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Web services play vital role in the development of emerging technologies such as Cloud computing and Internet of Things. Although, there is a close relationship among the discovery, selection and composition tasks of Web services, research community has treated these challenges at individual level rather to focus on them collectively for developing efficient solution, which is the purpose of this work. This paper aims to propose an approach to integrate the service discovery, selection and composition of Semantic Web services on runtime basis.

The proposed approach defined as a quality of service (QoS)-aware approach is based on QoS model to perform discovery, selection and composition tasks at runtime to enhance the user satisfaction and quality guarantee by incorporating non-functional parameters such as response time and throughput with the Web services and user request. In this paper, the proposed approach is based on ontology for semantic description of Web services, which provides interoperability and automation in the Web services tasks.

This work proposed an integrated framework of Web service discovery, selection and composition which supports end user to search, select and compose the Web services at runtime using semantic description and non-functional requirements. The proposed approach is evaluated by various data sets from the Web Service Challenge 2009 (WSC-2009) to show the efficiency of this work. A use case scenario of Healthcare Information System is implemented using proposed work to demonstrate the usability and requirement the proposed approach.

The main contribution of this paper is to develop an integrated approach of Semantic Web services discovery, selection and composition by using the non-functional requirements.

The main goal of this paper is to study the cloud service discovery mechanisms. In this paper, the discovery mechanisms are ranked in three major classes: centralized, decentralized, and hybrid. Moreover, in this classification, the peer-to-peer (P2P) and agent-based mechanisms are considered the parts of the decentralized mechanism. This paper investigates the main improvements in these three main categories and outlines new challenges. Moreover, the other goals are analyzing the current challenges in a range of problem areas related to cloud discovery mechanisms and summarizing the discussed service discovery techniques.

Systematic literature review (SLR) is utilized to detect, evaluate and combine findings from related investigations. The SLR consists of two key stages in this paper: question formalization and article selection processes. The latter includes three steps: automated search, article selection and analysis of publication. These investigations solved one or more service discovery research issues and performed a general study of an experimental examination on cloud service discovery challenges.

In this paper, a parametric comparison of the discovery methods is suggested. It also demonstrates future directions and research opportunities for cloud service discovery. This survey will help researchers understand the advances made in cloud service discovery directly. Furthermore, the performed evaluations have shown that some criteria such as security, robustness and reliability attained low attention in the previous studies. The results also showed that the number of cloud service discovery–related articles rose significantly in 2020.

This research aimed to be comprehensive, but there were some constraints. The limitations that the authors have faced in this article are divided into three parts. Articles in which service discovery was not the primary purpose and their title did not include the related terms to cloud service discovery were also removed. Also, non-English articles and conference papers have not been reviewed. Besides, the local articles have not been considered.

One of the most critical cloud computing topics is finding appropriate services depending on consumer demand in real-world scenarios. Effective discovery, finding and selection of relevant services are necessary to gain the best efficiency. Practitioners can thus readily understand various perspectives relevant to cloud service discovery mechanisms. This paper's findings will also benefit academicians and provide insights into future study areas in this field. Besides, the drawbacks and benefits of the analyzed mechanisms have been analyzed, which causes the development of more efficient and practical mechanisms for service discovery in cloud environments in the future.

This survey will assist academics and practical professionals directly in their understanding of developments in service discovery mechanisms. It is a unique paper investigating the current and important cloud discovery methods based on a logical categorization to the best of the authors’ knowledge.

The purpose of this paper is to address the Internet of Things (IoT) service discovery problem and investigate the existing solutions to tackle this problem in many aspects.

This paper presents an overview of IoT services aiming at providing a clear understanding about their features because this term is still ambiguous for the IoT service discovery approaches. Besides, a full comparison study of the most representative service discovery approaches in the literature is presented over four perspectives: the IoT information model, the mechanism of IoT service discovery, the adopted architecture and the context awareness. These perspectives allow classifying, comparing and giving a deeper understanding of the existing IoT service discovery solutions.

This paper presents a new definition and a new classification of IoT services and citation of their features comparing with the traditional Web services. This paper discusses the existing solutions, as well as the main challenges, that face the service discovery issue in the IoT domain. Besides, two classifications of the approaches are adopted on the basis of their service description model and their mechanism of discovery, and a set of requirements that need to be considered when defining an IoT service are proposed.

There are few number works that survey the service discovery approaches in the IoT domain, but none of these surveys discuss the service description models in the IoT or the impact of the context awareness aspect in the service discovery solution. There are also few works that give a comprehensive overview of IoT services to understand their nature to facilitate their description and discovery. This paper fills this gap by performing a full comparison study of multi-category and recent approaches for service discovery in the IoT over many aspects and also by performing a comprehensive study of the IoT service features.

The purpose of this paper is to characterise a number of current and future computing environments and summarises their resource discovery requirements. It then seeks to analyse, with respect to the requirements of each environment, several established service discovery protocols and some newer protocols that are still in the research domain. In addition, the key features of a new resource discovery protocol that has been developed to operate with heterogeneous computing environments are described.

A comprehensive literature survey was undertaken, highlighting the shortcomings of existing resource discovery protocols with respect to large pervasive computing environments. Given the identified gaps in existing protocols, an alternative protocol is suggested.

The main findings of this paper relate to the identified shortcomings of existing resource discovery protocols. It was also found that a hybrid resource discovery protocol capable of spanning dynamic, mobile computing environments and more stable ones was able to overcome many of the challenges presented by large‐scale pervasive computing environments.

This paper presents comprehensive literature survey of the state‐of‐the‐art in resource discovery protocols, pointing out some of the problems that are not solved. The paper describes the design of an alternative protocol, and presents an evaluation of it. The pervasive computing research community can draw upon the survey and evaluation to guide the design of future resource discovery protocols for the increasingly dynamic world in which we live.

The success of web services involved the adoption of this technology by different service providers through the web, which increased the number of web services, as a result making their discovery a tedious task. The UDDI standard has been proposed for web service publication and discovery. However, it lacks sufficient semantic description in the content of web services, which makes it difficult to find and compose suitable web services during the analysis, search, and matching processes. In addition, few works on semantic web services discovery take into account the user’s profile. The purpose of this paper is to optimize the web services discovery by reducing the search space and increasing the number of relevant services.

The authors propose a new approach for the semantic web services discovery based on the mobile agent, user profile and metadata catalog. In the approach, each user can be described by a profile which is represented in two dimensions: personal dimension and preferences dimension. The description of web service is based on two levels: metadata catalog and WSDL.

First, the semantic web services discovery reduces the number of relevant services through the application of matching algorithm “semantic match”. The result of this first matching restricts the search space at the level of UDDI registry, which allows the users to have good results for the “functional match”. Second, the use of mobile agents as a communication entity reduces the traffic on the network and the quantity of exchanged information. Finally, the integration of user profile in the service discovery process facilitates the expression of the user needs and makes intelligible the selected service.

To the best knowledge of the authors, this is the first attempt at implementing the mobile agent technology with the semantic web service technology.

The aim of this article is to describes Sprague Library’s experience in using EBSCO Discovery Service (EDS) to market library services and resources in order to draw conclusions for other institutions.

Uses the case study of Montclair State University in developing a strategy for using Discovery Tools as a library promotional tool. Also includes examples from other institutions.

EDS (and other Discovery Services) can be helpful in highlighting library resources and services that may go unnoticed. Studies show a correlation between discovery tools and increased Interlibrary Loan (ILL) activity so it’s important to promote services like ILL within your discovery service.

With a reasonable effort, libraries can use discovery tools to provide additional modes of communication with users.

Highlights some of Sprague Library’s unique efforts in utilizing EDS to promote library resources and services.

There is an open discussion in the geographic information community about the use of digital libraries or search engines for the discovery of resources. Some researchers suggest that search engines are a feasible alternative for searching geographic web services based on anecdotal evidence. The purpose of this study is to measure the performance of Bing (formerly Microsoft Live Search), Google and Yahoo! in searching standardised XML documents that describe, identify and locate geographic web services.

The study performed an automated evaluation of three search engines using their application programming interfaces. The queries asked for XML documents describing geographic web services, and documents containing links to those documents. Relevant XML documents linked from the documents found in the search results were also included in the evaluation.

The study reveals that the discovery of geographic web services in search engines does not require the use of advanced search operators. Data collected suggest that a resource‐oriented search should combine simple queries to search engines with the exploration of the pages linked from the search results. Finally the study identifies Yahoo! as the best performer.

This is the first study that measures and compares the performance of major search engines in the discovery of geographic web services. Previous studies were focused on demonstrating the technical feasibility of the approach. The paper also reveals that some technical advances in search engines could harm resource‐oriented queries.

With the rise of alternate discovery services, such as Google Scholar, in conjunction with the increase in open access content, researchers have the option to bypass academic libraries when they search for and retrieve scholarly information. This state of affairs implies that academic libraries exist in competition with these alternate services and with the patrons who use them, and as a result, may be disintermediated from the scholarly information seeking and retrieval process. Drawing from decision and game theory, bounded rationality, information seeking theory, citation theory, and social computing theory, this study investigates how academic librarians are responding as competitors to changing scholarly information seeking and collecting practices. Bibliographic data was collected in 2010 from a systematic random sample of references on CiteULike.org and analyzed with three years of bibliometric data collected from Google Scholar. Findings suggest that although scholars may choose to bypass libraries when they seek scholarly information, academic libraries continue to provide a majority of scholarly documentation needs through open access and institutional repositories. Overall, the results indicate that academic librarians are playing the scholarly communication game competitively.

Process mining tools can help discover and improve the business processes of urban community services from historical service event records. However, for the community service domains with small datasets, the effects of process mining are generally limited due to process incompleteness and data noise. In this paper, a cross-domain knowledge transfer method is proposed to help service process discovery with small datasets by making use of rich knowledge in similar domains with large datasets.

First, ontology modeling is used to reduce the effects of cross-domain semantic ambiguity on knowledge transfer. Second, association rules (of the activities in the service processes) are extracted with Bayesian network. Third, applicable association rules are retrieved using an applicability assignment function. Further, the retrieved association rules in domains with large datasets are mapped to those with a small dataset using a linear programming method, with a heuristic miner being adopted to generate the process model.

The proposed method is verified based on the empirical data of 10 service domains from Beidaihe, China. Results show that process discovery performance of all 10 domains were improved with the overall robustness score, precision, recall and F1 score increased by 13%, 13%, 17% and 15%, respectively. For the domains with only small datasets, the cross-domain knowledge transfer method outperforms popular state-of-the art methods.

The limitations of sample sizes are greatly reduced. This scheme can be followed to establish business process management systems of community services with reasonable performance and limited sample sizes.

Web services are going mobile. A mobile enterprise can be established in a cellular network by participating mobile hosts, which act as web service providers, and their clients. Mobile hosts enable seamless integration of user‐specific services to the enterprise, by following web service standards, also on the radio link and via resource constrained smart phones. However, establishing such a mobile enterprise poses several technical challenges, such as the quality of service (QoS), discovery aspects and proper integration solutions, for the network as well as for the mobile phone users. The purpose of this paper is to summarize the challenges and research associated with this domain and with establishing the mobile enterprise.

The paper summarizes the challenges and research in the mobile web services domain, along with a detailed discussion of the developed mobile web service mediation framework (MWSMF). MWSMF is realized based on the enterprise service bus (ESB) technology, as an intermediary between mobile hosts and web service clients. Moreover, to scale the mobile enterprise to the loads possible in cellular networks, some of the components of MWSMF are shifted to the new utility computing paradigm, cloud computing.

From the study it was found that ESB provides a good integration solution for the mobile enterprise research challenges. The detailed analysis of the MWSMF concludes that the mediation framework and its components are horizontally scalable, thus allowing to utilize elasticity of cloud platform to meet load requirements of mobile enterprise in an easy and quick manner.

The study addresses the research with providing services from smart phones and establishing mobile enterprise. The QoS challenges are addressed and the study introduces an integration framework using ESB technology. The porting of MWSMF onto the cloud is also addressed. As an added value, the research serves as a case study for porting enterprise applications to the cloud.