Project statement:

• Create a cloud environment with a number of servers, allowing users to submit their jobs, scale their jobs
• Make simple resource management solutions in determining where to place a VM and when to migrate them

Project steps

• Cloud environment setup
  • Set up the KVM environment
  • Provide an interface for job submission and scaling
• Middleware implementation
  • Explore libvirt to achieve VM creation, scaling, and migration
  • Study and summarize papers in VM placement
  • Design and develop a VM placement and migration decision algorithm
• System monitoring
  • Install one of the cloud monitoring system to observe various behaviors of the system
  • Continuously display memory load, CPU load, IO load, etc.
  • For individual VMs, individual nodes, etc.
  • Create the interface for the monitoring result display
  • Obtain cloud workloads, and perform cloud middleware management
• Analyze the results

Papers to refer:

• D. Ardagna, M. Trubian, and L. Zhang, “SLA based resource allocation policies in autonomic environments,” Journal of Parallel and Distributed Computing, vol. 67, pp. 259-270, 2007.
• J. Almeida, V. Almeida, D. Ardagna, Í. Cunha, C. Francalanci, and M. Trubian, “Joint admission control and resource allocation in virtualized servers,” Journal of Parallel and Distributed Computing, vol. 70, pp. 344-362, 2010.
• On Theory of VM Placement: Anomalies in Existing Methodologies and Their Mitigation Using a Novel Vector Based Approach
• On Resource Management for Cloud Users: A Generalized Kelly Mechanism Approach
• SLA-aware virtual resource management for cloud infrastructures
• VMware Distributed Resource Management: Design, Implementation, and Lessons Learned
• Q-Clouds: Managing Performance Interference Effects for QoS-Aware Clouds