Joint VM placement and routing for data center traffic engineering

TLDR

Data centers require efficient traffic management, yet placement and routing are often optimized separately despite their mutual dependence. The study investigates a joint tenant (server or virtual machine) placement and routing problem to minimize traffic costs. We propose a Markov‑approximation‑based online algorithm that adapts to changing traffic loads with few VM migrations and is easy to implement. Evaluation on real data center traffic traces shows consistent, significant improvement over common heuristics.

Abstract

Today's data centers need efficient traffic management to improve resource utilization in their networks. In this work, we study a joint tenant (e.g., server or virtual machine) placement and routing problem to minimize traffic costs. These two complementary degrees of freedom—placement and routing—are mutually-dependent, however, are often optimized separately in today's data centers. Leveraging and expanding the technique of Markov approximation, we propose an efficient online algorithm in a dynamic environment under changing traffic loads. The algorithm requires a very small number of virtual machine migrations and is easy to implement in practice. Performance evaluation that employs the real data center traffic traces under a spectrum of elephant and mice flows, demonstrates a consistent and significant improvement over the benchmark achieved by common heuristics.