.png){kind=icon}
返回
A High-Performance Sketch With Dynamic Memory Allocation for Priority-Oriented Data Stream Processing
.png){kind=icon}
PRE
AI
DOI：10.1109/TC.2025.3643356.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Sketch is widely used in many traffic estimation tasks due to its good balance among accuracy, speed, and memory usage. In scenarios with priority flows, priority-aware sketch, as an emerging method, provides differentiated detection accuracy for flows of different priorities, optimizing resource allocation and improving the detection accuracy of high-priority flows. However, existing priority-aware sketches methods struggle to effectively handle the dynamic changes in flow priority distribution in real-world detection environments, leading to wasted or insufficient storage space. To address this issue, this paper proposes a new priority-aware sketch with Dynamic Memory Allocation called DMA-Sketch. It dynamically adjusts the detection framework based on flow priority distribution information and adaptively allocates appropriate memory space to each storage region. The experimental results show that DMA-Sketch improves the overall priority accuracy, high-priority accuracy and throughput by up to 1.33$\times$, 16.39$\times$ and 1.88$\times$, respectively, under the scenarios with changing flow priority distribution over the state-of-the-art schemes.
Keyword:
Sketch
network measurements
priority-aware
dynamic
期刊
IF:
3.8
论文数:
5.4K
被引数:
9.8K
机构
引用论文
Diamond Sketch: Accurate Per-flow Measurement for Big Streaming DataDiamond Sketch: 大数据流的精确流量测量
PREAI
分享收藏分享收藏Sliding Sketches: A Framework using Time Zones for Data Stream Processing in Sliding Windows.png)
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data MiningIF0
PREAI
分享收藏WavingSketch: An Unbiased and Generic Sketch for Finding Top-k Items in Data StreamsProceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data MiningIF0
PREAI
分享收藏
查看更多内容