To improve the performance of Ad hoc on-demand multipath distance vector (AOMDV) protocol, we proposed NS-AOMDV which is short for "AOMDV based on node state". In NS-AOMDV, we introduce node state to improve AOMDV's performance in selecting main path. In route discovery process, the routing update rule calculates the node weight of each path and sorts the path weight by descending value in route list, and we choose the path which has the largest path weight for data transmission. NS-AOMDV also uses the technology of route request (RREQ) packet delay forwarding and energy threshold to ease network congestion, limit the RREQ broadcast storm, and avoid low energy nodes to participate in the establishment of the path. The results of simulation show that NS-AOMDV can effectively improve the networks' packets delivery rate, through put and normalized routing overhead in the situation of dynamic network topology and heavy load.

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A method for optimal control of cylindrical plunge grinding cycles is introduced. Unlike conventional cycles which have a few pre-determined sequential steps with discrete infeed rates, the new method will continually vary the infeed velocity. The proposed method utilizes the Model Predictive Control (MPC) approach whereby the control action at each sampling instant is selected in accordance with its effect on the future values of process variables and part quality attributes. This paper describes the problem and presents some preliminary results. It also discusses the difficulties that will need to be overcome before the controller can be implemented on-line.