Performance Evaluation Of Computer Networks Research Articles

What probability distribution describes search?

Typically, search research papers assume that target acquisition is described by an exponential distribution. We investigate when this assumption is valid. It is obvious that two people are more effective than one person at finding a target, but how can that be quantified? The network imaging sensor (NIS) and time-dependent search parameter (TDSP) models quantify how much more effective multiple observers are at finding a target than a single individual for a wide variety of scenarios. We reference and summarize evidence supporting the NIS and TDSP models and demonstrate how NIS model results can be expressed in terms of a reduced hyperexponential distribution for scenarios where observer and target are stationary. Target acquisition probabilities are determined by analysis and confirmed by computer simulations and perception experiments. Search by multiple stationary observers looking for a stationary target is described by the hyperexponential distribution. Stationary scenarios with multiple observers are more accurately modeled by hyperexponential rather than exponential distributions. Hyperexponential distributions are an example of phase-type distributions used in queuing and in the performance evaluation of computer networks and systems. The observation that search, queuing, and computer networks share phase-type distributions facilitates cross fertilization between these fields.

Performance evaluation of a novel redundancy method for videoconferencing traffic in MPLS networks

Performance evaluation of computer networks using mathematical modelling is widely used in assessing the advantages and drawbacks of any new mechanism before its deployment. In this contribution, we introduce a new mechanism that aims at rerouting multi-point to multi-point (MP2MP) traffic such as videoconferencing in multi-protocol label switching-traffic engineering (MPLS-TE) networks. Then we develop a stochastic model in order to evaluate the amelioration incurred by our proposal compared to the existing approaches. In particular, we assess two criterions: the scalability and bandwidth efficiency. Our results show that our proposed method leads to better scalability while reducing the ratio of bandwidth wastage such as traffic duplication observed in the existing mechanisms. Our proposed rerouting mechanism contains two parts. First, we define the concept of MP2MP TE tunnel in MPLS as opposed to the existing MP2MP connectionless tunnel (i.e., without support of TE features such as bandwidth reservation and fast reroute in case of link and/or node failure). Second, we explain how to build a MP2MP TE bypass tunnel that is how to encapsulate a primary MP2MP TE tunnel into a backup MP2MP TE tunnel in order to provide the fast redundancy feature.

Efficiency evaluation of the computer networks in e-learning system

The possibilities of evaluation of the most significant performance of computer networks online by the standard tools of the operating system and office applications are analyzed in the article. Influence of network characteristics on the quality of the information transmitted by the network is shown. Implementation of the proposed methods are done for performance evaluation of computer networks, which can be used in the educational process as in traditional learning and in e-learning system

Extending Stochastic Network Calculus to Loss Analysis

Loss is an important parameter of Quality of Service (QoS). Though stochastic network calculus is a very useful tool for performance evaluation of computer networks, existing studies on stochastic service guarantees mainly focused on the delay and backlog. Some efforts have been made to analyse loss by deterministic network calculus, but there are few results to extend stochastic network calculus for loss analysis. In this paper, we introduce a new parameter named loss factor into stochastic network calculus and then derive the loss bound through the existing arrival curve and service curve via this parameter. We then prove that our result is suitable for the networks with multiple input flows. Simulations show the impact of buffer size, arrival traffic, and service on the loss factor.

An algorithm approach to bounding aggregations of multidimensional Markov chains

We analyze transient and stationary behaviors of multidimensional Markov chains defined on large state spaces. In this paper, we apply stochastic comparisons on partially ordered state which could be very interesting for performance evaluation of computer networks. We propose an algorithm for bounding aggregations in order to derive upper and lower performance measure bounds on a reduced state space. We study different queueing networks with rejection in order to compute blocking probability and end to end mean delay bounds. Parametric aggregation schemes are studied in order to propose an attractive solution: given a performance measure threshold, we vary the parameter values to obtain a trade-off between the accuracy of bounds and the computation complexity.

Performance analysis of email systems under three types of attacks

Email is a crucial part of our daily life, but email systems are facing increasing security threats such as attacks and spam. Because of this, new mechanisms are being provided to defend against the attacks and to reduce the amount of spam in email systems. Up to now, few available works have been reported on the performance evaluation of email systems under attack, which has become necessary for enhancing email security. In this paper, we propose a novel method to study the impact of three types of attacks on email systems. We construct a multiple queueing model to characterize three types of attacks integrally, and study the performance metrics of system security such as system availability, average queue length and information leakage probability. Numerical examples indicate that the approach of this paper is effective and efficient for dealing with the security analysis of email systems under attack. We believe that this work will open a new avenue for the performance evaluation of computer networks under email attack and other forms of attacks.

On the efficiency of fluid simulation of networks

Performance evaluation of computer networks through traditional packet-level simulation is becoming increasingly difficult as networks grow in size along different dimensions. Due to its higher level of abstraction, fluid simulation is a promising approach for evaluating large-scale network models. In this paper we focus on evaluating and comparing the computational effort required for fluid- and packet-level simulation. To measure the computational effort required by a simulation approach, we introduce the concept of “simulation event rate”, a measure that is both analytically tractable and adequate. We identify the fundamental factors that contribute to the simulation event rate in fluid- and packet-level simulations and provide an analytical characterization of the simulation event rate for specific network models. Among such factors, we identify the “ripple effect” as a significant contributor to the computational effort required by fluid simulation. We also show that the parameter space of a given network model can be divided into different regions where one simulation technique is more efficient than the other. In particular, we consider a realistic large-scale network and demonstrate how the computational effort depends on simulation parameters. Finally, we show that flow aggregation can effectively reduce the impact of the ripple effect and that the ripple effect has less impact when simulating the WFQ scheduling policy.