In this paper, we propose a MMPP (Markov modulated Poisson process) traffic model that accurately approximates the LRU (long range dependence) characteristics of Internet traffic traces. Using the notion of sessions and flows, the proposed MMPP model mimics the real hierarchical behavior of the packet generation process by Internet users. Thanks to its hierarchical structure, the proposed model is both simple and intuitive: it allows the generation of traffic with the desired characteristics by easily setting a few input parameters which have a clear physical meaning. Results prove that the queuing behavior of the traffic generated by the MMPP model is coherent with the one produced by the real traces collected at our institution edge route...
In this paper, we show how to utilize the expectation-maximization (EM) algorithm for efficient and ...
[Abstract]: This paper presents the Poisson Pareto burst process (PPBP) as a simple but accurate mo...
In this paper, we show how to utilize the expectation-maximization (EM) algorithm for efficient and ...
Markov Modulated Posson Process (MMPP) is a good model of Internet traffic. We take an IP trace and ...
In this paper, we propose a novel and mathematically rigorous measure of variability, called the ind...
SUMMARY Measuring and modeling network traffic is of key impor-tance for the traffic engineering of ...
Traffic control cannot be done without having a well-fit model to represent the traffic. Therefore t...
In this work, we propose a Hidden Markov Model for Internet traffic sources at packet level, jointly...
In this work, we propose a Hidden Markov Model for Internet traffic sources at packet level, jointly...
In this work, we propose a Hidden Markov Model for Internet traffic sources at packet level, jointly...
In this work, we propose a Hidden Markov Model for Internet traffic sources at packet level, jointly...
We describe the frst steps in the evaluation of an idea to match the high vari- ability found in mea...
Abstract. In recent years several studies have reported peculiar types of traffic behavior, such as ...
In this work, we propose a Hidden Markov Model for Internet traffic sources at packet level, jointly...
Input characterization to describe the flow of incoming traffic in network systems, such as the GRID...
In this paper, we show how to utilize the expectation-maximization (EM) algorithm for efficient and ...
[Abstract]: This paper presents the Poisson Pareto burst process (PPBP) as a simple but accurate mo...
In this paper, we show how to utilize the expectation-maximization (EM) algorithm for efficient and ...
Markov Modulated Posson Process (MMPP) is a good model of Internet traffic. We take an IP trace and ...
In this paper, we propose a novel and mathematically rigorous measure of variability, called the ind...
SUMMARY Measuring and modeling network traffic is of key impor-tance for the traffic engineering of ...
Traffic control cannot be done without having a well-fit model to represent the traffic. Therefore t...
In this work, we propose a Hidden Markov Model for Internet traffic sources at packet level, jointly...
In this work, we propose a Hidden Markov Model for Internet traffic sources at packet level, jointly...
In this work, we propose a Hidden Markov Model for Internet traffic sources at packet level, jointly...
In this work, we propose a Hidden Markov Model for Internet traffic sources at packet level, jointly...
We describe the frst steps in the evaluation of an idea to match the high vari- ability found in mea...
Abstract. In recent years several studies have reported peculiar types of traffic behavior, such as ...
In this work, we propose a Hidden Markov Model for Internet traffic sources at packet level, jointly...
Input characterization to describe the flow of incoming traffic in network systems, such as the GRID...
In this paper, we show how to utilize the expectation-maximization (EM) algorithm for efficient and ...
[Abstract]: This paper presents the Poisson Pareto burst process (PPBP) as a simple but accurate mo...
In this paper, we show how to utilize the expectation-maximization (EM) algorithm for efficient and ...