[ISLPED] Temperature-aware Adaptive VM Allocation in Heterogeneous Dat…

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Young Geun Kim, Jeong In Kim, Seung Hun Choi, Seon Young Kim, and Sung Woo Chung, “Temperature-aware Adaptive VM Allocation in Heterogeneous Data Centers”, IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED 2019), Lausanne, Switzerland, July 2019.

 

 

 

 

Abstract

Virtualized data centers usually consist of heterogeneous servers which have different specifications (performance). Though there are usually a number of unused servers with different performance in such heterogeneous 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. When the temperature of a CPU core in a server exceeds a pre-defined thermal threshold, our proposed technique first identifies memory intensiveness and usage of VMs (Virtual Machines). Depending on the memory intensiveness and usage of VMs, our technique adaptively employs the following three methods: 1) a method that migrates a VM to another 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 up to 17.1% and saves system-wide EDP by up to 24.5%, compared to a conventional DVFS-based DTM technique, satisfying thermal constraints.

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