Packet delay and loss traces are frequently used by network engineers, as well as network applications, to analyze network performance. The clocks on the end-systems used to measure the delays, however, are not always synchronized, and this lack of synchronization reduces the accuracy of these measurements. Therefore, estimating and removing relative skews and offsets from delay measurements between sender and receiver clocks are critical to the accurate assessment and analysis of network performance. We introduce a linear programming-based algorithm to estimate the clock skew in network delay measurements and compare it with three other algorithms. We show that our algorithm has a time complexity of O(N), leaves the delay after the skew removal positive, and is robust in the sense that the error margin of the skew estimate is independent of the magnitude of the skew. We use traces of real Internet delay measurements to assess the algorithm, and compare its performance to that of three other algorithms. Furthermore, we show through simulation that our algorithm is unbiased, and that the sample variance of the skew estimate is better (smaller) than existing algorithms.

The authors review the results of a two-level control framework for integrated video and image traffic in an ATM multiplexer. The framework gives priority to video traffic, and uses flow control on the image traffic in order to prevent congestion while improving its throughput. It functions on two levels, or time scales. Buffer management and scheduling are done at the level of cell arrivals and departures, or microsecond time scales, while flow control is done at the burst level, or millisecond time scales. The control framework guarantees upper bounds on cell loss rates for both video and image traffic over a defined control interval, with a specified probability.>

The authors introduce a model based on arrival rate histograms for characterizing the behavior of an ATM buffer when it is carrying variable bit rate video traffic. Traffic smoothing on a frame-by-frame basis allows a quasistatic approximation that accurately predicts results such as buffer occupancy distributions and cell loss rates to be made. Convolving individual source histograms allow prediction of the queueing performance of a multiplexed stream. The approximation is investigated in more detail by modeling video as a Markov modulated Poisson process. It is shown that the multiplexer system is nearly completely decomposable (NCD). NCD systems have a well-known approximate solution, which is identical to the histogram approximation. Error bounds for the NCD approximation are also known and are reasonably tight. Results indicate that while the presence of strong correlations is an important characteristic of video traffic, the actual form of that correlation is not.>

The authors develop a model for characterizing the behavior of an asynchronous transfer mode (ATM) buffer when it is carrying variable-bit-rate video traffic. Traffic smoothing on a frame-by-frame basis allows the modeling of video sources as randomly modulated Poisson processes which are characterized by their bit rate histograms. An M/D/1/N approximation is used to accurately predict results such as buffer occupancy distributions and cell loss rates. Given the bit rate histograms of several individual video sources, a histogram for the aggregate arrival process can be found and the system behavior can be predicted. A new call admission control scheme and policing algorithm are developed based on the model. They can be used to prevent congestion in the network and to protect calls that adhere to parameters given at call setup.>