A genetic algorithm with the concept of viral infections to solve hard constraints in workflow scheduling

초록

Cloud computing is an emerging technology that allows users to utilize on-demand computation, storage, data and services from around the world. The main contribution of this work is to propose a new multi-objective genetic algorithm coupled with the viral infection capable of handling hard constraints, such as restrictions on task scheduling, which are not handled by current algorithms. Furthermore, our algorithm can optimize any number of parameters such as execution time, cost, reliability, and availability; In addition, it can handle restrictions such as deadlines and requirements on the different variables. Using data of the Amazon EC2 cloud resources and workflows from London e-Science Center, we have been investigating the problem of scheduling workflow applications and have compared our algorithm with other scheduling algorithms. Our experimentations have shown the efficiency of our algorithm and have confirmed that the viral infection operator is a powerful tool when solving hard constraints.