Energy-Efficient Transaction Processing
Overview
Compared to early Transaction Processing (TP) systems, today’s TP systems have seen dramatic changes in both application requirements and underlying hardware support. As such, existing algorithms and design decisions hardly reflect reality and require revisiting them. However, more importantly, future generation TP systems must also necessarily evolve because of the emergence of energy efficiency as a first order design consideration.
This project is an early venture into a very new area, seeking to identify the most appropriate metrics for energy efficiency (QoE) in TP environments, the most appropriate ways to combine these energy efficiency metrics with existing quality of service (QoS) metrics and the most appropriate ways to specify any trade-off between QoE and QoS. Project plans also include the development of new scheduling algorithms and new TP system components that optimize a particular metric under different hardware configurations, as well as the experimental evaluation of the developed algorithms on simulation platforms and on real, state-of-the-art hardware.
This exploration has the potential to have a great impact in the development of new data management technologies. It is expected to advance the knowledge and understanding of the interplay among modern hardware components and facilitate the development of next generation TP systems that exploit new hardware features with the potential to achieve significant energy savings. This understanding could help formulate the foundations of the important area of energy-efficient data management, and thus contribute to the societal goal of energy conservation and sustainability.
People
Faculty:
- Panos K. Chrysanthis, Principal Investigator
- Alexandros Labrinidis, co-Principal Investigator
Collaborators:
- Shimin Chen CSD CMU (previously @ Intel Labs Pittsburgh)
Graduate Students:
- Sean Snyder
Undergraduate Students:
- Katlyn Daniluk (Summer Intern 2010)