Energy analysis and optimization for distributed data centers under electrical load shedding

The number and scales of data centers have significantly increased in the current digital world. The distributed data centers are standing out as a promising solution due to the development of modern applications which need a massive amount of computation resources and strict response requirements. Their reliability and availability heavily depend on the electrical power supply. Most of the data centers are equipped with battery groups as backup power in case of electrical load shedding or power outage due to severe weather or human-driven factors. The limited numbers and degradation of batteries, however, can hardly support the servers to finish all the jobs on time. In this thesis, we divide all the workload in data centers into web jobs and batch jobs. We develop a battery allocation and workload migration framework to guarantee web jobs are never interrupted and try to minimize the waiting time of batch jobs simultaneously. Our extensive evaluations show that our battery allocation and workload migration results can guarantee all the web jobs uninterrupted and minimize the average waiting time of batch jobs within a limited overall cost compared to the current practical allocation.