  For software-defined networking (SDN) systems, to enhance the scalability and
reliability of control plane, existing solutions adopt either multi-controller
design with static switch-controller associations, or static control devolution
by delegating certain request processing back to switches. Such solutions can
fall short in face of temporal variations of request traffics, incurring
considerable local computation costs on switches and their communication costs
to controllers. So far, it still remains an open problem to develop a joint
online scheme that conducts dynamic switch-controller association and dynamic
control devolution. In addition, the fundamental benefits of predictive
scheduling to SDN systems still remain unexplored. In this paper, we identify
the non-trivial trade-off in such a joint design and formulate a stochastic
network optimization problem that aims to minimize time-averaged total system
costs and ensure long-term queue stability. By exploiting the unique problem
structure, we devise a predictive online switch-controller association and
control devolution (POSCAD) scheme, which solves the problem through a series
of online distributed decision making. Theoretical analysis shows that without
prediction, POSCAD can achieve near-optimal total system costs with a tunable
trade-off for queue stability. With prediction, POSCAD can achieve even better
performance with shorter latencies. We conduct extensive simulations to
evaluate POSCAD. Notably, with mild-value of future information, POSCAD incurs
a significant reduction in request latencies, even when faced with prediction
errors.
