Pairing New Approach of Tree Soft with MCDM Techniques: Toward Advisory an Outstanding Web Service Provider Based on QoS Levels

Abstract


 Web services (WSs) have become dynamic because of technological advancements and internet usage. Hence, selecting a WS provider among a variety of WS providers that perform the same function is a critical process. However, the crucial point is that various consumers may have varied needs when it comes to the quality attributes of services, such as cost, response time, throughput, security, availability, etc. These aspects of Web services are known as quality of service (QoS), or non-functional characteristics. Hence, this issue is the robust motivator for conducting this study. The objective of this study is to evaluate a set of WSs that provide various services for various consumers and organizations. This evaluation is conducted based on a set of QoS attributes. Hence, we are applying a new approach to describe this problem in the form of leaves or branches of a tree or hierarchy. This approach is represented in a soft tree set. Also, we leveraged Multi-Criteria Decision Making (MCDM) techniques such as entropy and weighted sum methods under the authority of the Single Value Neutrosophic (SVN) Scale. The entropy technique analyzes attributes or leaves in each level contained in the tree's soft approach, obtaining attributes’ weights. These weights are used to rank and recommend optimal WS providers through the application of these weights in WSM. The results of implementing entropy-WSM in a tree-soft approach indicated that WS2 is the optimal provider. In contrast, WS3 is the worst provider.