Communication-driven scheduling for virtual clusters in cloud

Abstract

Due to high flexibility and cost-effectiveness, cloud computing is increasingly being explored as an alternative to local clusters by academic and commercial users. Recent research already confirmed the feasibility of running tightly-coupled parallel applications with virtual clusters. However, such types of applications suffer from significant performance degradation, especially as the overcommitment is common in cloud. That is, the number of executable Virtual CPUs (VCPUs) is often larger than that of available Physical CPUs (PCPUs) in the system. The performance degradation mainly results from that the current Virtual Machine Monitors (VMMs) cannot co-schedule (or coordinate at the same time) the VCPUs that host parallel application threads/processes with synchronization requirements. We introduce a communication-driven scheduling approach for virtual clusters in this paper, which can effectively mitigate the performance degradation of tightly-coupled parallel applications running atop them in overcommitted situation. There are two key contributions. 1) We propose a communication-driven VM scheduling (CVS) algorithm, by which the involved VMM schedulers can autonomously schedule suitable VMs at runtime. 2) We integrate the CVS algorithm into Xen VMM scheduler, and rigorously implement a prototype. We evaluate our design on a real cluster environment, and experiments show that our solution attains better performance for tightly-coupled parallel applications than the state-of-the-art approaches like Credit scheduler of Xen, balance scheduling, and hybrid scheduling.