Theory of linear and integer programming
Theory of linear and integer programming
An approximation algorithm for the generalized assignment problem
Mathematical Programming: Series A and B
An optimization problem in adaptive virtual environments
ACM SIGMETRICS Performance Evaluation Review - Special issue on the workshop on MAthematical performance Modeling And Analysis (MAMA 2005)
Live migration of virtual machines
NSDI'05 Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation - Volume 2
Multicommodity demand flow in a tree and packing integer programs
ACM Transactions on Algorithms (TALG)
SnowFlock: rapid virtual machine cloning for cloud computing
Proceedings of the 4th ACM European conference on Computer systems
Mathematics of Operations Research
VL2: a scalable and flexible data center network
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Black-box and gray-box strategies for virtual machine migration
NSDI'07 Proceedings of the 4th USENIX conference on Networked systems design & implementation
Strategies for Traffic-Aware VM Migration
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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Virtualization can deliver significant benefits for cloud computing by enabling VM migration to improve utilization, balance load and alleviate hotspots. While several mechanisms exist to migrate VMs, few efforts have focused on optimizing migration policies in a multi-rooted tree datacenter network. The general problem has multiple facets, two of which map to generalizations of well-studied problems: (1) Migration of VMs in a bandwidth-oversubscribed tree network generalizes the maximum multicommodity flow problem in a tree, and (2) Migrations must meet load constraints at the servers, mapping to variants of the matching problem --- generalized assignment and demand matching. While these problems have been individually studied, a new fundamental challenge is to simultaneously handle the packing constraints of server load and tree edge capacities. We give approximation algorithms for several versions of this problem, where the objective is to alleviate a maximal number of hot servers. In the full version of this work [5], we empirically demonstrate the effectiveness of these algorithms through large scale simulations on real data.