A Parallel Heuristic Scheduler for Cloud Computing Environment

Abstract

Cloud computing is a different paradigm from traditional computing. It consists of providing IT services such as servers, storage, databases, network management, software, data analytics, artificial intelligence, etc., via the Internet (the Cloud) to provide faster innovation, flexible resources, productivity, and competitiveness. Several challenges in handling end-user applications need to be addressed more efficiently. Task Scheduling is a significant problem in Cloud computing since the cloud provider has to deal with many user applications. Consequently, task scheduling can no longer be handled by traditional schedulers. This paper's primary purpose is to propose a parallel multi-core hybrid heuristic scheduler based on exceeding the computing capacity of any processor while guaranteeing the results' accuracy. The main objective is to determine the feasible schedule that minimizes applications execution time while maximizing cloud resource utilization. Tests on benchmark instances showed that the proposed approach finds optimum/near-optimum solutions in many cases, while the computational times are minimal compared to other sequential techniques found in the literature