An Enhanced Ant Colony Optimization Based Algorithm to Solve QoS-Aware Web Service Composition

Dahan, Fadl; Hindi, Khalil El; Ghoneim, Ahmed; AlSalman, Hussain

doi:10.1109/access.2021.3061738

Cited by 36 publications

(26 citation statements)

References 41 publications

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“…Research into the problems of the search, selection, and composition of services for different options of online technologies continues today. Thus, in [18], it is proposed to use an improved version of the algorithm of optimization of colonies of flying ants to solve the problem of selecting services according to their quality indicators. A special algorithm of global optimization and dynamic redevelopment is proposed in [19] to solve the problem of choosing the optimal plan for performing a function on a set of services with different quality indicators.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Improving a method for selecting information technology services

Рetrychenko

Левыкин

Iuriev

2021

EEJET

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The main purpose of modern information systems (IS) is to support the procedures of controlling many business processes (BP) of an enterprise. At the same time, due to a weak formalization of BP, processes of development, reengineering of various service-oriented IS and IT services are a complex problem. To address this problem, the task to improve the method for choosing IT services that meet an assigned set of functional and non-functional limitations was stated. The specific features of the original method for choosing IT services were analyzed, its main shortcomings were identified. The model of the BP precedent was modified to establish the relationship between descriptions of the precedent, functional requirements, and the used IT services. The method for selecting IT services for the IS was improved by adding the functions of requirements analysis and searching for descriptions of IT services that partially meet the stated functional requirements. In the method, the adaptive linear associator of the mADALIN neuron was used to quantify the degree of match of the functional requirement and the description of the function of the IT service. These proposals were the basis for the improved method for selecting the IT service that best fits the set of constraints that are formed. Based on the result of the conducted research, an experimental test of the improved method for selecting an IT service to solve the problem of automation of the activities of sale force of the electronic policy OSAGO was carried out. The information technology implementing the original method for choosing IT services was compared to the improved method. It was shown that the improved method makes it possible to identify situations of a match of functional requirements of a customer and the descriptions of IT services. This makes it possible to select those IT services that match the functional requirements to a degree above the assigned minimum limit

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Section: Literature Review and Problem Statementmentioning

confidence: 99%

Improving a method for selecting information technology services

Рetrychenko

Левыкин

Iuriev

2021

EEJET

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“…With the continuous development of intelligent optimization algorithms in recent years, more and more swarm intelligence optimization algorithms are studied and applied in Web service composition. For example, the cuckoo search based web service composition method proposed in reference [3], and the flying ant colony algorithm model proposed in reference [4] based on the improved ant colony algorithm to solve the multi-objective optimization and service selection problems in QoS, but at the same time, these methods can not avoid falling into the local optimal situation. Reference [5] proposed a new particle swarm optimization algorithm, bee colony optimization algorithm, to solve the multi-objective web service composition problem.…”

Section: Current Research Statusmentioning

confidence: 99%

Composition of Web Services of Multi-Population Adaptive Genetic Algorithm Based on Cosine Improvement

Meng¹,

Zhang²

2021

JCC

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Web quality of service (QoS) awareness requires not only the selection of specific services to complete specific tasks, but also the comprehensive quality of service of the whole web service composition. How to select the web service composition with the highest comprehensive QoS is a NP hard problem. In this paper, an improved multi population genetic algorithm is proposed. Cosine adaptive operator is added to the algorithm to avoid premature algorithm caused by improper genetic operator and the disadvantage of destroying excellent individuals in later period. Experimental results show that compared with the common genetic algorithm and multi population genetic algorithm, this algorithm has the advantages of shorter time consumption and higher accuracy, and effectively avoids the loss of effective genes in the population.

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“…The QoS matrix was derived from Equation (2). It allowed for defining the values to be used by the recognition modules (Γ).…”

Section: Ks and Ps Recognition Scenariosmentioning

confidence: 99%

“…In combination with other services, these functionalities are those that satisfy specific requirements. The composition task depends on placing logically arranged services and involves aspects defined in its non-functional requirements (NFRs), which constitute quality of service (QoS) criteria to select WSs [2]. The FRs establish which services will be in the WSC, and the NRFs establish which QoS criteria those services will have to satisfy.…”

Section: Introductionmentioning

confidence: 99%

QoS-Based Pattern Recognition Approach for Web Service Discovery: Ar_WSDS

Adarme

Jimeno

2021

Applied Sciences

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Web service composition requires high levels of integration and reliability of the services involved in its operation, which must meet specific quality criteria to ensure their proper execution and deployment. The discovery and selection of web services currently face optimization problems. Many services might satisfy a requirement with similar quality criteria. Because of this, software developers have to choose the most appropriate services for a given composition, complicated by the rapid increase in providers and services available in the cloud. Service composition also implies coupling according to a composition flow and non-functional requirement criteria. Such requirements make selection and composition a complex task not previously solved in the literature. This paper presents Ar_WSDS, a computational approach for web services discovery and selection in cloud environments, which bases its implementation on the brain’s pattern recognition systematic functioning. This process allows classifying web services through recognition modules created dynamically based on their quality parameters, resulting in a set of web services suitable for a web service composition. This approach allows a solution to the selection problem using less complex tasks. This paper introduces an architectural and procedural definition that provides the web service description with a pattern to recognize and select services using different recognition levels. We simulated our approach and evaluated it using a dataset from the QWS project that offers a set of quality criteria collected from different providers. The web services are recognized and classified using different quality criteria for the composition and each of their services. The results demonstrate the effectiveness of the discovery and selection process compared to other approaches. Furthermore, Ar_WSDS allows us to recognize and filter out web services with ambiguity and similarity in their provider information, a process that minimizes the discovery space for services.

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An Enhanced Ant Colony Optimization Based Algorithm to Solve QoS-Aware Web Service Composition

Cited by 36 publications

References 41 publications

Improving a method for selecting information technology services

Improving a method for selecting information technology services

Composition of Web Services of Multi-Population Adaptive Genetic Algorithm Based on Cosine Improvement

QoS-Based Pattern Recognition Approach for Web Service Discovery: Ar_WSDS

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