Enriching Web Services Tags to Improve Data-Driven Web Services Composition

2021 ◽  
Author(s):  
Nahid Dara ◽  
Sima Emadi
Keyword(s):  
Web Services ◽  
Service Composition ◽  
Clustering Algorithm ◽  
Heuristic Method ◽  
Data Driven ◽  
Automatic Search ◽  
Automatic Service Composition ◽  
The Given ◽  
Graph Planning

Due to the large number of existing services and complexity of manual composition, automatic service composition is provided to enable automatic search of the service compositions for the given queries. Many solutions for automatic service composition have been developed, including integer programming, graph planning, artificial intelligence, and so on in this paper, a heuristic method is proposed to improve the data-driven composition of web services by enriching tags based on tags semantic. To do so, firstly, useful information on web services is collected from various sources and is turned into collections of tags. In the next step, using the hierarchical clustering algorithm, the tags are clustered based on semantic similarity. Thereafter, for services which do not have enough tags, enrichment of the tag is carried out and finally, using an algorithm, composition solutions based on QoS parameters are extracted, which can formulate user targets or even provide potential compositions. Moreover, a series of tests were conducted on the web services, which validate the efficiency of the proposed approach. The experimental results confirm the effectiveness of the proposed service composition method and high quality of tag enriching strategies.   

scholarly journals A Cluster-Based Browsing Model For QoS-Aware Web Service Selection

2021 ◽  
Author(s):  
Kian Farsandaj
Keyword(s):  
Web Services ◽  
Web Service ◽  
Clustering Algorithm ◽  
Service Selection ◽  
Functional Requirements ◽  
Analysis Techniques ◽  
Symbolic Data ◽  
Web Service Selection ◽  
The Web

In the last decade, selecting suitable web services based on users’ requirements has become one of the major subjects in the web service domain. Any research works have been done - either based on functional requirements, or focusing more on Quality of Service (QoS) - based selection. We believe that searching is not the only way to implement the selection. Selection could also be done by browsing, or by a combination of searching and browsing. In this thesis, we propose a browsing method based on the Scatter/Gather model, which helps users gain a better understanding of the QoS value distribution of the web services and locate their desired services. Because the Scatter/Gather model uses cluster analysis techniques and web service QoS data is best represented as a vector of intervals, or more generically a vector of symbolic data, we apply for symbolic clustering algorithm and implement different variations of the Scatter/Gather model. Through our experiments on both synthetic and real datasets, we identify the most efficient ( based on the processing time) and effective implementations.

Applying Evolutionary Many-Objective Optimization Algorithms to the Quality-Driven Web Service Composition Problem

2016 ◽  
pp. 170-194
Author(s):  
Arion de Campos Jr. ◽  
Aurora T. R. Pozo ◽  
Silvia R. Vergilio
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Optimization Algorithms ◽  
Web Service Composition ◽  
Nsga Ii ◽  
Preference Relations ◽  
Multi Objective ◽  
Composition Problem

The Web service composition refers to the aggregation of Web services to meet customers' needs in the construction of complex applications. The selection among a large number of Web services that provide the desired functionalities for the composition is generally driven by QoS (Quality of Service) attributes, and formulated as a constrained multi-objective optimization problem. However, many equally important QoS attributes exist and in this situation the performance of the multi-objective algorithms can be degraded. To deal properly with this problem we investigate in this chapter a solution based in many-objective optimization algorithms. We conduct an empirical analysis to measure the performance of the proposed solution with the following preference relations: Controlling the Dominance Area of Solutions, Maximum Ranking and Average Ranking. These preference relations are implemented with NSGA-II using five objectives. A set of performance measures is used to investigate how these techniques affect convergence and diversity of the search in the WSC context.

Towards Automatic Composition of Geospatial Web Services

2010 ◽  
pp. 205-212
Author(s):  
Peng Yue ◽  
Liping Di ◽  
Wenli Yang ◽  
Genong Yu ◽  
Peisheng Zhao
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
General Information ◽  
Domain Experts ◽  
Service Oriented ◽  
Multiple Services ◽  
Automatic Service Composition ◽  
Geospatial Web Services ◽  
Technology Domain

In a service-oriented environment, an individual geospatial Web service is not sufficient to solve a complex real-world geospatial problem. Service composition, the process of chaining multiple services together, is required. Manual composition of Web services is laborious and requires much work of domain experts. Automatic service composition, if successful, will eventually widen the geospatial users market. This chapter reviews current efforts related to automatic service composition in both general information technology domain and geospatial domain. Key considerations in the geospatial domain are discussed and possible solutions are provided.

Quality-of-Service Based Web Service Composition and Execution Framework

2014 ◽  
pp. 74-93
Author(s):  
Bassam Al Shargabi ◽  
Osama Al-haj Hassan ◽  
Alia Sabri ◽  
Asim El Sheikh
Keyword(s):  
Quality Of Service ◽  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Service Selection ◽  
Web Service Composition ◽  
Web Service Selection ◽  
Selection Decisions ◽  
Uddi Registry

Software is gradually becoming more built by composing web services to support enterprise applications integration; thus, making the process of composing web services a significant topic. The Quality of Service (QoS) in web service composition plays a crucial role. As such, it is important to guarantee, monitor, and enforce QoS and ability to handle failures during execution. Therefore, an urgent need exists for a dynamic Web Service Composition and Execution (WSCE) framework based on QoS constraints. A WSCE broker is designed to maintain the following function: intelligent web service selection decisions based on local QoS for individual web service or global QoS based selection for composed web services, execution tracking, and adaptation. A QoS certifier controlled by the UDDI registry is proposed to verify the claimed QoS attributes. The authors evaluate the composition plan along with performance time analysis.

scholarly journals A Cluster-Based Browsing Model For QoS-Aware Web Service Selection

2021 ◽  
Author(s):  
Kian Farsandaj
Keyword(s):  
Web Services ◽  
Web Service ◽  
Clustering Algorithm ◽  
Service Selection ◽  
Functional Requirements ◽  
Analysis Techniques ◽  
Symbolic Data ◽  
Web Service Selection ◽  
The Web

In the last decade, selecting suitable web services based on users’ requirements has become one of the major subjects in the web service domain. Any research works have been done - either based on functional requirements, or focusing more on Quality of Service (QoS) - based selection. We believe that searching is not the only way to implement the selection. Selection could also be done by browsing, or by a combination of searching and browsing. In this thesis, we propose a browsing method based on the Scatter/Gather model, which helps users gain a better understanding of the QoS value distribution of the web services and locate their desired services. Because the Scatter/Gather model uses cluster analysis techniques and web service QoS data is best represented as a vector of intervals, or more generically a vector of symbolic data, we apply for symbolic clustering algorithm and implement different variations of the Scatter/Gather model. Through our experiments on both synthetic and real datasets, we identify the most efficient ( based on the processing time) and effective implementations.

Quality-of-Service Based Web Service Composition and Execution Framework

2011 ◽  
Vol 6 (3) ◽  
pp. 57-74 ◽  
Author(s):  
Bassam Al Shargabi ◽  
Osama Al-haj Hassan ◽  
Alia Sabri ◽  
Asim El Sheikh
Keyword(s):  
Quality Of Service ◽  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Service Selection ◽  
Web Service Composition ◽  
Web Service Selection ◽  
Selection Decisions ◽  
Uddi Registry

Software is gradually becoming more built by composing web services to support enterprise applications integration; thus, making the process of composing web services a significant topic. The Quality of Service (QoS) in web service composition plays a crucial role. As such, it is important to guarantee, monitor, and enforce QoS and ability to handle failures during execution. Therefore, an urgent need exists for a dynamic Web Service Composition and Execution (WSCE) framework based on QoS constraints. A WSCE broker is designed to maintain the following function: intelligent web service selection decisions based on local QoS for individual web service or global QoS based selection for composed web services, execution tracking, and adaptation. A QoS certifier controlled by the UDDI registry is proposed to verify the claimed QoS attributes. The authors evaluate the composition plan along with performance time analysis.

Web Service Composition, Optimization and the Implications for Developing Economies

2012 ◽  
pp. 57-78
Author(s):  
Adenike Osofisan ◽  
Idongesit E. Eteng ◽  
Iwara Arikpo ◽  
Abel Usoro
Keyword(s):  
Quality Of Service ◽  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Developing Economies ◽  
Web Service Composition ◽  
Theoretic Approach ◽  
Computing Paradigm ◽  
Service Oriented

The emergence of the Service Oriented computing paradigm with its implicit inclusion of web services has caused a precipitous revolution in software engineering, e-service compositions, and optimization of e-services. Web service composition requests are usually combined with end-to-end Quality of Service (QoS) requirements, which are specified in terms of non-functional properties e.g. response time, throughput, and price. This chapter describes what web services are; not just to the web but to the end users. The state of the art approaches for composing web services are briefly described and a novel game theoretic approach using genetic programming for composing web services in order to optimize service performance, bearing in mind the Quality of Service (QoS) of these web services, is presented. The implication of this approach to cloud computing and economic development of developing economies is discussed.

An Agent Architecture for Qos-Based Web Service Composition Using the Skyline Algorithm

2017 ◽  
Vol 6 (3) ◽  
pp. 179 ◽  
Author(s):  
El-Alami Ayoub ◽  
Hair Abdellatif
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Service Selection ◽  
Web Service Composition ◽  
Web Service Selection ◽  
Concrete Service ◽  
The Web ◽  
Selection Of

<p>Web service composition is a concept based on the built of an abstract process, by combining multiple existing class instances, where during the execution, each service class is replaced by a concrete service, selected from several web service candidates. This approach has as an advantage generating flexible and low coupling applications, based on its conception on many elementary modules available on the web. The process of service selection during the composition is based on several axes, one of these axes is the QoS-based web service selection. The Qos or Quality of Service represent a set of parameters that characterize the non-functional web service aspect (execution time, cost, etc...). The composition of web services based on Qos, is the process which allows the selection of the web services that fulfill the user need, based on its qualities. Selected services should optimize the global QoS of the composed process, while satisfying all the constraints specified by the client in all QoS parameters. In this paper, we propose an approach based on the concept of agent system and Skyline approach to effectively select services for composition, and reducing the number of candidate services to be generated and considered in treatment. To evaluate our approach experimentally, we use a several random datasets of services with random values of qualities.</p>

scholarly journals Develop a dynamic DBSCAN algorithm for solving initial parameter selection problem of the DBSCAN algorithm

2021 ◽  
Vol 23 (3) ◽  
pp. 1602
Author(s):  
Md. Zakir Hossain ◽  
Md. Jakirul Islam ◽  
Md. Waliur Rahman Miah ◽  
Jahid Hasan Rony ◽  
Momotaz Begum
Keyword(s):  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Cluster Radius ◽  
Dbscan Algorithm ◽  
Clustering Quality ◽  
Data Clusters ◽  
Minimum Number ◽  
The Given ◽  
Clustering Problems

<p>The amount of data has been increasing exponentially in every sector such as banking securities, healthcare, education, manufacturing, consumer-trade, transportation, and energy. Most of these data are noise, different in shapes, and outliers. In such cases, it is challenging to find the desired data clusters using conventional clustering algorithms. DBSCAN is a popular clustering algorithm which is widely used for noisy, arbitrary shape, and outlier data. However, its performance highly depends on the proper selection of cluster radius <em>(Eps)</em> and the minimum number of points <em>(MinPts)</em> that are required for forming clusters for the given dataset. In the case of real-world clustering problems, it is a difficult task to select the exact value of Eps and <em>(MinPts)</em> to perform the clustering on unknown datasets. To address these, this paper proposes a dynamic DBSCAN algorithm that calculates the suitable value for <em>(Eps)</em> and <em>(MinPts)</em> dynamically by which the clustering quality of the given problem will be increased. This paper evaluates the performance of the dynamic DBSCAN algorithm over seven challenging datasets. The experimental results confirm the effectiveness of the dynamic DBSCAN algorithm over the well-known clustering algorithms.</p>

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