Deep packet inspection (DPI) is a key technology in software defined network (SDN) which can centralize network policy control and accelerate packet transmission. In this paper, we propose a new SDN architecture with DPI module. Base on the centralization idea of SDN, we deploying a parallel DPI to the control layer. We present DPI interface in the SDN controller and discuss OpenFlow protocol extension. Paralleling the DPI algorithm effectively reduces the time of detecting packets and sending flow tables. We also describe an Adaptive Highest Random Weight with an additional feedback corresponding to queue length and string length matching at each processor. The original Highest Random Weight (HRW) hash ensures the connection locality. Treating all tasks as the same weight just balances the workload over the number of different task. By adding the adjustment multiplier and combined with the characteristics of the fixed hash function, the system can allocate resource dynamically and achieve connection-level parallelism in consideration of the processing time for per packet.

A computer-assisted minimally invasive cochlear implant system is developed to help doctors perform minimally invasive cochlear implant to avoid disadvantages of traditional complex operation like large invasive and long time to recovery et al. Virtual space visualization, space mapping and operation path plan, mechanism for drill positioning and holding are realized with multi-use of computer navigation and virtual space visualization technology and screw theory. Totally 6 cadaveric skull specimen experiments are performed. In experiments, all cochleae are opened perfectly without facial nerves damaged. The results demonstrate that the computer-assisted minimally invasive cochlear implant system can meet the clinical operation demands.