This report provides a comprehensive review of multiple research papers focused on various aspects of cloud computing. The papers address key issues such as dynamic multi-level auto-scaling for containerized applications, vertical elasticity of Docker containers, and cost-aware workflow scheduling in hybrid clouds. Other topics include containers orchestration with cost-efficient autoscaling, deadline-driven resource provisioning in hybrid clouds, coordination of vertical elasticity for containers and virtual machines, and resource provisioning-based scheduling frameworks for heterogeneous workloads. Furthermore, the review covers capacity-driven scaling schedules, elastic scheduling of scientific workflows, optimized hybrid service brokering, scheduling stochastic tasks on heterogeneous cloud platforms, elasticity in Docker Swarm, machine learning-based auto-scaling, dynamic multi-workflow scheduling, and cost-aware resource provisioning. The report also examines the impact of scheduling dynamic workloads and managing deadline-constrained bag-of-tasks jobs. The papers explore various methodologies, including qualitative and quantitative designs, literature reviews, and data analysis, to propose solutions and evaluate the performance of different approaches in cloud environments. These studies aim to enhance efficiency, reduce costs, and improve resource management within cloud computing systems.
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