- Forecasting for Cloud computing on-demand resources based on pattern matching
- Auto-scaling Techniques for Elastic Applications in Cloud Environments
- Auto-Scaling Model for Cloud Computing System
- Rebalancing in a Multi-Cloud Environment
- Infrastructure Outsourcing in Multi-Cloud Environment
- Workload Classification for Efficient Auto-Scaling of Cloud Resources
- Dynamically Scaling Applications in the Cloud
- Optimal Autoscaling in the IaaS Cloud
- Dynamic Resource Provisioning for Deadline and Budget Constrained Application in Cloud Environment
- AutoScale: Dynamic, Robust Capacity Management for Multi-Tier Data Centers
- DEPAS: A Decentralized Probabilistic Algorithm for Auto-Scaling
- Efficient Autoscaling in the Cloud using Predictive Models for Workload Forecasting
- Agile, Dynamic Provisioning of Multi-tier Internet Applications
- A Profile-Based Approach to Just-in-Time Scalability for Cloud Applications
- Approximation Modeling for the Online Performance Management of Distributed Computing Systems
- Virtual Machine Placement in Cloud Environments
- Dynamic placement of virtual machines for cost optimization in multi-cloud environments
- Auto-scaling to minimize cost and meet application deadlines in cloud workflows
- Managing a SaaS Application in the Cloud Using PaaS Policy Sets and a Strategy-Tree
- CloudScale: Elastic Resource Scaling for Multi-Tenant Cloud Systems
- An extreme automation framework for scaling cloud applications
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