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Due to the limited node degree and fragile links, design and management of free space optical (FSO) networks is still a great challenge. In this paper, based on a tiered mobile FSO network model, a localized Delaunay triangulation (LDT) algorithm for the topology control of the upper tier is proposed. Then we study how the lower tier is supported by the upper tier. An effective dynamic multipoint-to-point access (DMPPA) method is presented, which can "enlarge" the access degree without sacrificing the connectivity of the upper tier. Meanwhile, a mutual "help" strategy is proposed to balance the residual energy of the cluster heads and improve the node distribution uniformity. Simulation results show that the LDT algorithm can produce a high-connectivity topology and satisfy node degree constraints and that the DMPPA method and the "help" strategy can ensure the network quality of service and extend the survival time of the whole FSO network.

With the rapid development of machinery industry, the processing parameters which affect on the quality of the products in machining and measuring index also appeared diversified, which makes the study of multi-objective optimization problem is very important. Among the many factors, cutting consumption plays a key role in many indicators, in effect, cutting force and cutting temperature on the quality and performance of products is the most prominent, so this paper takes PCBN tool cutting Cr12MoV steel as the experimental basis, the cutting parameters to optimize the parameters;the cutting force and cutting temperature as the index;with the aid of the BP neural network modeling of cutting force and cutting temperature, at the same time, this paper improved particle swarm optimization algorithm to achieve multiple objectives, provides multi objective optimization parameters more reliable for die steel production process.