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Title: Network Burst Monitoring and Detection Based on Fractal Dimension with Adaptive Time-Slot Monitoring Mechanism
Authors: Hsiao-Wen Tin;Shao-Wei Leu;Shun-Hsyung Chang;Gene-Eu Jan
Contributors: 國立臺灣海洋大學:電機工程學系
Date: 2013
Issue Date: 2016-08-10T02:25:38Z
Publisher: Journal of Marine Science and Technology
Abstract: Abstract: This study proposed an approach to measure the burstiness of network traffic based on fractal dimensions (FDs). By definition, burstiness is the degree of variation in network traffic. This study defined two types of FDs: (1) the FD of network traffic that describes the flow variation of network traffic, and (2) the FD of the range that describes the degree of flow dispersal. The proposed method uses an adaptive time-slot monitoring mechanism to monitor the network. The relevant FDs are derived from measurements obtained during each time slot in a monitoring window.This study conducted experiments using NS2 simulation data. The experimental results indicate that the proposed method can effectively measure the burstiness of network traffic. The method provides a meaningful way to describe the variation of network traffic and reduces monitoring overhead by using an adaptive time-slot monitoring mechanism.
Appears in Collections:[Department of Electrical Engineering] Periodical Articles

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