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.
Ziyu ShaoXin JinWenjie JiangMinghua ChenMung Chiang
Ephermika TariangNabajyoti Medhi
Lin WangFa ZhangAthanasios V. VasilakosChenying HouXiaogang Li
Renuga KanagaveluBu‐Sung LeeNguyen The Dat LeLuke Ng MingjieKhin Mi Mi Aung