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Scalable Network Monitoring in High Speed Networks

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Network monitoring serves as basis for a wide scope of network operations, engineering and management. Precise network monitoring involves inspecting every packet traversing in a network. However, this is infeasible in today’s and future high-speed networks, due to significant overheads of processing, storing, and transferring measured data. Therefore, scalable network monitoring techniques are in urgent need. This book addresses the scalability issue of network monitoring from both traffic and performance perspectives.

On scalable traffic monitoring, we present sampling techniques for total load and flow measurement. In order to develop accurate and efficient measurement schemes, we study various aspects of traffic characteristics and their impacts on packet sampling. We find that static sampling does not adjust itself to dynamic traffic conditions, yielding often erroneous estimations or excessive oversampling. We develop the adaptive random sampling technique for total load estimation, that determines the sampling probability adaptively according to traffic condition.We then enhance the adaptive sampling technique to measure traffic in flow level. Flow measurement is a particularly challenging problem, since flows arrive at random times, stay for random durations, and their rates fluctuate over time. Those characteristics make it hard to decide a sampling interval where sampling probability is adapted, and to define a large flow pragmatically. Through a stratified approach, we estimate large flows accurately, regardless of their arrival times, durations, or the rate variabilities during their life times.

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