The Journey of QoS-Aware Autonomic Cloud Computing

Abstract

In a cloud environment, uncertainty and resource dispersion lead to problems with resource allocation due, for instance, to heterogeneity, dynamism, and failures. Unfortunately, existing resource management techniques, frameworks, and mechanisms are insufficient to handle these environments, applications, and resource behaviors. To provide efficient workload performance and applications, these issues must be addressed effectively. The authors offer a broad, methodical literature analysis of resource management in cloud computing, including resource provisioning, resource scheduling, and autonomic resource provisioning and scheduling. They describe the current status of resource management in cloud computing and provide further analysis of its techniques as developed by various industry and academic groups. They also look at possible future directions for resource management in cloud computing.