Virtualized data centers usually consist of heterogeneous servers which have different specifications (performance). Though there usually exist unused heterogeneous servers in such data centers, conventional DVFS (Dynamic Voltage and Frequency Scaling)-based DTM (Dynamic Thermal Management) techniques do not exploit the unused servers to cool down hot servers. In this paper, we propose a novel DTM technique which adaptively exploits external computing resources (unused servers with different performance) as well as internal computing resources (unused CPU cores in the server) available in heterogeneous data centers. Additionally, we also propose to consider locations of the servers when migrating VMs (Virtual Machines) among servers in a rack, which has a large impact on the on-chip temperatures and performance due to the heat conduction; when VMs run on the two closest servers in the rack, the ambient temperature of servers is up to 6.2° higher, compared to the case where VMs run on the two farthest servers, so that on-chip temperature more rapidly increases causing up to 13.5% of performance degradation due to more frequent thermal throttling. When the temperature of a CPU core in a server exceeds a pre-defined thermal threshold, our proposed technique estimates the impact of VM migrations on performance (e.g., performance degradation due to the physical machine migrations and/or core migrations of VMs). Depending on the estimated performance impact of VM migrations, our technique adaptively employs the following three methods: (1) a method that migrates a VM to another distant server with different performance, (2) a method that migrates VMs among CPU cores in the server, and (3) a DVFS-based method. In our experiments, our proposed technique improves performance by 15.1% and saves system-wide EDP by 22.9%, on average, compared to a state-of-the-art DVFS-based DTM technique, satisfying thermal constraints.

虚拟数据中心通常由具有不同规格（性能）的异构服务器组成。尽管在此类数据中心中通常存在未使用的异构服务器，但是基于常规DVFS（动态电压和频率缩放）的DTM（动态热管理）技术不会利用未使用的服务器来冷却热服务器。在本文中，我们提出了一种新颖的DTM技术，该技术可自适应地利用异构数据中心中可用的外部计算资源（具有不同性能的未使用服务器）以及内部计算资源（服务器中未使用的CPU内核）。此外，我们还建议在机架中的服务器之间迁移VM（虚拟机）时考虑服务器的位置，这会由于热传导而对片上温度和性能产生很大影响；当虚拟机在机架中最接近的两个服务器上运行时，与虚拟机在最远的两个服务器上运行的情况相比，服务器的环境温度最高高6.2°，因此片上温度会更快地升高，导致温度高达13.5由于更频繁的热调节而导致性能下降的百分比。当服务器中CPU核心的温度超过预定义的热阈值时，我们提出的技术将估算VM迁移对性能的影响（例如，由于物理机迁移和/或VM的内核迁移而导致的性能下降）。根据VM迁移对性能的估计影响，我们的技术自适应地采用以下三种方法：（1）一种将VM迁移到具有不同性能的另一台远程服务器的方法，（2）一种在服务器中CPU核心之间迁移VM的方法。 ，（3）基于DVFS的方法。在我们的实验中，与最新的基于DVFS的DTM技术相比，我们提出的技术与传统的满足热约束的技术相比，性能提高了15.1％，平均节省了系统范围的EDP 22.9％。