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基于LEAST的高速网络大流检测算法
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TP393

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陕西省自然科学基金资助项目(2012JZ8005)


An Elephant Flow Identifying and Measuring Algorithm Based on LEAST in High-speed Network Environment
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    摘要:

    针对大流漏检率过高,占用SRAM过大问题,提出了基于最少(LEAST)改进型大流检测算法。主要思想:利用LEAST淘汰机制将小流丢弃使得大流能够被保护,采用窗口-储备策略解决检测大流的公平性问题。通过相关组织所提供的实际互联网数据进行了实验比较,结果显示:与现有算法相比,新算法具有更高的测量准确性,平均大流漏检率降低至0%~0.13%。

    Abstract:

    In high-speed network environment, it's very important to extract elephant flow timely and accurately for cognizing behavior and law of network. In order to reduce the elephant flow measurement missing rate and overmuch occupation of SRAM, an improved algorithm based on LEAST is proposed. By using LEAST elimination mechanism for discarding the mice flow, the elephant flow can be protected. And Window-Reserve strategy is adopted to ensure the fairness of identifying and measuring elephant flow. Finally, through the comparison between the simulation results and the actual flow data, the result shows that the new algorithm has a higher measurement accuracy and is more practicable, and the elephant flow on the average measurement missing rate is reduced to 0%~0.13%.

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徐敏,夏靖波,申健,陈珍.基于LEAST的高速网络大流检测算法[J].空军工程大学学报,2015,(4):62-65

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  • 在线发布日期: 2015-11-24
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