  Mobile-edge computing (MEC) enhances the capacities and features of mobile
devices by offloading computation-intensive tasks over wireless networks to
edge servers. One challenge faced by the deployment of MEC in cellular networks
is to support user mobility. As a result, offloaded tasks can be seamlessly
migrated between base stations (BSs) without compromising the
resource-utilization efficiency and link reliability. In this paper, we tackle
the challenge by optimizing the policy for migration/handover between BSs by
jointly managing computation-and-radio resources. The objectives are twofold:
maximizing the sum offloading rate, quantifying MEC throughput, and minimizing
the migration cost. The policy design is formulated as a decision-optimization
problem that accounts for virtualization, I/O interference between virtual
machines (VMs), and wireless multi-access. To solve the complex combinatorial
problem, we develop an efficient relaxation-and-rounding based solution
approach. The approach relies on an optimal iterative algorithm for solving the
integer-relaxed problem and a novel integer-recovery design. The latter
outperforms the traditional rounding method by exploiting the derived problem
properties and applying matching theory. In addition, we also consider the
design for a special case of "hotspot mitigation", referring to alleviating an
overloaded server/BS by migrating its load to the nearby idle servers/BSs. From
simulation results, we observed close-to-optimal performance of the proposed
migration policies under various settings. This demonstrates their efficiency
in computation-and-radio resource management for joint service migration and BS
handover in multi-cell MEC networks.
