In this paper, we investigate the traffic behaviour of a local ATM network. The major loading application in this network is network file system (NFS). The cell data are collected between switches. The results show that the traces present two different kinds of properties: long-range dependence (LRD) or short-range dependence (SRD). Then we propose a new method for in-service QoS violations and spare capacity estimations. For a typical ATM network, a large number of cells must be observed before we can get a statistically meaningful cell loss probability (CLP) result but these results may be too obsolete for effective network management. On the contrary, it is difficult to choose a suitable representative analytical model for many applications in ATM networks that exhibit varied statistical properties. Besides, finding analytical models may be complex and slow to fit. For both SRD and LRD processes, there exists a relationship between the logarithm of the CLP and the buffer size. The relationship for SRD processes is often linear while it is polynomial for LRD processes. If we can know the traffic presents LRD or SRD, the above relationships help us estimate the CLP of the queuing behaviour. The proposed method in this paper uses a simple regression test to select the suitable model: LRD or SRD. Then it employs the relationships between log(CLP) and buffer size of the selected model. With observations of cell loss for several small-buffer pseudo-queues and the selected regression model, the scheme can estimate the QoS and the spare capacity of the actual system. It requires only a short observation period and it does not need analytical models describing the statistics of traffic. The collected data are used for the basis of the simulation sources and the results of the simulations show the effectiveness of the method for both LRD and SRD trace data.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications