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Top1. Introduction
This paper aims to understand the MWS discovery approaches for a dynamic mobile environment by identifying and comparing the current methods that are employed in MWS discovery with respect to the type of problem targeted. Then again identify noteworthy research prospects and understand the research gaps that can be explored in this domain. Web services can be as simple as Microsoft.Net passport or Google MAP API (Abidi, Daniyal, & Mehdi, 2014). MWS is different from conventional web services as it is lightweight and requires adaptable protocols, lightweight XML parser, lightweight SOAP implementation, RESTful description, smaller message formats suitable for deployment in resource-constrained devices in a dynamic mobile environment (DME) (Elgazzar, Hassanein, & Martin, 2013; Kim & Lee, 2009). DME is an environment that consists of heterogeneous mobile devices operated by numerous classes of users in highly mutable settings (Bobek & Nalepa, 2017). DME consist of mesh topology between awareness of the environment, user location, network condition, processing capabilities of the device, local storage, and energy resources, diversity of visualization capabilities, the proliferation of mobile devices and platforms that power the devices (Elgazzar, Martin, & Hassanein, 2014). The procedure of MWS discovery in a dynamic mobile environment presents its own unique set of challenges because of the constrictions in numerous and disparate mobile devices as shown in Figure 1(a).
The life cycle of MWS comprises publishing, locating or discovery, selection, composition, and invocation. But the most important stage is the discovery also known as matchmaking according to (Alonso, Casati, Kuno, & Machiraju, 2004; Fielding, 2000; Saadon & Mohamad, 2015). Matchmaking is the process of comparing the advertised MWS by the service publisher and the requested MWS to find not only the best possible web service but also the most relevant web service for a particular task. MWS discovery models based on semantic techniques appear to be the most encouraging technique these days as it improves the match-making accuracy by discriminating between syntactically similar but semantically disparate web services (De Souza Neto, Moreira, & Musicante, 2018; Ghayekhloo & Bayram, 2015). According to (Klusch, Kapahnke, Schulte, Lecue, & Bernstein, 2016), the semantic web service matchmaking techniques used in web services discovery can be divided into four categories generally logic-based, non-logic-based, hybrid, and adaptive. More specific categories of MWS are provided in (Saadon & Mohamad, 2011).
Web service discovery is very popular, yet research work addressing the issues in MWS discovery in a dynamic mobile environment is very limited (Verma & Srivastava, 2018). The key questions emerge to identify the contemporary web service discovery techniques that are applicable to dynamic mobile environment: how the proliferation of functionally similar MWS in DME is tackled? What are the contributions and drawbacks of the discovery techniques that tackle the persistent and unanticipated changes in DME in terms of effectiveness and efficiency? Thus, an evidence-based approach such as Systematic Literature Review (SLR) that offers a system for integrating empirical research so as to obtain a meaningful interpretation is a suitable approach that can facilitate summarizing, analysing, and synthesizing literature (Kitchenham et al., 2010) on MWS discovery approaches for a dynamic mobile environment, it will also simplify the process of developing new insight through critical evaluation of the existing research to find gaps (Xiao & Watson, 2017). SLR is different from other literature review methods of the literature review as it is considered to be Evidence-Based Software Engineering (Kitchenham et al., 2010). SLR that investigate the dimensions of web service discovery approaches is very imperative in developing a rigorous understanding of the current approaches so as to find noteworthy research prospects.