improving resource management performance using artificial intelligence: a genetic algorithm based approach

Resource management in networks is recently appeared as a major challenge in our new information technology era and it has been widely attracted researchers of the field. there are many providers in each network that offer different services in form of applications to end-users all around the world and various resources are needed for deployment of these services. developing effective resource management schemes improves functionality of providers. in this research, genetic algorithms which can consider numerous states simultaneously while investigating their fitness are applied to provision the resources. the proposed approach finds the exact virtual resources for hosting requests of demanded applications by keeping costs at minimum؛ previous approaches focused on workloads and minimizing their make spans. the approach helps cloud providers select the most proper computing virtual resources for hosting the demanded applications while considering both cost and mapping of requirements of the applications. results show the efficiency of each approach in comparison with other approaches.