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FLOW BASED DYNAMIC LOAD BALANCING FOR PASSIVE NETWORK MONITORING

机译:无源网络监控的基于流动态负载平衡

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Cluster based packet capturing is a way of overcoming the speed of a slow disk to tap a high-speed network. Most cluster-based architectures, however, do not consider load balancing as an important issue. In order to perform monitoring at full line speed without losing packets, we accept that the balance among back-end servers must be maintained. Conventional methods rely on fixed or random routing where a "source-destination" address pair is used as a unit for load balancing. Instead of using such a coarse grain unit, we use a flow, a "source-destination-port" pair. In addition, we adaptively balance loads of back-end servers using a flow load estimation technique. The proposed methods have been validated by performing a trace-based simulation. Compared to the existing routing approaches, our method balances load of back-end servers. From a simulation, we find that for protocols having a transient load with a small variance in flow length, we may use simple methods of load balancing such as round-robin, but for those having a persistent load with a large variance, we need to use a flow estimation technique.
机译:基于群集的数据包捕获是一种克服慢磁速度挖掘高速网络的方式。但是,基于群集的大多数基于群式,不考虑负载平衡作为一个重要问题。为了在不丢失数据包的情况下以全线速度执行监控,我们可以接受必须维护后端服务器之间的余额。常规方法依赖于固定或随机路由,其中​​“源 - 目的地”地址对用作用于负载平衡的单元。我们使用流量,而不是使用这种粗晶单元,而不是使用这种流量,是“源目的地端口”对。此外,我们使用流量负载估计技术自适应地平衡后端服务器的负载。通过执行基于痕量的仿真,已经验证了所提出的方法。与现有路由方法相比,我们的方法余额负载后端服务器。从模拟中,我们发现,对于具有流量长度的瞬态负载的协议,我们可以使用简单的负载平衡方法,例如循环罗宾,但对于具有大方差的持久负载的方法,我们需要使用流量估计技术。

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