Evaluation MCDM Multi-disjoint Paths Selection Algorithms Using Fuzzy-Copeland Ranking Method

To increase the Internet's reliability and to have greater control over traffic transmission, reliable path selection is important and Multipath routing is promising technique that are used in the communication networks. Finding reliable end-end paths and backup can increase network performance. So, using proper decision metrics and algorithm should be used to paths and backup selection phase in these networks. For this goal, in this paper selecting a more reliable multi disjoint paths is addressed as a multi-criteria decision making (MCDM) problem and availability factor is defined and calculated based on network histories. For decision algorithm, a new fuzzy evaluation method is proposed to rank these multi disjoint paths selection algorithms and it is compared with bandwidth based, TOPSIS, FuzzyTOPSIS and AHP methods as candidate techniques to select more appropriate global disjoint paths in the IP/MPLS networks with packet loss, delay and availability parameters as decision making metrics. The proposed method combines fuzzy theory and Copeland method to evaluate the rank of each proposed method base on bandwidth, delay and new defined availability metric of selected end to end paths. Simulation results show that this method selects more reliable backup paths with better bandwidth in compared with others and can be used to path selection in IP/MPLS networks

Application of Fuzzy Multi-Criteria Decision Making Methods on Six Sigma Projects Selection

Abstract. Six sigma method widely applied in production and service businesses is known as a project-oriented method. In six sigma method, selection of the prior project among others can be considered as a multi -criteria decision making problem. The conducted literature review has revealed that there is a large number of methods to select six sigma projects. It is more appropriate to use fuzzy multi-criteria decision making methods in project selection since evaluation criteria of six sigma projects include uncertainties. The aim of this study is to select the most appropriate project as a result of evaluating the projects by Fuzzy VIKOR, Fuzzy TOPSIS and Fuzzy COPRAS as methods of fuzzy multicriteria decision-making and integrating the ranking scores obtained from each method by Copeland method. The proposed method has been implemented in a large scale production company, operating in Aydın ASTİM Organized Industrial Zone.Keywords. Six Sigma Projects, Fuzzy VIKOR, Fuzzy TOPSIS, Fuzzy COPRAS, Fuzzy AHP, Copeland Method.JEL. M11, C44, L20, C02, D70, O22

A fuzzy-based QoS Maximization protocol for WiFi Multimedia (IEEE 802.11e) Ad hoc Networks

The Quality of Service (QoS) management within a multiple-traffic Wi-Fi MultiMedia (WMM) ad hoc network is a tedious task, since each traffic type requires a well determined QoS-level. For this reason, the IEEE Working Group has proposed the IEEE 802.11e Enhanced Distributed Channel Access (EDCA) protocol at the MAC layer of WMM ad hoc networks. However, several studies have shown that EDCA must be further improved for three main reasons. The first reason is the poor performance of EDCA under high traffic conditions due to the high collision rate. The second reason is the need to maximize the traffic performance (delay, throughput, etc.) guaranteed by EDCA, seen the rapid evolution of the applications (multimedia, real time, etc.). The third reason is the need to maximize the energy efficiency of the EDCA, seen its use in battery constrained devices (e.g. Laptop, Smart phone, Tablet computers, etc.). For these three reasons, we propose in this paper a Three-in-One solution MAC protocol called QoS Maximization of EDCA (QM-EDCA), which is an enhanced version of EDCA. Based on the fuzzy logic mathematic theory, QM-EDCA incorporates a dynamic MAC parameters fuzzy logic system, in order to adapt dynamically the Arbitration inter frame Spaces according to the network state and remaining energy. Simulation results show that QM-EDCA outperforms EDCA by reducing significantly the collision rate, and maximizing traffic performance and energy-efficiency. In addition our solution is fully distributed