  Service-oriented virtual network deployment is based on statistical resource
demands of different services, while data traffic from each service fluctuates
over time. In this paper, a delay-aware flow migration problem for embedded
services is studied to meet end-to-end (E2E) delay requirement with
time-varying traffic. A non-convex multi-objective mixed integer optimization
problem is formulated, addressing the trade-off between maximum load balancing
and minimum reconfiguration overhead due to flow migrations, under processing
and transmission resource constraints and QoS requirement constraints. Since
the original problem is non-solvable in optimization solvers due to unsupported
types of quadratic constraints, it is transformed to a tractable mixed integer
quadratically constrained programming (MIQCP) problem. The optimality gap
between the two problems is proved to be zero, so we can obtain the optimum of
the original problem through solving the MIQCP problem with some
post-processing. Numerical results are presented to demonstrate the
aforementioned trade-off, as well as the benefit from flow migration in terms
of E2E delay performance guarantee.
