Genetic Approach for Service Selection problem in Composite Web Service

Abstract

Services are the basic amass that aims to support the building of business application in a more flexible and interoperable manner for enterprise collaboration. Satisfying the needs of service consumer and to become accustomed to changing needs, service composition is performed to compose the various capabilities of available services. With the proliferation of services presenting similar functionalities around the web, the task of service selection for service composition is intricate. It is vital to provide systematic methodology for selecting required web services according to their non-functional characteristics or quality of service (QoS). Various heuristic and meta-heuristic algorithms are evolving to solve the QoS based service selection problem. One of the meta-heuristic algorithms is genetic algorithm. In this paper, the genetic algorithm is developed to maximize the non-functional Characteristic called the reliability of the composite web service and the performance of the developed algorithm is calculated.

A decentralizedagent‐basedsemantic service control andself‐adaptationin smart health mobile applications

“…Most delegate optimization techniques include Genetic Algorithms (GA) [15], Particle Swarm Optimization (PSO) [16], Ant Colony Optimization (ACO) [17] and Grey Wolf Optimization (GWO) [18]. These optimizers are most widely used for optimizing services qualities in the field of smart health.…”

“…Several approaches and platforms 4,5,8–18 have been proposed for reconfigurable IoT systems in the field of smart health. The three main categories of approaches are semantic‐based platforms, 4,5,8–11 rules‐based approaches, 12 and metaheuristic‐based approaches 13–18 .…”

“…Several approaches and platforms 4,5,8–18 have been proposed for reconfigurable IoT systems in the field of smart health. The three main categories of approaches are semantic‐based platforms, 4,5,8–11 rules‐based approaches, 12 and metaheuristic‐based approaches 13–18 . For example, Naqvi et al 4 have proposed a semantic‐based context‐driven approach with QoC (Quality of Context) for mobile cloud computing.…”

Semantic Web: A Study on Web Service Composition Approaches

“…Clustering Web services is very much important to facilitate service discovery. It can be done in many ways, one of them is based on the parameters used in the web service invocation [16].QOS-based web service composition based on Genetic Algorithm (GA) is introduced in [18] [21]. This GA based approach is considering QoS parameters.…”

An empirical study on QoS-based web services selection and composition

“…Sasikaladevi et al [21] devised a Population Based Service Selection Algorithm (PBSSA). Multidimensional Multi-choice Knapsack Problem (MMKP) to find the optimal fitness and Genetic algorithm is used to solve the MMKP.…”