The Experts below are selected from a list of 72813 Experts worldwide ranked by ideXlab platform

Yi Shi - One of the best experts on this subject based on the ideXlab platform.

  • A novel Network Traffic Analysis method based on fuzzy association rules
    Lecture Notes in Computer Science, 2004
    Co-Authors: Xinyu Yang, Wenjing Yang, Ming Zeng, Yi Shi
    Abstract:

    For Network Traffic Analysis and forecasting, a novel method based on fuzzy association rules is proposed in this paper. Connecting fuzzy logic theory with association rules, the method sets up the fuzzy association rules and could analyze the Traffic of the global Network by using data mining algorithm. Therefore, this method can represent the Traffic's characters much more precisely and forecast the behaviors of Traffic in advance. The paper firstly introduces the new classification method on Network Traffic. Then the fuzzy association rules are applied to analyze the behaviors of Traffic in existence. Finally, the results of simulation experiments indicating that the fuzzy association rule is very effective in discovering the relativity of different Traffic in the Analysis of Traffic flow are shown.

  • MDAI - A Novel Network Traffic Analysis Method Based on Fuzzy Association Rules
    Modeling Decisions for Artificial Intelligence, 2004
    Co-Authors: Xinyu Yang, Wenjing Yang, Ming Zeng, Yi Shi
    Abstract:

    For Network Traffic Analysis and forecasting, a novel method based on fuzzy association rules is proposed in this paper. Connecting fuzzy logic theory with association rules, the method sets up the fuzzy association rules and could analyze the Traffic of the global Network by using data mining algorithm. Therefore, this method can represent the Traffic’s characters much more precisely and forecast the behaviors of Traffic in advance. The paper firstly introduces the new classification method on Network Traffic. Then the fuzzy association rules are applied to analyze the behaviors of Traffic in existence. Finally, the results of simulation experiments indicating that the fuzzy association rule is very effective in discovering the relativity of different Traffic in the Analysis of Traffic flow are shown.

Chen Shuhui - One of the best experts on this subject based on the ideXlab platform.

  • Design and implementation of Network Traffic Analysis system
    Journal of Computer Applications, 2011
    Co-Authors: Chen Shuhui
    Abstract:

    With the rapid increase of Network Traffic and the development of Network applications,Network Traffic monitor and Analysis becomes more and more difficult.This paper described the design and of implementation of a high-speed real-time Network Traffic Analysis System,named NTAS.It used PF_RING-based Network Traffic capture mechanism to capture Network Traffic,implementing intact Network session management and protocols identification based on Deterministic Finite Automation(DFA).NTAS outperformed current similar system in terms of performance and protocol-recognition accuracy.Experiment results show that NTAS can real-time monitor and analyze Network Traffic in high-speed Network environment.

Juana Baños - One of the best experts on this subject based on the ideXlab platform.

  • WWIC - Network Traffic Analysis and QoE Evaluation for Video Progressive Download Service: Netflix
    Lecture Notes in Computer Science, 2015
    Co-Authors: Francisco Lozano, Mari-carmen Aguayo-torres, Gerardo Gómez, Carlos Cárdenas, Juana Baños
    Abstract:

    Over the Top video streaming services has grown very rapidly in recent years, with the emerge of diverse online video stores. One of the popular over the top services is Netflix. The significant increase of user data consumption by this type of services affects the performance of communications Networks, and operators need methods to estimate how well the Network behaves. In this paper a Network Traffic Analysis of Netflix is presented. The Traffic study has been performed with diverse devices and access technologies. A model for quality of experience (QoE) evaluation, based on application performance metrics, has been applied to estimate Mean Opinion Score (MOS) by end users.

  • Network Traffic Analysis and QoE Evaluation for Video Progressive Download Service: Netflix
    2015
    Co-Authors: Francisco Lozano, Mari-carmen Aguayo-torres, Gerardo Gómez, Carlos Cárdenas, Juana Baños
    Abstract:

    Over the Top video streaming services has grown very rapidly in recent years, with the emerge of diverse online video stores. One of the popular over the top services is Netflix. The significant increase of user data consumption by this type of services affects the performance of communications Networks, and operators need methods to estimate how well the Network behaves. In this paper a Network Traffic Analysis of Netflix is presented. The Traffic study has been performed with diverse devices and access technologies. A model for quality of experience (QoE) evaluation, based on application performance metrics, has been applied to estimate Mean Opinion Score (MOS) by end users.

Xinyu Yang - One of the best experts on this subject based on the ideXlab platform.

  • A novel Network Traffic Analysis method based on fuzzy association rules
    Lecture Notes in Computer Science, 2004
    Co-Authors: Xinyu Yang, Wenjing Yang, Ming Zeng, Yi Shi
    Abstract:

    For Network Traffic Analysis and forecasting, a novel method based on fuzzy association rules is proposed in this paper. Connecting fuzzy logic theory with association rules, the method sets up the fuzzy association rules and could analyze the Traffic of the global Network by using data mining algorithm. Therefore, this method can represent the Traffic's characters much more precisely and forecast the behaviors of Traffic in advance. The paper firstly introduces the new classification method on Network Traffic. Then the fuzzy association rules are applied to analyze the behaviors of Traffic in existence. Finally, the results of simulation experiments indicating that the fuzzy association rule is very effective in discovering the relativity of different Traffic in the Analysis of Traffic flow are shown.

  • MDAI - A Novel Network Traffic Analysis Method Based on Fuzzy Association Rules
    Modeling Decisions for Artificial Intelligence, 2004
    Co-Authors: Xinyu Yang, Wenjing Yang, Ming Zeng, Yi Shi
    Abstract:

    For Network Traffic Analysis and forecasting, a novel method based on fuzzy association rules is proposed in this paper. Connecting fuzzy logic theory with association rules, the method sets up the fuzzy association rules and could analyze the Traffic of the global Network by using data mining algorithm. Therefore, this method can represent the Traffic’s characters much more precisely and forecast the behaviors of Traffic in advance. The paper firstly introduces the new classification method on Network Traffic. Then the fuzzy association rules are applied to analyze the behaviors of Traffic in existence. Finally, the results of simulation experiments indicating that the fuzzy association rule is very effective in discovering the relativity of different Traffic in the Analysis of Traffic flow are shown.

Liu Fengcheng - One of the best experts on this subject based on the ideXlab platform.

  • Network Traffic Analysis System Based on Multidimensional Data Model
    Computer Engineering, 2006
    Co-Authors: Liu Fengcheng
    Abstract:

    By applying the multidimensional multilevel data model to Network Traffic,a new definition of Network flow is provided,which is called the Network flow multidimensional data model or NF-MDM for short.This paper clearly defines the fact table and dimension tables of NF-MDM,and then establishes the star schema and multidimensional cube of Network flows,and then analyzes the Network Traffic by aggregation,slice,dice,drill-down,roll-up.The experiments indicate that the NF-MDM provides clearer angles and more flexible methods for metwork Traffic analyses.A multidimensional Network Traffic Analysis system based on the NF-MDM has been implemented and applied to some kind of high-end commercial Network Traffic Analysis equipments.