Abstract: A test method for a time-sensitive networking device, including steps of: sending a test request and a test goal; converting the test goal into test information; making a determination on a test scenario, wherein when the test scenario is a simulation test, a test indication signal is sent to a networking device under test, and when the test scenario is a field test, no test indication signal is sent; determining whether feedback information is received from the networking device under test within a test duration; in case of the reception, testing the feedback information and outputting a test result. A test system for a time-sensitive networking device, including a networking device testing apparatus, a user terminal and a plurality of networking devices under test. One terminal of the networking device testing apparatus is connected to the user terminal, and another terminal is connected to the plurality of networking devices under test.

Abstract: A method for task offloading based on power control and resource allocation in the Industrial Internet of Things includes establishing a computing model for computation tasks at different offloading locations, constructing communication power control, resource allocation and computation offloading problems as a mixed integer non-linear programming model, solving them using a deep reinforcement learning algorithm to obtain an optimal strategy for offloading of the computation tasks, thus achieving communication power optimization and cross-domain resource allocation.

Abstract: The present invention discloses a knowledge inference engine system and a method of implementation, relating to the field of wired communication networking technology. The system includes a data generation module, a stream partitioning model, an offline scheduling module, an online scheduling module, a scheduling solution base and a historical information base module, the data generation module used to generate a dataset and divide it into a plurality of partitions, the stream partitioning model used to partition the dataset, the offline scheduling module used to generate a scheduling solution for static network requirements, the online scheduling module used to rapidly generate a scheduling solution for a new TT stream, the scheduling solution base used to store a result of the partitioning, an iterative scheduling order for the partitions and the offline scheduling solution, the historical information base used to update and store relevant data information and performance indicators.

Abstract: A method for task offloading based on power control and resource allocation in the Industrial Internet of Things includes establishing a computing model for computation tasks at different offloading locations, constructing communication power control, resource allocation and computation offloading problems as a mixed integer non-linear programming model, solving them using a deep reinforcement learning algorithm to obtain an optimal strategy for offloading of the computation tasks, thus achieving communication power optimization and cross-domain resource allocation.