Resource scheduling methods for cloud computing environment: The role of meta-heuristics and artificial intelligence

Abstract

The growth and development of scientific applications have demanded the creation of efficient resource management systems. Resource provisioning and scheduling are two core components of cloud resource management systems. Cloud resource scheduling is the most critical problem to solve efficiently due to the heterogeneity of resources, their inter-dependencies, and unpredictability of load in the cloud environment. In this paper, we review the background of scheduling and state-of-the-art scheduling techniques in cloud computing. We first introduce the general background, and phases of scheduling. A comprehensive survey of existing resource scheduling problems proposed so far is presented considering high-level taxonomy. This high-level taxonomy considers Virtual Machine (VM) placement, Quality of Service (QoS) parameters, heuristic methods, and other miscellaneous techniques for resource scheduling. This study also discusses scheduling in Infrastructure as a Service (IaaS) clouds and comparison based on important parameters is also investigated. The importance of meta-heuristic methods and artificial intelligence for resource scheduling methods in cloud computing is discussed thoroughly. The objective of this work is to help the researchers to understand the basic concepts related to scheduling and facilitate the process of designing new scheduling methods by addressing issues raised in the scheduling and studying the existing methodologies.