Task Scheduling in Cloud Environment–Techniques, Applications, and Tools: A Systematic Literature Review

Abstract

Cloud computing has become a revolutionary model for providing computational resources and services via the internet. As the volume of tasks and the dynamic nature of cloud resources increase, several critical challenges emerge, including load balancing, resource utilization, task allocation, and system performance. Ineffective scheduling leads to issues such as resource imbalance (either overuse or underuse) resulting in service degradation or resource wastage. The primary goal of this study is to review and analyze the challenges related to task allocation among limited cloud resources, focusing on factors like resource utilization, reliability, makespan time, cost, energy consumption, availability, response time, and other key performance metrics. The paper offers a systematic literature review of task scheduling in cloud computing, introducing a novel classification taxonomy and a comparative review of various techniques. This taxonomy categorizes metaheuristic scheduling techniques based on scheduling algorithms, problem nature, task types, primary scheduling objectives, task-resource mapping, scheduling constraints, and testing environments. This study provides a thorough assessment, classification, and analysis of different scheduling systems, discussing their advantages and limitations. It also outlines future research directions to support current researchers and practitioners.

Keywords

• Cloud computing
• task scheduling
• heuristic technique
• meta-heuristic technique
• hybrid technique
• makespan