Prof. Yuan Zhong
Columbia University
Talk:
Stochastic dynamic bin packing with applications to cloud computing
Abstract:
We present a new class of bin packing models, so-called large-scale stochastic dynamic bin packing, which are primarily motivated by the problem of virtual machine placement into physical servers in cloud computing clusters. A key performance objective is to minimize the total number of occupied servers. In this talk, we describe several placement policies and establish their performance and scalability properties. In particular, we propose Greedy-Random (GRAND), a class of extremely simple policies, and show that a version of GRAND is asymptotically optimal, as the system scale goes to infinity. We then complement the theoretical results with simulation studies, and conclude with some open problems. This talk is based on joint works with Sasha Stolyar of Lehigh University.
