An Optimal Micro-Services Architecture for Runtime Dynamic Binding in Web Services Using Hybrid Heuristic Algorithms

Abstract

Microservices are software development procedure a variation of the service-oriented architecture (SOA) auxiliary style that organizes an application as an assortment of approximately coupled administrations. In SOA, having numerous highlights, for example, adaptability and money saving advantages, interoperability, programming reuse. Also, the SOA is empowering and supports the official of administrations at runtime as powerful authoritative. Testing this dynamic restricting is one of the most testing assignments in SOA. Nonetheless, powerful authoritative of administrations raises a few extra difficulties, for example, overseeing multifaceted nature in administration structures utilizing dynamic official and non-deterministic conduct in administration choice and absence of discernibleness of the source code, absence of control of the administrations, the expense of testing. To overcome these problems, we propose optimal micro-service architecture for runtime dynamic binding in web services using hybrid heuristic algorithms (OMSA-DB). The main objective of proposed model is binding and scheduling Web services based on an assessment of this competition for users on the move. The first contribution is to introduce the dynamic whale optimization algorithm for new composition framework, which allows the process designers to design processes, based on business and process constraints. Second, we illustrate the derived micro-service architecture that exists in virtual space, to realize agile automation that can provide agility and flexibility to the optimal automation. Furthermore, we propose a queuing deep neural network (QDNN) is used to assign and periodically update service selection probabilities according to monitored average service response time.