An efficient optimization algorithm of autonomic managers in service-based applications

Abstract

Cloud Computing is an emerging paradigm in Information Technologies that enables the delivery of infrastructure, software and platform resources as services. It is an environment with automatic service provisioning and management. In these last years autonomic management of Cloud services is receiving an increasing attention. Meanwhile, optimization of autonomic managers remains not well explored. In fact, almost all the existing solutions on autonomic computing have been interested in modeling and implementing of autonomic environments without paying attention on optimization. In this paper, we propose a new efficient algorithm to optimize autonomic managers for the management of service-based applications. Our algorithm allows to determine the minimum number of autonomic managers and to assign them to services that compose managed service-based applications. The realized experiments proves that our approach is efficient and adapted to servicebased applications that can be not only described as architecture-based but also as behavior-based compositions of services.