公开(公告)号：US11431632B1

公开(公告)日：2022-08-30

申请号：US17739173

申请日：2022-05-09

Applicant: Zhejiang Lab

Inventor： Qi Xu ,  Hanguang Luo ,  Tao Zou ,  Ruyun Zhang ,  Geyang Xiao ,  Wanxin Gao ,  Huifeng Zhang ,  Congqi Shen

IPC: H04L45/745 ,  H04L45/50 ,  H04L45/00

Abstract: The present invention relates to the technical field of computer networking, in particular to an ID/location hybrid forwarding method based on source routing, including a message format based on an extension header of a MobilityFirst protocol, a source routing forwarding mechanism based on ID identifiers and a source routing forwarding mechanism based on location identifiers. Through the method of the present invention, the source routing forwarding mechanism based on ID identifiers can be adopted in the access domains of the MobilityFirst network to realize the internetworking of intra-domain networks, and the source routing forwarding mechanism based on location identifiers in the core domain realizes the interconnection of inter-domain networks; the method greatly simplifies the processing flow of the data plane of the MobilityFirst network, and meanwhile reserves the design that the ID identifiers and the location identifiers are separated, thereby effectively supporting intra-domain and inter-domain mobile data forwarding.

公开(公告)号：US12056533B2

公开(公告)日：2024-08-06

申请号：US18354601

申请日：2023-07-18

Applicant: ZHEJIANG LAB

Inventor： Huifeng Zhang ,  Congqi Shen ,  Tao Zou ,  Jun Zhu ,  Ruyun Zhang ,  Qi Xu ,  Hanguang Luo ,  Xingchang Guo

IPC: G06F9/46 ,  G06F9/50 ,  G06N20/00

CPC classification number: G06F9/5038 ,  G06N20/00

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.

公开(公告)号：US12015548B2

公开(公告)日：2024-06-18

申请号：US18542823

申请日：2023-12-18

Applicant: ZHEJIANG LAB

Inventor： Congqi Shen ,  Huifeng Zhang ,  Tao Zou ,  Ruyun Zhang

IPC: H04L45/00 ,  H04L45/74 ,  H04L69/22

CPC classification number: H04L45/38 ,  H04L45/74 ,  H04L69/22

Abstract: A method and a device for identification management and optimized forwarding in a large-scale polymorphic network, the method comprising the follow steps: S1, constructing a polymorphic backbone network; S2, modality identification management; S3, determining a modality to be forwarded; S4, configuring a flow table for a switching node; S5, receiving a packet by a balanced distributor, and preliminarily parsing the type of the packet; S6, parsing key field information in the packet, determining the switching nodes to be allocated according to the key field information, and transmitting the key field information to the corresponding switching node; S7, the switching node matching the stored flow table according to the key field information to determine a correct forwarding action.

公开(公告)号：US11979295B2

公开(公告)日：2024-05-07

申请号：US18359862

申请日：2023-07-26

Applicant: ZHEJIANG LAB

Inventor： Congqi Shen ,  Huifeng Zhang ,  Shaofeng Yao ,  Qi Xu ,  Ruyun Zhang

IPC: H04L41/16 ,  G06N20/00 ,  H04L41/40

CPC classification number: H04L41/16 ,  G06N20/00 ,  H04L41/40

Abstract: The present disclosure discloses a reinforcement learning agent training method, modal bandwidth resource scheduling method and apparatus. The reinforcement learning agent training method utilizes a reinforcement learning agent to continuously interact with a network environment in a polymorphic smart network to obtain the latest global network characteristics and output updated actions. By adjusting the bandwidth occupied by modals, a reward value is set to determine an optimization target for the agent, the scheduling of modals is realized, and the rational use of polymorphic smart network resources is guaranteed. The trained reinforcement learning agent is applied to the modal bandwidth resource scheduling method, and can adapt to networks with different characteristics, and thus can be used for intelligent management and control of polymorphic smart networks and has good adaptability and scheduling performance.

公开(公告)号：US11870560B2

公开(公告)日：2024-01-09

申请号：US17966917

申请日：2022-10-17

Applicant: ZHEJIANG LAB

Inventor： Congqi Shen ,  Shaofeng Yao ,  Zhongxia Pan ,  Hanguang Luo ,  Tao Zou

IPC: H04L45/00 ,  H04L45/76 ,  H04L45/745

CPC classification number: H04L45/76 ,  H04L45/54 ,  H04L45/745

Abstract: A geographical identification forwarding method for area-oriented addressing. The geographic location information is used as a transmission identification, and the communication process based on the geographical identification is realized by constructing the SDN-based geographical identification transmission architecture. In this method, a geographical identification is used instead of a traditional IP identification for network transmission, which effectively alleviates the problem of narrow waist of IP single bearing in the current network. At the same time, through a flow table decomposition design, the flow table size of the switch is effectively controlled. The method provided by the present invention can be extended to a plurality of geographical identification areas to realize large-area real-time cross-domain transmission. The method is simple to operate, easy to realize and high in real-time; the method has a wide application range, and can be used to build new networks and improve network performance.