A comparison of ATM and IP QoS network capabilities for handling LAN traffic with QoS differentiation, Journal of Telecommunications and Information Technology, 2003, nr 4

Now, a network operator must choose between two packet switched technologies for providing QoS in WAN networks, which are ATM and IP QoS [3, 4, 9]. As ATM has reached the maturity with capabilities for offering a number of different network services (i.e. CBR, VBR, ABR, UBR, GFR), the IP QoS with network services like expedited forwarding, assured forwarding, etc. is still at developing phase but nevertheless is commonly regarded as capable to guarantee in near future similar QoS level as ATM. This paper tries to compare the efficiency of the mentioned technologies (in case of IP QoS network the AQUILA network concept [1, 2] is investigated) for handling traffic generated by LANs with QoS differentiation. This is extremely required since the applications running in LAN differ in QoS requirements and emitted traffic profiles (streaming, elastic). Therefore, a classification process of outgoing LAN traffic into predefined sub-streams should be performed at the entry point to WAN network (edge ATM switch or IP router). Furthermore, particular sub-streams are submitted to adequate WAN network service, available in ATM or IP QoS. The paper presents the experimental results, measured in the test bed, corresponding to QoS level and QoS differentiation provided by ATM and IP QoS core. For this purpose, a set of representative applications currently available to a LAN user was selected demanding from the core different QoS level. They correspond to streaming applications like VoIP with QoS objectives represented mainly by packet delay characteristics and elastic applications controlled by TCP protocol with minimum guaranteed throughput/ goodput as target

Journal of Telecommunications and Information Technology, 2003, nr 4

kwartalni

Modelling of self-similar teletraffic for simulation

Recent studies of real teletraffic data in modern computer networks have shown that teletraffic exhibits self-similar (or fractal) properties over a wide range of time scales. The properties of self-similar teletraffic are very different from the traditional models of teletraffic based on Poisson, Markov-modulated Poisson, and related processes. The use of traditional models in networks characterised by self-similar processes can lead to incorrect conclusions about the performance of analysed networks. These include serious over-estimations of the performance of computer networks, insufficient allocation of communication and data processing resources, and difficulties ensuring the quality of service expected by network users. Thus, full understanding of the self-similar nature in teletraffic is an important issue. Due to the growing complexity of modern telecommunication networks, simulation has become the only feasible paradigm for their performance evaluation. In this thesis, we make some contributions to discrete-event simulation of networks with strongly-dependent, self-similar teletraffic. First, we have evaluated the most commonly used methods for estimating the self-similarity parameter H using appropriately long sequences of data. After assessing properties of available H estimators, we identified the most efficient estimators for practical studies of self-similarity. Next, the generation of arbitrarily long sequences of pseudo-random numbers possessing specific stochastic properties was considered. Various generators of pseudo-random self-similar sequences have been proposed. They differ in computational complexity and accuracy of the self-similar sequences they generate. In this thesis, we propose two new generators of self-similar teletraffic: (i) a generator based on Fractional Gaussian Noise and Daubechies Wavelets (FGN-DW), that is one of the fastest and the most accurate generators so far proposed; and (ii) a generator based on the Successive Random Addition (SRA) algorithm. Our comparative study of sequential and fixed-length self-similar pseudo-random teletraffic generators showed that the FFT, FGN-DW and SRP-FGN generators are the most efficient, both in the sense of accuracy and speed. To conduct simulation studies of telecommunication networks, self-similar processes often need to be transformed into suitable self-similar processes with arbitrary marginal distributions. Thus, the next problem addressed was how well the self-similarity and autocorrelation function of an original self-similar process are preserved when the self-similar sequences are converted into suitable self-similar processes with arbitrary marginal distributions. We also show how pseudo-random self-similar sequences can be applied to produce a model of teletraffic associated with the transmission of VBR JPEG /MPEG video. A combined gamma/Pareto model based on the application of the FGN-DW generator was used to synthesise VBR JPEG /MPEG video traffic. Finally, effects of self-similarity on the behaviour of queueing systems have been investigated. Using M/M/1/∞ as a reference queueing system with no long-range dependence, we have investigated how self-similarity and long-range dependence in arrival processes affect the length of sequential simulations being executed for obtaining steady-state results with the required level of statistical error. Our results show that the finite buffer overflow probability of a queueing system with self-similar input is much greater than the equivalent queueing system with Poisson or a short-range dependent input process, and that the overflow probability increases as the self-similarity parameter approaches one