2538 results about "Goodput" patented technology

The invention provides a data management method, device and equipment and a readable storage medium, and the method comprises the steps: obtaining key value cache data generated by a first type of computing power unit in a pre-filling stage, transmitting the key value cache data to a memory pool, and caching the key value cache data in the memory pool; and in response to a data acquisition demand of the second type of computing power unit in a decoding stage, transmitting the specified key value cache data cached in the memory pool to the second type of computing power unit according to the data acquisition demand. According to the technical scheme of the invention, the memory pool is arranged and the aggregated transmission channel is utilized, so that the transmission efficiency of the key value cache data between the computing power devices is effectively improved, the data transmission delay is reduced, and the network transmission protocol overhead is reduced, thereby improving the data interaction efficiency of the computing power devices in a pre-filling stage and a decoding stage, and improving the user experience. The utilization of computing power resources is optimized, and the throughput and performance of large model reasoning are improved.

The invention relates to the technical field of software defined networks, in particular to an SRv6-based SDN (Software Defined Network) data center load balancing method and system, and the method comprises the steps: obtaining node real-time load and SRv6 routing available resource information through an SDN controller, constructing a load balancing model, and recognizing an overload node and a congestion link; generating a flow scheduling path in combination with segmented routing characteristics; in combination with network state information, monitoring the load condition in real time when the node is unbalanced or the link packet loss rate is gt; when 5%, a load balancing adjustment mechanism is triggered, unbalance types are distinguished, a related flow set is determined, optimization is performed by using a DQN algorithm, and a flow scheduling strategy is generated and dynamically adjusted by taking throughput maximization and unbalance degree minimization as targets; and issuing the scheduling strategy to the data center network equipment, updating the flow table through the Netconf protocol, and redistributing the flow. Therefore, the problems of low load balancing efficiency, insufficient dynamic adaptability, low resource utilization rate and the like in the prior art are solved.

The invention discloses a high-dynamic mobile ad hoc network dynamic time slot allocation method and device, equipment and a storage medium, and belongs to the technical field of wireless communication and networks. The device is deployed between an upper-layer application module and a bottom-layer communication module of a communication node, and comprises a topology sensing module, a time frame construction module, an idle time slot distribution module, a GNSS module and an information interaction module. According to the method, neighbor nodes are determined among nodes through interaction information, and node topology change indexes and link states are calculated; the coordination node performs idle time slot allocation according to a request sent by the node in the control time slot, and dynamically adjusts a sensing period according to the current network topology change; and the node sends data in the information time slot according to the time slot allocation table, and carries out information interaction and topology perception according to the perception period. According to the method, the packet loss rate in the link unstable environment is effectively reduced, the data transmission reliability is higher, the method can adapt to link and topology dynamic changes, and the network throughput and the resource utilization rate are improved.

A method, a network device, and a non-transitory computer-readable storage medium are described in relation to an LAS service. The LAS service may include enablement or disablement of the LA service subsequent to an establishment and active traffic flow associated with an application session. The LAS service may be enabled or disabled based on performance metric criteria and threshold values not being satisfied or being satisfied. The LAS service may be implemented to include an exposure function.

The invention relates to the technical field of network management, in particular to an Internet of Things gateway control method and system based on AI computing power, and the method comprises the following steps: obtaining channel real-time signal intensity, noise level and occupancy proportion, monitoring protocol type and transmission condition, analyzing the relationship between retransmission times and interference, deducing protocol combination interference and throughput, and obtaining a real-time channel signal intensity, noise level and occupancy proportion. And configuring an optimal scheduling scheme, evaluating resource consumption and load states, packaging and requesting permission entrustment, and judging permission information in combination with an interaction record and an access control list. According to the method, different protocol distribution combinations are simulated and deduced, the data throughput of the whole network is further estimated and optimized, potential protocol conflicts are reduced, the use efficiency and the overall performance of network resources are effectively improved, consumption of a local computing unit and network bandwidth is comprehensively considered, packaging processing of request information is optimized, and the network performance is improved. And the real-time response capability and manageability of the network state are obviously improved.

The invention discloses a self-adaptive modulation method and device for a power line carrier communication system, and the method comprises the following steps: S1, obtaining the channel information of the power line carrier communication system, and calculating the signal-to-noise ratio of each data subcarrier; and S2, based on a preset mapping relationship between different data subcarrier signal-to-noise ratios and corresponding modulation modes, according to the signal-to-noise ratio of each data subcarrier calculated in the step S1, adaptively allocating a corresponding modulation mode to each data subcarrier for modulation. According to the channel information of the power line carrier communication system, under the condition that the constraint of the target bit error rate is met, a proper modulation mode can be adaptively selected for each data subcarrier, and the system throughput is improved while the communication reliability is ensured.

The invention discloses a P4 switch processor core-oriented multi-service traffic packet scheduling method, which mainly comprises the following steps of: proposing a feature extraction method based on a statistical interval and Sketch, integrating data packet time correlation and traffic dynamic change, optimizing a Bloom filter conflict detection mechanism, and improving the adaptability and accuracy of an algorithm in a limited resource environment; a decision tree model is combined with scheduling, a decision tree is reconstructed to adapt to an operation mode and a data processing requirement of a P4 switch, and high-precision service flow classification under linear speed operation is ensured; a packet scheduling method AD-PIFO is designed based on a variable priority, the forwarding priority of a data packet is dynamically adjusted, the QoS requirements of different services are met, and the overall performance and efficiency of the switch are improved. The method is outstanding in high-priority traffic throughput and low-delay performance, is superior to similar algorithms in medium-low priority traffic throughput, is stable and effective under different load conditions, is reasonable in extra time overhead of data packet transmission, and is widely applied to SDN network optimization data packet scheduling scenes.

The present disclosure provides connection management techniques based on graph neural networks (GNN) and deep reinforcement learning (DRL) to optimize user association and load balancing. A graph structure of a communication network is considered for the GNN architecture and DRL is used to learn parameters of the GNN algorithm / model. Connection management is defined as a combinatorial graph optimization problem, and the DRL mechanism uses the underlying graph to learn weights of the GNN for an optimal user connections or associations. The connection management techniques can consider local network features to make better decisions to balance network traffic load while network throughput is also maximized. Implementations are provided based on edge computing frameworks include the Open RAN (O-RAN) architecture. Other embodiments may be described and / or claimed.

The invention belongs to the field of unmanned aerial vehicle communication, and discloses a flight ad hoc network distributed routing method based on multi-agent reinforcement learning, and the method comprises the steps: building four network performance models: energy consumption, packet delivery rate, throughput and end-to-end time delay; establishing a node interaction mechanism; establishing a Markov decision process, defining definitions of a state space, an action space and a space state transition probability, and designing a reward function; based on an improved multi-agent depth deterministic policy gradient algorithm DE-MADDPG, designing a flight ad hoc network distributed routing method based on multi-agent reinforcement learning; each unmanned aerial vehicle modifies a running protocol and a protocol parameter according to local network information of each node, optimizes a main network and a subnetwork of the system, and improves the overall performance of the network. The method mainly solves the problems that a traditional flight ad hoc network protocol is not high in adaptive capacity, and the network environment is not matched with the protocol. Compared with a traditional method, the method has the advantages of being low in control delay, high in control precision and good in performance.

Various methods and systems of the present disclosure provide a protocol data unit (PDU) set based quality of service (QoS) handling in a wireline access. To support the PDU Set based QoS handling in the wireline access, one or more PDU Set QoS parameters and / or PDU Set information may be provided to one or more wireline nodes (e.g., a wireline gateway access function (W-AGF) and / or a residential gateway (RG) etc.). When the W-AGF receives one or more N2 requests associated with one or more PDU session resources, the W-AGF maps one or more QoS profiles received from 5G core (5GC) to a wireline access user plane (W-UP) QoS level. The W-AGF sets up one or more W-UP resources based on the W-UP QoS level for a PDU session. Further, various methods and systems of the present disclosure also provide low latency, low loss, and scalable throughput (L4S) enabled wireline access.

A method for optimizing coexistence of low latency, low loss and scalable throughput (L4S) traffic and non-L4S traffic in a 5G wireless system is provided, which method includes one of: a) performing one of i) a flow control between a centralized unit (CU) and a distributed unit (DU), or ii) radio resource management at the DU, to reduce latency experienced by the L4S traffic; or b) performing one of iii) a flow control between the CU and the DU to facilitate greater frequency of transmission of non-L4S traffic from CU-user plane (CU-UP) to the DU, or iv) radio resource management at the DU, to reduce a scheduling priority metric of a logical channel for the L4S traffic relative to a scheduling priority metric of a logical channel for the non-L4S traffic. To reduce latency of the L4S traffic, the L4S traffic scheduling priority is increased relative to the non-L4S traffic.

A method is described for aligning high efficiency (HE), extremely high throughput (EHT), and EHT+sub-physical layer protocol data units (sub-PPDUs) included in an aggregated PPDU (APPDU) trigger frame. The method includes aligning a preamble portion of the sub-PPDUs by applying a multi-user PPDU (MU-PPDU) format to each of the sub-PPDUs and aligning a data portion of the sub-PPDUs by including a padding subfield in each of the sub-PPDUs to produce a common length.

Devices, networks, systems, methods, and processes for identifying, classifying, and scheduling Low Latency, Low Loss, and Scalable throughput (LAS) traffic are described herein. A device may receive a data flow comprising one or more data packets. The device may parse the one or more data packets to check for a congestion indicator. Upon detecting the congestion indicator in any data packet, the device can classify or mark the data flow as LAS. The device may schedule the data flow by utilizing an Active Queue Management (AQM) queue for L4S data flows. The device can also mark other uplink or downlink data flows associated with the data flow as L4S. The device can also facilitate LAS capability sharing while associating with one or more wireless devices. The device may utilize a management frame with an extended capabilities field to inform the LAS capability of the device.

The invention discloses a TSN scheduling optimization method and device based on flow sensing autonomous learning, equipment and a medium. The method comprises the following steps: deploying a lightweight flow detection module in a switch or a router, and after a controller receives a data request, automatically identifying a newly arrived unknown service flow by using the lightweight flow detection module, and judging whether the newly arrived unknown service flow is a periodic TT flow or an unpredictable burst flow; the controller performs classification management on the identified service flow types, collects topological information and flow requirements of the whole network and issues the topological information and the flow requirements to the terminal nodes through a network management interface; the controller constructs an intelligent queue scheduling task based on the collected network topology information and traffic demand and converts the task into a Markov decision process MDP, network resources, queue states and priorities are used as a state space, a scheduling strategy is used as an action space, a reward function is designed in combination with throughput and delay indexes, and an intelligent queue scheduling task is obtained. Driving a dynamic environment through real-time data and training a DRL model; an enhanced queue scheduling mechanism Pro-CQF is adopted, different priority labels are configured according to classified flow types, and then mixed flow scheduling is carried out; the controller periodically collects time delay, packet loss rate and end-to-end transmission delay indexes and feeds back the indexes to the DRL model, and a scheduling strategy is updated online. According to the method, the traffic sensing and scheduling efficiency is greatly improved in a network environment in which multiple service flows coexist and end-side equipment functions are different, and the reliability and the expandability of the TSN in industrial Internet of Things, edge computing and other high-real-time application scenes are remarkably enhanced.

A switch is provided for routing packets in an interconnection network. The switch includes a plurality of egress ports to transmit packets and one or more ingress ports to receive packets. The switch also includes a network capacity circuit for obtaining network capacity for transmitting packets via the plurality of egress ports. The switch also includes a port sequence generation circuit configured to generate a port sequence that defines a pseudo-randomly interleaved sequence of a plurality of path options via the plurality of egress ports, based on the network capacity. The switch also includes a routing circuit for routing one or more packets, received from the one or more ingress ports, towards a destination, based on the port sequence.

Dynamic Transmission Opportunity (TXOP) sharing between overlapping Basic Service Sets (BSSs) in wireless networks. A sharing Access Point (AP) initiates a process by generating and wirelessly transmitting a control frame to allocate its TXOP to a shared AP in an overlapping BSS. Subsequently, the sharing AP receives a return TXOP frame from the shared AP, indicating the return of any unused TXOP portion. The sharing AP then has the flexibility to either resume its own transmissions using the returned TXOP or reallocate it to an alternative AP. Using the techniques in dense wireless networking environments enables efficient spectrum utilization through dynamic TXOP allocation and reclamation. The techniques address challenges of resource management in multi-AP scenarios, improving overall network performance and reducing interference in overlapping coverage areas.

The invention provides a PCIe-NTB (Peripheral Component Interconnect Express-Network Temporary Block)-based P2P (Peer-to-Peer) communication method and system between IO (Input / Output) devices, the system comprises a plurality of computing nodes, and the computing nodes comprise a PCIe Switch, an NTB and a plurality of PCIe IO devices; the plurality of PCIe IO devices are connected with the CPU through the PCIe Switch; the NTB is connected with the PCIe Switch; the PCIe IO equipment at least comprises two different types of IO equipment, namely an IO equipment type 1 and an IO equipment type 2; the plurality of computing nodes are connected through the NTB; the system supports P2P communication between IO device types 1 or between IO device types 1 and IO device types 2 of different computing nodes. In the scheme, P2P communication can be directly carried out among IO devices of a plurality of computing nodes on the basis of PCIe-NTB, protocol conversion overhead and main memory and IO device memory moving overhead required by traditional NIC RDMA communication are avoided, and the characteristics of low delay and high throughput of a PCIe network can be fully utilized.

The invention provides a stream computing resource scheduling method and system based on a dynamic time window, and relates to the field of stream computing resource scheduling, and the method comprises the following steps: constructing a master-slave event time monitoring network to obtain a task feature vector, and establishing an adaptive time window scheduling mechanism to dynamically adjust the window size; and constructing a multi-level task priority queue, carrying out state transition by adopting a remote direct memory access mechanism of incremental transmission, and finally coordinating computing nodes through a distributed task arrangement protocol to complete resource switching. According to the method, computing resource competition can be effectively reduced, the flow computing task processing efficiency is improved, dynamic optimal configuration of resources is realized, and the system throughput is enhanced.

The invention discloses a cross-fragmentation transaction and fragmentation migration method and system, and relates to the technical field of transaction methods, and the method comprises the following steps: for a transaction input into a network, if accounts of a payer and a payee are in one fragmentation, carrying out an on-chip transaction; if the account of the payer and the account of the payee do not belong to the same fragment, cross-fragment transaction processing is carried out, and the cross-fragment transaction processing comprises the steps of main fragment transaction distribution; verifying transactions in the fragments; carrying out cross-fragment transaction verification; and submitting the cross-fragment transaction. According to the invention, the introduction of the block chain fragmentation technology can enable the block chain network to maintain the decentration characteristic, and achieve higher throughput and lower transaction delay at the same time.

This disclosure provides systems, methods, and apparatus, including computer programs encoded on computer-readable media, for signaling between an access point (AP) multi-link device (MLD) and a non-AP MLD that support multi-link communication in a wireless local area network (WLAN). In some implementations, a multi-link association may include a first link (referred to as an anchor link) and one or more other links (referred to as auxiliary links). The signaling may include control information to activate or deactivate auxiliary links dynamically based on communication load, throughput requirements, or quality of service (QOS). The signaling also may include requests, acknowledgments, or negotiation regarding multi-link connections. Furthermore, signaling and timing information may be used to coordinate when auxiliary links are used for communication or when to promote an auxiliary link to an anchor link.

The invention relates to the technical field of transaction data verification, in particular to a transaction data verification method and system. The method comprises the following steps: carrying out transaction data acquisition on block chain network nodes to obtain an original transaction data set; performing adaptive heterogeneous fragmentation on the original transaction data set to obtain a fragmented transaction data set; performing verification weight coefficient distribution on the fragment transaction data set to obtain a weighted fragment transaction data set; performing multi-level verification engine deployment on the verification nodes to obtain a layered verification node network; performing asynchronous message queue mechanism configuration on the hierarchical verification node network to obtain a parallel verification network cluster; and performing load balancing scheduling on the weighted fragment transaction data set based on the parallel verification network cluster to obtain a transaction verification task sequence. According to the invention, the throughput and transaction confirmation speed of the block chain system can be effectively improved.

The invention discloses a multi-resonator filter collaborative optimization method and system based on cloud computing, particularly relates to the field of cloud computing task processing, is used for solving the problem of resource scheduling resources, and can realize intelligent grouping of tasks in a task input stage through a dynamic density clustering method. A dynamic weight coefficient is calculated in combination with the data association degree and the resource conflict probability, so that priority division of tasks is completed before scheduling, and the accuracy of scheduling decision making is improved; a capacity expansion threshold is adjusted in combination with a historical load trend prediction model and a dynamic weight, and a resource capacity expansion strategy based on benefit driving is realized, so that the energy consumption of the system is reduced, and meanwhile, resource expansion is ensured to accurately match actual requirements; task subblock disassembly and a greedy distribution strategy are carried out based on the real-time energy efficiency ratio and the network topology cost, so that the calculation load tends to the optimal node distribution all the time, the calculation throughput is improved, and the delay loss of cross-node data transmission is reduced.

Implementing interference avoidance for high density ad hoc networks may include creating ad hoc Wireless Local Area Network (WLAN) clusters (WLAN pico-nets) of Information Handling Systems (IHSs) with nonoverlapping channels, enabling each IHS to have a high bandwidth wireless interface, and isolating nearby ad hoc WLAN clusters, using a Basic Secure Set (BSS) color field to associate IHSs within an ad hoc WLAN cluster (which may be preconfigured for each ad hoc WLAN cluster). Physical separation of ad hoc WLAN clusters may be optimized, minimizing cochannel interference, such as through use of dynamic threshold calculations. Nearby ad hoc WLAN clusters may be further isolated by dynamically adjusting transmit power control to isolate nearby ad hoc WLAN clusters, and / or by scaling channel width, such as through Dynamic Throughput Scalar calculations.

Disclosed is a method for transmitting and receiving a physical protocol data unit (PPDU) in a wireless communication system. A terminal receives a preamble of the PPDU from an access point (AP). The preamble includes a universal signal (U-SIG) field and an extremely high throughput (EHT)-SIG field, wherein the EHT-SIG field may be configured with at least one content channel on a frequency axis. Here, the number of the at least one content channel may be recognized on the basis of the U-SIG field. Subsequently, the terminal receives data of the PPDU on the basis of the U-SIG field and the EHT-SIG field.

The invention discloses an Internet of Things equipment energy management optimization method. The method comprises the following steps: S1, collecting and quantifying environment data and equipment state information; s2, analyzing the quantized data, and evaluating and quantifying the current energy consumption state of the equipment; s3, dynamically adjusting the task execution sequence according to the energy consumption mode of the equipment, the task priority and the external environment condition by using a priority-based self-adaptive hierarchical scheduling algorithm; s4, executing the tasks by utilizing the Internet of Things equipment according to the adjusted execution sequence, and preferentially executing the low-energy-consumption or high-efficiency tasks; and S5, further optimizing an intelligent scheduling algorithm according to task execution result feedback, and realizing continuous self-adaptive energy management optimization. By means of combination of hierarchical division and real-time scheduling, complexity of task scheduling is simplified, accuracy and effectiveness of scheduling are guaranteed at the same time, and therefore the problems that an existing method is poor in real-time performance, low in throughput and the like are solved under the condition that algorithm complexity is not remarkably increased.

Embodiments of the present disclosure provide a method of a burst-based route discovery process. The method includes sending a probing interest packet to an NDN network; when one NDN forwarder receives the probing interest packet from a corresponding face, sending the probing interest packet to neighboring NDN forwarders; after anyone NDN forwarder receives the probing interest packet, sending back a burst of K probing data packets; as the burst of K probing data packets being received by an NDN forwarder, evaluating gaps between arrival times of the burst of K probing data packets; determining an available network throughput level of a face of the NDN forwarder; and if determined available network throughput level indicates a predefined increase in network throughput, setting the face of the NDN forwarder as a face for forwarding interest packets; and sending the burst of K probing data packets to neighboring NDN forwarders.

Extended Reality (XR) applications may require high throughput and very low latency. New Radio (NR) Wireless receiver / transmitter units (WTRUs) running XR applications (XR-WTRUs) may be confronted with link failures when these applications are used in dense urban or indoor environments because of these devices operating in the millimeter band. Methods and devices are provided therefore for performing cell selection and beam management proactively to avoid link failure due to objects being in line of sight between the XR-WTRU and a network node with which it has established a connection. XR-WTRUs may therefore perform visual sensing that may enable visualizing current and future radio environment and using this information to prevent link failures by handing the XR-WTRU over to an alternative network node in line of sight of the XR-WTRU before the XR-WTRU is no longer in line of sight of the network node with which it has established a connection.

The invention discloses a CPE router, a data transmission method and device, a medium and a product, and relates to the technical field of network communication and data transmission optimizing.According to the scheme, the method comprises the steps of collecting and preprocessing inlet flow and wireless channel data of the CPE router, extracting transmission urgency and a channel quality index, constructing a transmission decision model and outputting service priority classification; and meanwhile, a dynamic transmission strategy and an early warning mechanism are formulated in combination with a channel prediction model result, and network resource allocation is optimized. According to the scheme, accurate matching and intelligent scheduling of network resources are achieved by dynamically sensing the channel state and the service characteristics, key service transmission delay is effectively reduced, the throughput of high-priority data is improved, meanwhile, transmission stability in a complex environment is enhanced, data retransmission caused by channel fluctuation is reduced, and the transmission efficiency is improved. Smoother multi-service concurrent experience is provided for users, potential transmission risks are warned in advance, and network service quality and equipment operation reliability are guaranteed.

The invention belongs to the technical field of alliance chain consensus, and discloses an alliance chain consensus improvement method and system based on contribution degree and grouping, and a CG-PBFT algorithm aims at optimizing the performance and efficiency of a block chain network. According to the algorithm, the consensus set is grouped, so that the communication complexity among the nodes is reduced, the nodes in the group are easier to cooperate, and the throughput and efficiency of the network are improved. In order to solve the problems of performance imbalance, safety and resource consumption of a PBFT algorithm, a consensus mechanism based on contribution degree is introduced into CG-PBFT, and a node with the highest contribution degree is selected as a master node through management of a master node election stage. The node contribution degree is a measurement method for measuring the overall contribution of the nodes to the network, and the node data contribution degree and the online resource consumption are mainly considered. The CG-PBFT algorithm is combined with the PoC contribution degree algorithm and the PBFT algorithm, the consensus consistency and the final consistency of the nodes are ensured, and meanwhile, the risk that an attacker tampers the consensus is reduced by reasonably grouping the consensus nodes.

The invention relates to the technical field of communication fault monitoring, in particular to a multi-core optical cable fault online monitoring method based on an optical fiber sensing technology. The method comprises the following steps: firstly, establishing a primary network topological graph according to a direct communication relationship of core nodes, selecting a key service optical cable according to a key service type of the primary network topological graph, and establishing a secondary network topological graph; the second-level link historical performance data of the second-level network topological graph is clustered, and the performance state of the second-level link is judged in real time; calculating a trunk index according to the bandwidth and the throughput and determining a trunk optical cable; performing fault monitoring on the trunk optical cable by using ROTDR equipment, completing super-resolution reconstruction and signal analysis through an SR-LSTM model, positioning a fault position and identifying a fault type; a state space and an action space are constructed through an Actor-Critic reinforcement learning framework in combination with a performance state, a fault position and a fault type, an intelligent agent learns an optimal operation and maintenance strategy, and online fault monitoring of a main optical cable is realized.