Web Service Compositions for a Dynamic Large Environment Using Quality of Service (QOS) Optimization Techniques

Abstract

Many internet services are now available on the internet. End consumers have a variety of problems, such as when a single solution is unable to satisfy the need, when multiple solutions offer the same performance, or when the best possible service is required. Customers can build valuable solutions from the ones that are currently available at runtime thanks to the structure of dynamic internet services. When the same capacity is offered by several potential services, using QoS standards with internet solutions is crucial for selecting the best appropriate service. The best service is provided with a guarantee using genetic programming in conjunction with QoS-based solution construction. The architecture for an automated internet solution composition is suggested in this study, which is looking at QoS-based internet service structures. In this architecture, users first enter their functional and non-functional needs via interfaces into the system. Hereditary formula (GA) is then built for the ideal composition of web services in order to conveniently satisfy users' needs. In this situation, our task offers an optimization-based approach for structuring dynamic online solutions that takes the quality of service model into account. The suggested method creates the optimum makeup using a Genetic Formula. The suggested method effectively identifies the structure strategy that satisfies individual constraints. In a simulated setting, the approach's performance is evaluated.