Abstract: A method, an apparatus and a medium for optimizing allocation of switching resources in the polymorphic network. The method selects the ASIC switching chip, FPGA and PPK software switching on the polymorphic network element based on machine learning, and specifically comprises the following steps: manually pre-configuring, formulating basic rules for polymorphic software and hardware co-processing; offline learning, designing training configuration in the offline learning stage to capture different switching resource usage variables, running experiments to generate the original data of a training classifier, and using the generated performance indices to train the model offline; and online reasoning, obtaining switching resource allocation advises, and updating modality codes according to the switching resource allocation advises.

Abstract: A content store-and-forward method, apparatus, an electronic apparatus and a storage medium, the method comprising the following steps: receiving an interest packet in a named data network; forwarding the interest packet to a storage node, so that the storage node looks up the corresponding content, and packages the content into a data packet containing the hash value of the name identifier and the corresponding content; receiving the data packet forwarded by the storage node; forwarding the data packet to an interest packet port, wherein the interest packet port is a port that has once received the name identifier corresponding to the content in the data packet; forwarding another data packet to the storage node, so that the storage node parses the hash value and the content of the name identifier in the another data packet, and stores the hash value of the name identifier and the corresponding content.