Issue No. 06 - June (2013 vol. 24)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPDS.2012.308
Hong Xu , University of Toronto, Toronto
Baochun Li , University of Toronto, Toronto
We present Anchor, a general resource management architecture that uses the stable matching framework to decouple policies from mechanisms when mapping virtual machines to physical servers. In Anchor, clients and operators are able to express a variety of distinct resource management policies as they deem fit, and these policies are captured as preferences in the stable matching framework. The highlight of Anchor is a new many-to-one stable matching theory that efficiently matches VMs with heterogeneous resource needs to servers, using both offline and online algorithms. Our theoretical analyses show the convergence and optimality of the algorithm. Our experiments with a prototype implementation on a 20-node server cluster, as well as large-scale simulations based on real-world workload traces, demonstrate that the architecture is able to realize a diverse set of policy objectives with good performance and practicality.
Resource management, Servers, Algorithm design and analysis, Cloud computing, Computer architecture, Educational institutions, Stability analysis, VM placement, Cloud computing, resource management, stable matching
H. Xu and B. Li, "Anchor: A Versatile and Efficient Framework for Resource Management in the Cloud," in IEEE Transactions on Parallel & Distributed Systems, vol. 24, no. , pp. 1066-1076, 2013.