A multimedia traffic modeling framework for simulation-based performance evaluation studies

Golaup, A.; Aghvami, Hamid

doi:10.1016/j.comnet.2005.09.028

Cited by 15 publications

(4 citation statements)

References 23 publications

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“…Golaup et al [25] have proposed a framework for simulating multimedia traffic using a source model, which represented a set of multimedia traffic component; consisting of a block, transaction, and streaming characteristic. Each traffic component was statistically analyzed and combined into a source model.…”

Section: Traffic Modeling and Its Application In Dataset Genera-mentioning

confidence: 99%

Novel Bi-directional Flow-based Traffic Generation Framework for IDS Evaluation and Exploratory Data Analysis

Wilailux

Ngamsuriyaroj

2021

Journal of Information Processing

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Flow-based network traffic information has been recently used to detect malicious intrusion. However, several available public flow-based datasets are unidirectional, and bidirectional flow-based datasets are rarely available. In this paper, a novel framework to generate bidirectional flow-based datasets for IDS evaluation is proposed. The generated dataset has the mixed combination of normal background traffic and attack traffic. The background traffic is based on the key traffic feature of the MAWI network traffic traces, and five popular attack traffics are generated based on their statistical traffic features. The generated dataset is characterized using the PCA approach, and we found out that benign and malicious traffic are distinct. With the proposed framework, a dataset of bi-directional flow-based traffic is generated and it would be used for evaluating an effective intrusion detection engine.

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Section: Traffic Modeling and Its Application In Dataset Genera-mentioning

confidence: 99%

Novel Bi-directional Flow-based Traffic Generation Framework for IDS Evaluation and Exploratory Data Analysis

Wilailux

Ngamsuriyaroj

2021

Journal of Information Processing

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“…A variable of primary importance in computer networks is the inter arrival time between on-traffic or that between off-traffic, see [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. It is well established that the popular models for the burst and idle times of on/off traffic are the Pareto and gamma distributions, respectively.…”

Section: Introductionmentioning

confidence: 99%

On the convolution of Pareto and gamma distributions

Nadarajah

Kotz

2007

Computer Networks

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“…A considerable amount of research on traffic modelling has been carried out to investigate the characteristics of different traffic sources for various communication networks [33], [34], [35], [36]. Here, we refer to their results.…”

Section: A Traffic Modelsmentioning

confidence: 99%

A priority-based processor sharing model for TDM passive optical networks

Wang

Zukerman

Addie

et al. 2010

IEEE J. Select. Areas Commun.

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Abstract-The use of passive optical networks (PONs) enables access rates of multi-Gbit/sec bandwidth and provision of quality of service for high definition multimedia services. In this paper, we consider and analyse a generic multi-priority dynamic bandwidth allocation (DBA) algorithm for TDM PONs serving multimedia traffic in an upstream link. PON traffic is served strictly according to its priority. We consider this DBA algorithm using two approaches: (i) the algorithm assigns a fixed service quantum to each priority service and (ii) different service quanta are assigned to different priority services. The mean message delay is evaluated using a multiqueue processor sharing (MPS) model and an MPS with Heterogeneous Traffic (MPS-HT) model for the two approaches respectively. The MPS model is a classical processor sharing model limited by the critical assumption that there is egalitarian service sharing among all users, which is inefficient for multimedia applications in PONs. We extend the MPS model to a general MPS-HT model that enables the analysis of message delay performance in the case where the service quanta may be different for different services.

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A multimedia traffic modeling framework for simulation-based performance evaluation studies

Cited by 15 publications

References 23 publications

Novel Bi-directional Flow-based Traffic Generation Framework for IDS Evaluation and Exploratory Data Analysis

Novel Bi-directional Flow-based Traffic Generation Framework for IDS Evaluation and Exploratory Data Analysis

On the convolution of Pareto and gamma distributions

A priority-based processor sharing model for TDM passive optical networks

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