HBP: an optimization technique to shorten the control cycle time of the Neural Network Controller that provides dynamic buffer tuning to eliminate overflow at user level
The NNC (Neutral Network Controller) automatically tunes the buffer size at the user/server level to eliminate any chance of overflow in the client/server interaction over a TCP logical channel. Together with the buffer tuning operations it the system/router level (e.g. the AQM (Active Queue Management) activities) they form a unified Solution. The power and stability of the NNC was verified Over the Internet, but the result shows that the drawback of the NNC is its long control cycle time. This drawback hinders the deployment of the NNC in the real-time, applications. To overcome this we propose the novel HBP (Hessian Based Pruning) optimization technique. This technique Operates as a renewal process, and within the service life of the Optimized NNC (O-NNC) the optimization operation repeats as renewal cycles. The feed-forward neutral network configuration of the O-NNC is optimized in every cycle that involves two phases. In its original un-optimized form the NNC rolls as a twill system, of two modules: "Chief + Learner". The O-NNC always starts with the unoptimized configuration. In the first phase the weights for the Learner's neutral network arcs are computed and sorted. Those arcs with weights insignificant to the control convergence speed and precision are marked. The marking is based on "dynamic sensitivity analysis" that utilizes the HBP technique in the second phase the Chief optimizes the neutral network by excluding/skipping the marked arcs. The aim is to shorten the computation for the control cycle. The "HBP+NNC" is the basis of the O-NNC model, which essentially uses virtual pruning because the marked arcs are excluded from the computation but not physically removed. While the Chief is carrying out actual dynamic buffer tuning the Learner undergoes training. The O-NNC model is verified by running the lava-based prototype on the Aglets mobile agent agent platform in the Internet environment. The results are positive and indicate that the HBP technique indeed yields a shorter O-NNC control cycle time than the original un-optimized NNC in a consistent manner.
hbp optimization pruning o-nnc taylor series buffer overflow control