  The containerized services allocated in the mobile edge clouds bring up the
opportunity for large-scale and real-time applications to have low latency
responses. Meanwhile, live container migration is introduced to support dynamic
resource management and users' mobility. However, with the expansion of network
topology scale and increasing migration requests, the current multiple
migration planning and scheduling algorithms of cloud data centers can not suit
large-scale scenarios in edge computing. The user mobility-induced live
migrations in edge computing require near real-time level scheduling.
Therefore, in this paper, through the Software-Defined Networking (SDN)
controller, the resource competitions among live migrations are modeled as a
dynamic resource dependency graph. We propose an iterative Maximal Independent
Set (MIS)-based multiple migration planning and scheduling algorithm. Using
real-world mobility traces of taxis and telecom base station coordinates, the
evaluation results indicate that our solution can efficiently schedule multiple
live container migrations in large-scale edge computing environments. It
improves the processing time by 3000 times compared with the state-of-the-art
migration planning algorithm in clouds while providing guaranteed migration
performance for time-critical migrations.
