendous redesigns and optimizations have been proposed to improve the sketches for better network measurement performance. However, existing reviews or surveys mainly focus on one particular aspect of measurement tasks. Researchers and engineers in the network measurement community desire an all-in-one survey that covers the entire processing pipeline of sketch-based network measurement. To this end, we present the first comprehensive survey of this area. We first introduce the preparation of flows for measurement, then detail the most recent investigations of design, aggregation, decoding, application and implementation of sketches for network measurement. To summarize the existing efforts, we carry out an in-depth study of the existing literature, covering more than 90 sketch designs and optimization strategies. Furthermore, we conduct a comprehensive analysis and qualitative/quantitative comparison of the sketch designs. Finally,we highlight the open issues for future sketch-based network measurement research.
翻译:网络测量探索基本网络,以支持诸如网络管理、网络更新、网络维护、网络防御等高层决策。由于网络流动的庞大、迅速和不可预测的特征,在测量节点中广泛执行草图,以大致记录流动的频率或估计其基本程度。在核心方面,草图通常保留一个或多个反面阵列,并依靠散列功能为每次流动选择计数器。然后,对分布式测量节点的空间高效草图进行汇总,以提供流动数据。目前,提出了巨大的重新设计和优化,以改进网络测量绩效的草图。然而,现有的审查或调查主要侧重于计量任务的一个特定方面。网络测量社区的研究人员和工程师希望进行一次全方位调查,涵盖整个草图网络测量处理管道的全过程。我们为此提出这方面的第一次全面调查。我们首先介绍测量流动的准备情况,然后详细介绍对网络测量的最新设计、汇总、解码、应用和实施的草图调查。我们目前进行的一项全面研究,然后比较目前进行的深度研究,我们进行一项质量分析。