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 multirooted 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. We empirically demonstrate the effectiveness of these algorithms through large scale simulations on real data.