An improved budget and priority aware task scheduling technique for Public Cloud Computing

The emergence of Cloud computing has generated a fundamental shift in the Computing industry by simplifying on-demand access to computing resources. The flexibility provided by Cloud computing has resulted in its greatly increased usage by end-users. With increased usage, the issue of optimizing cost of Cloud usage has become important for users of Public Clouds. There have been many task scheduling approaches that have been proposed. Most of these take computing requirements of the tasks into account but do not take the budget and relative differences in priority of the tasks. Information technology business users of Public clouds have to work under limited budgets when running their workloads, so an approach that could allow the workloads to be executed within their budgets will be beneficial. In the present work, the authors have proposed an improved fuzzy logic and heuristic based technique called Fuzzy Minimum Completion Time (FMCT) for performing budget and priority aware task scheduling for Public Cloud computing platforms. The authors have shown comparison of their technique to existing techniques using CloudSim simulator for various performance measures.