Various approaches have been developed for quantifying and displaying network traffic information for determining network status and in detecting anomalies. Although many of these methods are effective, they rely on the collection of long-term network statistics. Here, we present an approach that uses short-term observations of network features and their respective time averaged entropies. Acute changes are localized in network feature space using adaptive Wiener filtering and auto-regressive moving average modeling. The color-enhanced datagram is designed to allow a network engineer to quickly capture and visually comprehend at a glance the statistical characteristics of a network anomaly. First, average entropy for each feature is calculated for every second of observation. Then, the resultant short-term measurement is subjected to first- and second-order time averaging statistics. These measurements are the basis of a novel approach to anomaly estimation based on the well-known Fisher linear discriminant (FLD). Average port, high port, server ports, and peered ports are some of the network features used for stochastic clustering and filtering. We empirically determine that these network features obey Gaussian-like distributions. The proposed algorithm is tested on real-time network traffic data from Ohio University's main Internet connection. Experimentation has shown that the presented FLD-based scheme is accurate in identifying anomalies in network feature space, in localizing anomalies in network traffic flow, and in helping network engineers to prevent potential hazards. Furthermore, its performance is highly effective in providing a colorized visualization chart to network analysts in the presence of bursty network traffic.

Fast and efficient detection of anomalies is essential for maintaining a robust and secure network. This research presents a method of anomaly detection based on adaptive Wiener filtering of noise followed by ARMA modeling of network flow data. We dynamically calculate noise and traffic signal statistics using network-monitoring metrics for traffic features such as average port, high port, server ports, and peered ports. The underlying approach is tested on near-real-time Internet traffic in the wide-area network (WAN) of Ohio University. The average port feature is determined to be the most informative measure in the estimation process. High port, server ports, and peered ports are used for confirmation of the anomaly detection result. We empirically determine that most of the network features obey Gaussian-like distributions. Experiments reveal that the method is highly effective in predicting anomalies in network traffic flow and preventing any hazard that they may cause.

A significant percentage of the critical nets in high-performance systems are of the pin-to-pin type. To optimally design these nets such that signal integrity is preserved, efficient analytical metrics for transmission line termination are a valuable part of a system-level designer's toolset. Using the symbolic moment-based expressions in this paper, proper termination can be determined via a single-step procedure, without any preprocessing steps and/or time-domain simulations. Driver nonlinearities and effects of nonzero rise-time are also considered in the proposed termination methodology.

The Elmore delay is an extremely popular delay metric, particularly for RC tree analysis.The widespread usage of this metric is mainly attributable to it being the most accurate delay measure that is a simple analytical function of the circuit parameters.The only drawbacks to this delay metric are the uncertainty as to whether it is an optimistic or a pessimistic estimate, and the restriction to step response delay estimation.In this paper, we prove that the Elmore delay is an absolute upper bound on the 50% delay of an RC tree response.Moreover, we prove that this bound holds for input signals other than steps, and that the actual delay asymptotically approaches the Elmore delay as the input signal rise time increases.A lower bound on the delay is also developed using the Elmore delay and the second moment of the impulse response.The utility of this bound is for understanding the accuracy and the limitations of the Elmore delay metric as we use it for design automation.

RLC transmission line synthesis is a difficult problem because minimal net delay cannot be achieved or accurately predicted unless: 1) a termination scheme is chosen and properly implemented, and 2) output driver transition rates are constrained at or below the net's capability.This paper describes a method to concurrently find, for any RLC net, an optimal termination value, a maximum source transition rate, and an approximate net delay using the first few response moments.When optimal termination is accomplished and transition rates do not exceed the capabilities of the net, the resulting delay metrics are an interesting extension of the popular Elmore delay metric for RC interconnects.The task of physical RLC interconnect design is facilitated by the ease with which these first few moments are calculated for generalized RLC lines.

This paper addresses the functional behavior of Cellular Neural Networks (CNN). The impact of variable convergence times on the proper operation of the network is discussed A test method is presented to determine the functionality of the network. The function fault models assume that the cells are unable to switch between limiting states. The proposed method attains 100% stuck-at fault coverage without any extra hardware for its implementation. Moreover, the required number of test vectors is constant and independent of the array size which makes it suitable for practical implementations. The paper discusses the new fault model, presents the algorithmic procedures and shows simulated testing results.>

Properties of a new fine-line printed circuit board which are critical in the design of computer systems based on GaAs, 100 K and 10 K logic families, are characterized. The new PCB technology permits trace widths as fine as 0.002 in. on the inner layers of multilayer boards. While facilitating higher package density and controlled impedance interconnects with higher characteristic impedance (Z/sub 0/), the technology opens questions of thermal reliability, ohmic heating, and noise margin. Cross-validating analytic and laboratory analysis is used to investigate each of these issues. Provided that several key issues are addressed during design, this report supports the use of 0.002 in. technology in high-performance computer systems.>