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A High-Performance Sketch With Dynamic Memory Allocation for Priority-Oriented Data Stream Processing
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AI
DOI：10.1109/TC.2025.3643356.png)
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Abstract
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<inline-formula><tex-math notation="LaTeX">$\times$</tex-math></inline-formula>, 16.39<inline-formula><tex-math notation="LaTeX">$\times$</tex-math></inline-formula> and 1.88<inline-formula><tex-math notation="LaTeX">$\times$</tex-math></inline-formula>, respectively, under the scenarios with changing flow priority distribution over the state-of-the-art schemes.
Keywords:
Sketch
network measurements
priority-aware
dynamic
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