Thermal-aware task scheduling to minimize energy usage of blade server based datacenters

Blade severs are being increasingly deployed in modern datacenters due to their high performance/cost ratio and compact size. In this study, we document our work on blade server based datacenter thermal management. Our goal is to minimize the total energy costs (usage) of datacenter operation while providing a reasonable thermal environment for their reliable operation. Due to special characteristics of blade servers, we argue that previously proposed power-oriented schemes are ineffective for blade server-based datacenters and that task-oriented scheduling is a more practicable approach since the contribution to the total energy cost from cooling and computing systems vary according to the utilization rates. CFD simulations are used to evaluate scheduling results of three different task scheduling algorithms: Uniform Outlet Profile (UOP), Minimal Computing Energy (MCE), and Uniform Task (UT), under four different blade-server energy consumption models: DiscreteNonOptimal (DNO), DiscreteOptimal (DO), AnalogNonOptimal (ANO), and AnalogOptimal (AO). Simulation results show that the MCE algorithm, in most cases, results in a minimal total energy cost - a conclusion that differs from the findings of previous research. UOP performs better than UT at low datacenter utilization rates, whereas UT outperforms UOP at high utilization rates.