An integrated fuzzy-VIKOR-DEMATEL-TOPSIS technique for assessing QoS factors of SOA

Abstract

Quality of service (QoS) is a very important concept in service-oriented architecture (SOA). While there is a growing body of study on QoS-based service selection based on SOA, there is little research on analyzing QoS factors from the viewpoints of IT workers and researchers. As a result, the purpose of the current study aims to offer an integrated fuzzy VIKOR-TOPSIS-DEMATEL approach framework for evaluating QoS factors of online services from the viewpoint of experts in a fuzzy environment. A numerical assessment of the QoS factors for a case firm in Ghana indicated that the suggested technique is appropriate for the problem. Furthermore, the technique outcomes divided QoS factors into cause-effect variables, ranked QoS factors, and lastly, suggested conflicting QoS factors. The results from the Fuzzy DEMATEL aspect of the proposed approach found integrity, availability, accessibility, compliance, documentation, latency, and adaptability as causal variables. While response time, cost/price, reliability, performance, security, reputation, throughput, best practices, success ability, encryption, portability, storage, and consistency are regarded as influential variables. The Fuzzy TOPSIS aspect of the technique found adaptability, documentation, consistency, transaction, and accessibility are the most ranked QoS factors of online services. The fuzzy VIKOR side of the proposed method discovers integrity, cost, and latency as incommensurable QoS factors. Finally, a sensitivity analysis was carried out, and the results show the model is robust. This study confirms the position of existing knowledge on sensitivity analysis in the QoS literature. In the issue of QoS factor evaluation, this work effectively blended three MCDM techniques. The study's shortcoming stems from its reliance on data from QoS specialists from only one developing nation (i.e. Ghana).

Comparative analysis of fuzzy multi-criteria decision-making methods for quality of service-based web service selection

“…Comparative analysis of fuzzy multi-criteria decision-making methods for quality of … (Paul Aazagreyir) is now quite common [3]. The popularity of services and the uniformity of their functions result in nonfunctional attributes that are comparable [4]. The features and quality of the candidate service are the two criteria for web service selection.…”