Experimental study on the effective range of FCM's fuzzifier values for web services' QoS data

Abstract

The work presented in this paper is part of the development of a fuzzy Interval Type-2 (IT2)-based system. An IT2 system contains fuzzy type-2 membership functions that can be generated using a pair of FCM fuzzifier, m values. Evidences show that the effective range of m values is influenced by the underlying dataset. Hence, the objective of this paper is to present the experimental study on finding the effective range of m values for web services' QoS data. The study aimed at identifying range of m values that successfully generated Gaussian membership functions. As proposed by previous work, the experiment was carried out upon the m values in the range of 1.4 to 2.6. The works involved the datasets of three QoS parameters. The results showed that two of the datasets has the effective range of 1.7 to 2.6, while another one was 1.6 to 2.6.

Enabling Adaptive Routing Service Customization via the integration of SDN and NFV

“…For example, how much bandwidth is exactly required for HDTV to be transferred across the network is too hard for the common user to know. Considering that the user usually cannot express such quantitative requirements for QoS parameters accurately and his judgments on things always follow the Gaussian distribution (Platenius et al, 2013), we use intervals to denote QoS parameters and use the Gaussian fuzzy membership functions (Hasan et al, 2014) to specify the bandwidth, delay, delay jitter and error rate requirement of the user desired routing service. We denote the actual bandwidth, delay, delay jitter and error rate of the route provided by the ISP as bw , de , jit and err .…”