33results about How to "Improve data forwarding efficiency" patented technology

A data forwarding method for realizing local area network virtual channel transmission, comprising the following steps: first judging whether a data packet arrives at an interface of a device, and checking the frame check code of the data packet, and secondly judging whether the type of the incoming data packet matches the type of the input interface , and check whether the "label forwarding information data table" clearly indicates the output interface of the data packet or the VLAN ID of the output data packet according to the input interface or input data packet, and the device completes according to the instructions of the "label forwarding information data table". When data packets are exchanged between any two interfaces of the device, the virtual local area network identification VLAN ID is exchanged according to the specified. The present invention breaks through the limitations of LAN networking caused by the lack of VLAN IDs stipulated by IEEE802.1Q, and realizes the end-to-end interconnection of large-scale VLANs at low cost without using new communication protocols under the existing relevant protocols of the LAN. , it can not only support centralized broadband LAN access, but also provide LAN VPN and PPPOE access services at the same time, and network operators do not need to increase the cost of learning new technologies.

The invention discloses a method for predicting the link quality of a wireless sensor network, which includes the following steps: S1, using a Kalman filter algorithm to reduce the noise of the link quality parameters, using the maximum and minimum method to standardize the link quality parameters, and using The fuzzy C-means clustering algorithm divides the link quality level; S2, uses the XGBoost algorithm to train the link quality prediction model, and predicts the link quality level at the next moment through the prediction model. Considering the dynamic change of wireless sensor network link quality, the present invention provides an XGBoost-based wireless sensor network link quality prediction method, which can effectively predict the link quality at the next moment, and can improve network throughput, thereby improving The data forwarding efficiency of the network is improved, and it provides a basis for the upper layer routing protocol to select the communication link. In addition, this method has the advantages of prolonging the life of the network and saving node energy.

The invention discloses a community-type opportunistic network data forwarding method. In the source node community, data packets are forwarded in a single-copy forwarding manner. By calculating the central utility value of the neighbor node, the data packet is sent to the neighbor node in which the central utility value is the largest. node, repeat this process until it is sent to the destination node. When the data packet is forwarded between communities, because the community where the destination node is located is unknown, it is impossible to know exactly which community it should be sent directly to, so the multi-copy forwarding method is used to increase the delivery rate, and the data packet is sent to the drop boxes of other communities , and query the node set N corresponding to the community a to find the destination node, and then forward the data packet to the destination node. The method of the invention is directly applied to the community opportunity network, so that the network transmission speed becomes faster and the message load becomes smaller.

The utility model relates to a method for data forward, which is suitable for the message transmission between STA. The method is characterized in comprising a forward table for recording the corresponding relationship of STA and AP is arranged on the AP; the source AP can search whether the AP corresponding to the target STA is existed in self forward table after receiving the message emitted tothe target STA by the source STA; if existed, the received message can be forwarded directly to the AP corresponding to the target STA for processing; if not existed, the received message can be forwarded to AC for processing. In addition, the utility model also provides an access point device. With the technical proposal, the utility model can lighten the AC processing burden and reduce the AC performance requirement.

The invention provides a PMIPv6 switching method based on a busy forward chain. By the adoption of the PMIPv6 switching method based on the busy forward chain, unnecessary signaling overheads can be avoided, rapid MN switching is guaranteed, and the mobile management performance of PMIPv6 can be optimized. The PMIPv6 switching method based on the busy forward chain comprises the following steps that (1) switching is triggered, wherein a switching triggering message is sent to a current MAG to which an MN has access; (2) a switching decision is made, wherein the switching decision is made by the current MAG according to the switching triggering message and a threshold K; (3) switching is executed, wherein the forward chain is lengthened by the current MAG to a target MAG if the MN is in the idle state and the length of the forward chain is smaller than the threshold K, rapid switching is initiated if the MN is in the idle state and the length of the forward chain is equal to or larger than the threshold or the MN is in the busy state, and the target MAG is informed that the forward chain is in a loop state by the current MAG through a PBU message when the forward chain is in the loop state, so that the target MAG directly executes caching and waits for MN access instead of conducting forwarding according to the forward chain when the target MAG receives an MN data packet.

A method for predicting the link quality of a wireless sensor network using GRU, the method comprising: obtaining a link quality parameter of the wireless sensor network at each moment within a period of time, and determining the link quality parameter of each moment according to the obtained link quality parameter Quality level; calculate the Pearson correlation coefficient between the historical link quality parameter before the current moment and the link quality parameter at the current moment; determine the quantity of the historical moment with the current moment Pearson correlation coefficient greater than the threshold value, and according to the The above quantity determines the size of the time window, and the link quality parameters are intercepted with the time window of the size to obtain the training sample set, and the training sample set with the link quality level label is applied to the GRU neural network model Training: using the trained GRU neural network model to predict the link quality of the wireless sensor. The invention can effectively and accurately predict the link quality at the next moment.