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Power analysis of packet classification on programmable network processors

机译:可编程网络处理器上数据包分类的功耗分析

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摘要

Packet classification algorithms are increasingly being used to provide security and Quality of Service guarantees. These algorithms are usually implemented on power hungry programmable network processors, which are used in devices such as core routers and firewalls. This paper compares the energy used by five best-known algorithms Recursive Flow Classification, HiCuts, HyperCuts, Extended Grid-of-Tries with Path Compression and Tuple Space Search with Pruning. It does this by measuring the energy used to build the search structure during preprocessing for each of the five algorithms and the average energy taken to classify a packet. To do this we implemented all five algorithms in C code and used a microarchitectural power simulation tool called Sim-Panalyzer to estimate the power dissipated by the five algorithms while running on a SA1100 StrongARM RISC processor similar to the type found on many of today's programmable network processors.
机译:数据包分类算法越来越多地用于提供安全性和服务质量保证。这些算法通常在耗电的可编程网络处理器上实现,这些处理器用在诸如核心路由器和防火墙之类的设备中。本文比较了五个最著名的算法(递归流分类),HiCuts,HyperCuts,带路径压缩的扩展网格尝试和带修剪的元组空间搜索所消耗的能量。它通过测量在预处理过程中用于五种算法中每种算法的能量以及用于对数据包进行分类的平均能量来实现。为此,我们用C代码实现了全部五种算法,并使用了一种称为Sim-Panalyzer的微体系结构电源仿真工具,以在SA1100 StrongARM RISC处理器上运行时(与当今许多可编程网络中所使用的类型相似)估算这五种算法所消耗的功率。处理器。

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