High-speed network traffic model

In order to manage the whole network, a novel traffic model is proposed based the Active,probe method. The core of model has three parts: First we inject probe packet into the network by Poisson law. Second, we can get the interval of packet pairs by measuring OWD (One Way Delay time). Last we use the Initial Gap Increasing (IGI) algorithm to acquire traffic based M/M/1 queue model. At the same time, we may measure traffic on network edge in order to justify our result by active measurement. Our experiments show the competing traffic error within about 20%. In order to justify the result of active measurement, we introduce the XOR hash algorithm, which may allow 50,000 classification rules at least by computer simulating, The core of algorithm is how to solve collision and how to get random. We use some random generator, at the same time, we also get better random generator. The test results show that the classification rate. of XOR hash algorithm is up to 3 million packets per second and the maximum memory consumed is 6MB for 10,000 rules.