Quality of Service Evaluation using a Combination of Fuzzy C-Means and Regression Model

In this study, a network quality of service (QoS) evaluation system was proposed. The system used a c ombination of fuzzy C-means (FCM) and regression model to analyse and assess the QoS in a simulated network. Network QoS parameters of multimedia applications were intelligently analysed by FCM clu stering algorithm. The QoS parameters for each FCM cluster centre were then inputted to a regression model in order to qua ntify the overall QoS. The proposed QoS evaluation system provided va luable information about the network’s QoS patterns and ba sed on this information, the overall network’s QoS was effectiv ely quantified. Keywords—Fuzzy C-means; regression model, network quality of service

[1]  F. Fnaiech,et al.  Color image segmentation using automatic thresholding and the fuzzy C-means techniques , 2008, MELECON 2008 - The 14th IEEE Mediterranean Electrotechnical Conference.

[2]  Rolland Vida,et al.  Adaptive regression algorithm for distributed dynamic clustering in wireless sensor networks , 2009, 2009 2nd IFIP Wireless Days (WD).

[3]  Gerardo Beni,et al.  A Validity Measure for Fuzzy Clustering , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Andrew W. Moore,et al.  Architecture of a network monitor , 2003 .

[5]  Vinod Sharma,et al.  QoS routing in MPLS networks using active measurements , 2003, TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region.

[6]  Lucia Lo Bello,et al.  CWFC: A contention window fuzzy controller for QoS support on IEEE 802.11e EDCA , 2008, 2008 IEEE International Conference on Emerging Technologies and Factory Automation.

[7]  Rusty O. Baldwin,et al.  Improving the Real-time Performance of a Wireless Local Area Network , 1999 .

[8]  Dorel Picovici,et al.  Objective assessment of audio quality , 2008 .

[9]  Mark Davis,et al.  Performance evaluation of video streaming with background traffic over IEEE 802.11 WLAN networks , 2005, WMuNeP '05.

[10]  Chunhui Zhao,et al.  A Detection Method for Routing Attacks of Wireless Sensor Network Based on Fuzzy C-means Clustering , 2009, 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery.

[11]  Farnam Jahanian,et al.  An extensible probe architecture for network protocol performance measurement , 1998, SIGCOMM '98.

[12]  Preben E. Mogensen,et al.  Subjective evaluation of packet service performance in UMTS and heterogeneous networks , 2006, Q2SWinet '06.

[13]  S.K. Panda,et al.  Fuzzy C-Means clustering protocol for Wireless Sensor Networks , 2010, 2010 IEEE International Symposium on Industrial Electronics.

[14]  S. Chatterjee,et al.  Regression Analysis by Example , 1979 .

[15]  Ray Jain,et al.  The art of computer systems performance analysis - techniques for experimental design, measurement, simulation, and modeling , 1991, Wiley professional computing.

[16]  Zengfeng Wang Comparison of Four Kinds of Fuzzy C-Means Clustering Methods , 2010, 2010 Third International Symposium on Information Processing.

[17]  John A. Zinky,et al.  Experimental QoS performances of multimedia applications , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[18]  Marcelo Pias,et al.  EdgeMeter: distributed network metering model , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[19]  Jinglu Hu,et al.  Network Administrator Assistance System Based on Fuzzy C-means Analysis , 2009, J. Adv. Comput. Intell. Intell. Informatics.

[20]  Mohammad Saraireh Medium access control mechanisms for quality of service in wireless computer networks. , 2006 .