scholarly journals Using Ensemble and TOPSIS with AHP for Classification and Selection of Web Services

2021 ◽  
pp. 1-27
Author(s):  
Mithilesh Pandey ◽  
Sunita Jalal ◽  
Chetan Singh Negi ◽  
Dharmendra Kumar Yadav
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Selection ◽  
Ensemble Classification ◽  
Analytic Hierarchy ◽  
Web Service Selection ◽  
Weight Calculation ◽  
Order Preference ◽  
Computational Resources ◽  
The Web

Due to the increasing number of Web Services with the same functionality, selecting a Web Service that best serves the needs of the Web Client has become a tremendously challenging task. Present approaches use non-functional parameters of the Web Services but they do not consider any preprocessing of the set of functionally Similar Web Services. The lack of preprocessing results in increased use of computational resources due to unnecessary processing of Web Services that have a very low to no chance of satisfying the consumer’s requirements. In this paper, we propose an Ensemble classification method for preprocessing and a Web Service Selection method based on the Quality of Service (QoS) parameters. Once the most eligible Web Services are enumerated through classification, they are ranked using the Technique of Order Preference by Similarity to Ideal Solution (TOPSIS) method with Analytic Hierarchy Process (AHP) used for weight calculation. A prototype of the method is developed, and experiments are conducted on a real-world Web Services dataset. Results demonstrate the feasibility of the proposed method.

A Quality Driven Web Service Selection Model

2012 ◽  
pp. 142-164 ◽  
Author(s):  
Pierluigi Plebani ◽  
Filippo Ramoni
Keyword(s):  
Web Services ◽  
Web Service ◽  
Cost Benefit Analysis ◽  
Selection Process ◽  
Service Selection ◽  
User Preferences ◽  
Analytic Hierarchy ◽  
Web Service Selection ◽  
The One ◽  
The Web

The chapter introduces a quality of Web service model which can be exploited by a Web service broker during the Web service selection phase. The model considers both user and provider standpoints. On the one hand, providers express their capabilities with respect to measurable dimensions (e.g., response time, latency). On the other hand, users can define the requirements with a higher level of abstraction (e.g. performance). Since the quality is subjective by definition, the presented quality model also maps the user preferences, i.e., how much a quality dimension is more important than another one in evaluating the overall quality. The Analytic Hierarchy Approach (AHP) has been adopted as a technique for expressing user preferences. The chapter also describes how the model can be exploited in the Web service selection process. Starting from a set of functionally equivalent Web services, the selection process identifies which are the Web services able to satisfy the user requirements. Moreover, according to a cost-benefit analysis, the list of selected Web services is sorted and, as a consequence, the best Web service is identified.

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.

Social Web Services Management

2016 ◽  
pp. 204-220
Author(s):  
Zakaria Maamar ◽  
Noura Faci ◽  
Ejub Kajan ◽  
Emir Ugljanin
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Use ◽  
Service Selection ◽  
High Availability ◽  
Social Web ◽  
Web Service Selection ◽  
Ongoing Work ◽  
The Web ◽  
Selection Of

As part of our ongoing work on social-intensive Web services, also referred to as social Web services, different types of networks that connect them together are developed. These networks include collaboration, substitution, and competition, and permit the addressing of specific issues related to Web service use such as composition, discovery, and high-availability. “Social” is embraced because of the similarities of situations that Web services run into at run time with situations that people experience daily. Indeed, Web services compete, collaborate, and substitute. This is typical to what people do. This chapter sheds light on some criteria that support Web service selection of a certain network to sign up over another. These criteria are driven by the security means that each network deploys to ensure the safety and privacy of its members from potential attacks. When a Web service signs up in a network, it becomes exposed to both the authority of the network and the existing members in the network as well. These two can check and alter the Web service's credentials, which may jeopardize its reputation and correctness levels.

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.

Social Web Services Management

2014 ◽  
pp. 135-151
Author(s):  
Zakaria Maamar ◽  
Noura Faci ◽  
Ejub Kajan ◽  
Emir Ugljanin
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Use ◽  
Service Selection ◽  
High Availability ◽  
Social Web ◽  
Web Service Selection ◽  
Ongoing Work ◽  
The Web ◽  
Selection Of

As part of our ongoing work on social-intensive Web services, also referred to as social Web services, different types of networks that connect them together are developed. These networks include collaboration, substitution, and competition, and permit the addressing of specific issues related to Web service use such as composition, discovery, and high-availability. “Social” is embraced because of the similarities of situations that Web services run into at run time with situations that people experience daily. Indeed, Web services compete, collaborate, and substitute. This is typical to what people do. This chapter sheds light on some criteria that support Web service selection of a certain network to sign up over another. These criteria are driven by the security means that each network deploys to ensure the safety and privacy of its members from potential attacks. When a Web service signs up in a network, it becomes exposed to both the authority of the network and the existing members in the network as well. These two can check and alter the Web service's credentials, which may jeopardize its reputation and correctness levels.

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>

Context-Aware Personalization Recommendation of Web Services

2013 ◽  
Vol 765-767 ◽  
pp. 1490-1493
Author(s):  
Qiang Dong ◽  
Xiu Guo Zhang ◽  
Yuan Yuan ◽  
Ting Ting Han ◽  
Zhi Yi Zhu
Keyword(s):  
Web Services ◽  
Web Service ◽  
Selection Process ◽  
Service Selection ◽  
Research Area ◽  
Context Aware ◽  
Recommendation Algorithm ◽  
Web Service Selection ◽  
Recommendation Strategy ◽  
The Web

Web service selection has been a hot research area in recent years. In order to improve users satisfaction of service selection, optimization algorithm and recommendation algorithm have been used in the web service selection process. This paper uses context information in selecting and implementing process of Web services recommendation to make the recommendation result more accurate. According to different users different requests, combining with contexts obtained from environment, we give matching recommendation strategy suitable for the current situation, personalize the recommendation process and make it possible to improve the accuracy of the recommendation result.

scholarly journals An Intelligent Web Service Composition and Resource-Optimization Method Using K-Means Clustering and Knapsack Algorithms

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2023
Author(s):  
Issam Alhadid ◽  
Sufian Khwaldeh ◽  
Mohammad Al Rawajbeh ◽  
Evon Abu-Taieh ◽  
Ra’ed Masa’deh ◽  
...  
Keyword(s):  
Web Services ◽  
Web Service ◽  
Resource Utilization ◽  
Service Composition ◽  
Service Selection ◽  
Experimental Results ◽  
State Action ◽  
Web Service Selection ◽  
Proposed Model ◽  
The Web

Service-oriented architecture (SOA) has emerged as a flexible software design style. SOA focuses on the development, use, and reuse of small, self-contained, independent blocks of code called web services that communicate over the network to perform a certain set of simple tasks. Web services are integrated as composite services to offer complex tasks and to provide the expected services and behavior in addition to fulfilling the clients’ requests according to the service-level agreement (SLA). Web service selection and composition problems have been a significant area of research to provide the expected quality of service (QoS) and to meet the clients’ expectations. This research paper presents a hybrid web service composition model to solve web service selection and composition problems and to optimize web services’ resource utilization using k-means clustering and knapsack algorithms. The proposed model aims to maximize the service compositions’ QoS and minimize the number of web services integrated within the service composition using the knapsack algorithm. Additionally, this paper aims to track the service compositions’ QoS attributes by evaluating and tracking the web services’ QoS using the reward function and, accordingly, use the k-means algorithm to decide to which cluster the web service belongs. The experimental results on a real dataset show the superiority and effectiveness of the proposed algorithm in comparison with the results of the state–action–reward–state–action (SARSA) and multistage forward search (MFS) algorithms. The experimental results show that the proposed model reduces the average time of the web service selection and composition processes to 37.02 s in comparison to 47.03 s for the SARSA algorithm and 42.72 s for the MFS algorithm. Furthermore, the average of web services’ resource utilization results increased by 4.68% using the proposed model in comparison to the resource utilization by the SARSA and MFS algorithms. In addition, the experimental results showed that the average number of service compositions using the proposed model improved by 26.04% compared with the SARSA and MFS algorithms.

A Hybrid User-Centric Approach for Efficient Web Service Selection

2020 ◽  
Vol 10 (2) ◽  
pp. 1-20
Author(s):  
Neerja Negi ◽  
Satish Chandra
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Selection ◽  
User Requirements ◽  
End User ◽  
Main Challenge ◽  
Web Service Selection ◽  
User Expectations ◽  
Evaluation Mechanism ◽  
The Web

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.

Improving Energy Efficiency in Web Services

2013 ◽  
Vol 10 (1) ◽  
pp. 29-52 ◽  
Author(s):  
Jiwei Huang ◽  
Chuang Lin
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Web Services ◽  
Web Service ◽  
Service Selection ◽  
Service Systems ◽  
Markov Decision Problem ◽  
Speed Scaling ◽  
Dynamic Speed Scaling ◽  
The Web

With the rapid increase of the energy consumption associated with IT systems and services, energy efficiency is becoming a critical issue in the design, development and management of web service systems. One of the main mechanisms that can be used to reduce the energy consumption is dynamic speed scaling which scales the frequencies of the processors of web servers at hardware level. Another approach is service selection to facilitate the use of energy through effective distribution and management of the web services. In this paper, both the web service selection and server dynamic speed scaling are optimized by maximizing the quality of service (QoS) revenue and minimizing energy costs. Stochastic models of web service systems are proposed, and techniques for quantitative analysis of the performance and energy consumption are investigated. The authors formulate the service selection and speed scaling as a Markov Decision problem, and introduce related algorithms to solve it. Furthermore, the authors build up an optimization framework using multi-agent techniques, and design efficient algorithms to solve the problem in large-scale web service systems. Finally, the effectiveness of their approach is validated by simulation experiments.

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