A Hybrid User-Centric Approach for Efficient Web Service Selection

A Hybrid User-Centric Approach for Efficient Web Service Selection

Neerja Negi (Manav Rachna International Institute of Research and Studies, Faridabad, India) and Satish Chandra (Jaypee Institute of Information Technology, Faridabad, India)
Copyright: © 2020 |Pages: 20
DOI: 10.4018/IJIRR.2020040101


Over the last few years, e-commerce has exhibited explosive growth due to the ease of availability of the internet. E-commerce is rapidly changing the way in which businesses are interacting with each other as well as with their consumers. In each innovative e-commerce application, web services are being included as an important component. This leads to the availability of a huge number of web services that provide similar functionalities. The main challenge is to select the appropriate web service which fulfills the end user requirements. So, there is a need for a web service selection method that selects the web services not only based on their functionality, but also considers the nonfunctional requirements. This article proposes a method to preprocess web services using the J48 classification technique. After that, a hybrid weight evaluation mechanism is employed to obtain the weight values of each nonfunctional parameter. In the end, the web services that are near to user expectations are selected out using the ranking method.
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1. Introduction

Service-oriented architecture (SOA) provides a facility for software development that offers flexibility, reusability, and interoperability (Saxena et al., 2011). These types of software generally used in various domains such as e-governance, e-commerce, etc. E-Commerce generally offers business transaction activities on the web (Tsur et al., 2001). Thus, e-commerce suppliers offer web services as an essential feature to their consumers. Web services are usually applied to carry out application-to-application communication and to address the interoperability issues for the systems (Chen et al., 2003). For example, a web service could perform validation activities such as payment validation by taking information from a system. After that, it receives a further request for additional information for the completion of a payment method such as debit card account number, CVV number, and expiration date, etc. Therefore, web services are self-describing, interoperable, independent, modular applications that can be published, located, and invoked across the web (Ran, 2003). Due to the growth of internet technology, companies are promoting their approach to create a business in the form of web services. Nowadays, large numbers of web services are offering the same functionalities. So, there is a requirement to consider the nonfunctional parameters of web services to distinguish them from the functionally similar web services. For example, the nonfunctional parameters can be reliability, security, cost, and availability, etc. Sometime, it might be possible that some services have less response time, high availability, and high reliability (web services that are beneficial in all three terms) some of the web services have moderated quality and whereas other web services have low quality. Thus, it may be possible that the web services that are similar in functionality can differ in their QoS parameters.

Generally, the process of web service selection has done in two phases. In the first phase, based on their functionality web services with similar functionality are extracted from the web service pool The existing solutions such as the semantics-based approach (Purohit & Kumar, 2016; Kumar &. Mishra, 2008), AI-based solutions (Hwang et al., 2015) are best in this regard. In the second phase, the extracted web services from the first phase are sorted out based on their nonfunctional parameters. But to select the web services based on nonfunctional parameters, there is a need to determine the preference and weight value of QoS parameters. However, in many cases, the weight value of parameters has given by the end-user. But most of the time, due to the lack of precise knowledge end-user experience problems in specifying them accurately. It might be possible that sometimes, due to the incorrect specification of weights, the desired web services have not selected out by the system. In a previously proposed system (Negi & Chandra, 2014), the user specifies its QoS weight value according to their requirements. In this case, it should be necessary that the user should provide accurate value. But in real circumstances, there is a possibility that the user may not specify any weight values or he/she may specify partial weight values. So, there is a need for a mathematical model that could accurately calculate the weights for the users who are unable to specify exact weights for nonfunctional parameters.

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