Overview
Topic status: We're looking for students to study this topic.
Project Summary
The energy efficiency of cloud computing is determined by not only the energy efficiency of the hardware used in cloud computing, but also by the placement of SaaS applications in cloud computing. In cloud computing, a SaaS application is usually composed of several software components that may be deployed on different servers. The energy consumption of a server depends on the utilization rates of the CPU, main memory, I/O devices, and so on, and therefore different SaaS placements may result in different energy consumptions on the servers in cloud computing. Thus, SaaS placement directly affects the energy consumption in cloud computing. This project is to implement and evaluate a genetic algorithm for QoS-aware and energy-efficient SaaS placement.
Duration: starting 19th November 2012 (3 days/week)
Expected outcomes, applications and/or benefits
1. A software tool for QoS-aware and energy-efficient SaaS placement
Required student skills/experience
1. Sound knowledge in data structures and algorithms;
2. Competitive programming skills in C#.
- Study level
- Vacation research experience scholarship
- Supervisors
- QUT
- Organisational unit
Science and Engineering Faculty
- Research area
- Contact
- Contact the supervisor for more information.
Dr Maolin Tang
