4 results about "Queuing network" patented technology

The invention discloses an unmanned aerial vehicle complex airspace cooperative passage method based on a graph neural network, and the method comprises the steps: collecting the airspace data of an unmanned aerial vehicle complex airspace, and generating standardized airspace data; constructing a mixed queuing network, and forming arrival, queue length and service capability state of each service node and service link; mapping to obtain graph nodes, graph edges and graph features, and constructing an airspace graph; inputting the airspace graph into the graph neural network, and carrying out constraint updating on the mixed queuing network; integrating the service capability state, the queue length state and the congestion propagation parameters to form a network passing cost relationship; and executing a Frank-Wolfe algorithm, and generating a cooperative passing instruction for each unmanned aerial vehicle. According to the invention, by introducing the mixed queuing network and the Frank-Wolfe algorithm, efficient and stable cooperative passage scheduling of multiple unmanned aerial vehicles in a complex airspace environment is realized.

The invention provides a performance evaluation method of a four-way shuttle robot system based on path optimization, which comprises the following steps of: modeling path nodes in a two-dimensional coordinate system, and on the basis of considering the motion characteristics of acceleration, deceleration and the like during operation of a shuttle robot, obtaining a path with shortest operation time of the shuttle robot by improving a Dijkstra algorithm; on the basis, a semi-open-loop queuing network model considering path optimization is constructed, and system performance indexes including a task period, an equipment utilization rate and throughput are solved by adopting an AMVA algorithm. Simulation verification shows that the method is high in calculation precision and excellent in efficiency; sensitivity analysis further reveals an influence rule of structural parameters such as the number of roadways, the number of columns and the number of layers on system performance, and indicates that when the roadways are close to the number of columns and the number of layers is adaptive to the total quantity of goods positions, the throughput capacity of the system is optimal, and a quantitative basis is provided for storage system configuration.

The invention discloses a collaborative environment-oriented service deployment and request scheduling optimization method and device, and relates to the technical field of edge-cloud collaborative mobile edge computing in the power industry, and the method comprises the steps: constructing a multi-instance queuing network model and a multi-dimensional hierarchical soft actor-commentator algorithm; based on the multi-instance queuing network model, modeling a multi-instance execution relationship in a power station task processing process, and providing a performance evaluation basis for a request scheduling strategy by quantifying task transmission delay, queuing delay and calculation delay; and based on the multi-dimensional hierarchical soft actor-commentator algorithm and in combination with the current state of the power information system, determining the deployment number and distribution position of each micro-service instance, and formulating a request scheduling strategy. According to the method, the dependency relationship and the multiplexing characteristic between the micro-services are fully considered, the request response delay can be effectively reduced, the network load and the system energy consumption can be balanced, and the service quality and the resource utilization efficiency of the electric power station are improved.

This invention provides a parallel I / O write consistency guarantee method based on state preheating, belonging to the field of computer technology. This invention collects the I / O operation timestamp sequence of MPI processes and the inter-process communication topology, and uses a risk assessment model fused with temporal causal convolution and graph attention to output risk scores for each variable's write operation. It then uses an adaptive preheating timing estimation algorithm based on a queuing network to calculate the expected completion time variance of the I / O path, determining whether to trigger the preheating process. Finally, it uses a preheating intensity adjustment function to fuse the risk scores, MPI process size, and historical write success rate, triggering policy upgrades and retrying when deviations are detected. The execution results are updated with reinforcement learning reward signals to update the parameters of the artificial intelligence model and the weights of the policy decision model, achieving closed-loop adaptive adjustment. This solves the technical problem that parallel I / O write consistency guarantee mechanisms cannot adaptively adjust the synchronization strategy strength according to the real-time system load status and the risk of abnormal propagation between processes.