58 results about "Network Load Balancing" patented technology

The invention discloses a network load balancing distributed strategy optimization method. The method comprises the following steps: acquiring node load data; a gravity and repulsive force field is simulated to dynamically adjust load distribution; each data center node deploys a load balancing agent, and a task allocation strategy is dynamically adjusted through multi-agent reinforcement learning training; resource allocation optimization: based on a resource allocation optimization target, optimizing allocation from tasks to nodes with the target of minimizing data transmission cost and calculation delay and satisfying resource constraints at the same time; and the load index and the actual task delay of each node are monitored in real time, and the overall performance of the system is evaluated. The method can adapt to load fluctuation of the ground; the reward function ensures that the proxy not only optimizes local performance in a high dynamic scene, but also maintains the stability of a global network structure; the load attention mechanism enables the agent to dynamically pay attention to nodes with lower load and better delay.

A packet to be forwarded over a computer network to a destination is received. A group of multiple network paths is available to forward to the packet to the destination. One or more path selection factors are determined to be used to identify a specific network load balancing algorithm to select a specific network path from the group of multiple network paths. The one or more path selection factors include at least one path selection factor determined based at least in part on a dynamic state of the computer network or a network node in the computer network. In response to selecting, by the specific network load balancing algorithm, the specific network path from among the group of multiple network paths, the packet is forwarded over the specific network path.

This invention relates to a routing method and system for low-Earth orbit satellite constellation networks. This method enhances the congestion awareness of satellite nodes to improve the routing selection and traffic distribution effect. Based on real-time link status information, routes are updated promptly to better respond to changes in satellite network topology and network traffic, resulting in a higher packet delivery success rate. It improves congestion awareness to obtain link load information within a two-hop range and enhances network load balancing by providing a wider range of routing options, enabling satellite nodes to make routing and forwarding decisions with a broader routing perspective.

Techniques for load balancing secure network traffic are disclosed. A system, process, and / or computer program product for load balancing secure network traffic includes monitoring network traffic for one branch of a plurality of branches for an enterprise network, and splitting the network traffic of the one branch into a plurality of network segments based on a determination that the network traffic exceeds traffic capacity of at least one security processing node (SPN) of a plurality of SPNs using a network load balancer (NLB) in communication with a plurality of Network Processing Nodes (NPNs), the plurality of monitored branches being distributed to the plurality of SPNs via a plurality of tunnels.

The invention provides a terminal redirection method and device, and the method comprises the steps: determining a target distributed network for a to-be-migrated terminal in a current distributed network under the condition that the current distributed network meets an internal terminal redirection condition; acquiring base station information, and determining a plurality of candidate service paths according to the base station information, the to-be-migrated terminal and the target distributed network; determining a target service path by taking the optimal comprehensive performance parameter of the road section as a target; and generating a service strategy based on the target service path, and issuing the service strategy to the to-be-migrated terminal, the to-be-migrated terminal being used for redirecting to the target distributed network according to the service strategy. Therefore, the automatic redirection of the terminal among the distributed networks is realized by dynamically evaluating the network state and intelligently selecting the optimal migration path, and the network load balancing efficiency and the terminal service quality can be improved while the energy consumption is reduced.

The invention discloses a network load balancing method, a computer program product, equipment and a medium, relates to the technical field of data centers, is applied to a virtual switch of a data center, and obtains to-be-sent data; packaging the to-be-sent data to obtain initial packaged data; in the quintuple, determining an item to be transformed; in the initial encapsulation data, transforming a value corresponding to a to-be-transformed item in the outer layer message to obtain target encapsulation data; performing hash operation based on the quintuple of the target encapsulation data to obtain a hash value; and transmitting the target encapsulation data according to a transmission path corresponding to the hash value. The method and the device have the beneficial effects that different transmission paths can be used for transmitting the target encapsulation data, and finally, different to-be-sent data of the same stream are transmitted through different transmission paths, so that the occupation of a single transmission path by the data of the same stream is avoided, load balancing between the transmission paths is realized, and the transmission efficiency is improved. The network load balancing capability of the data center is improved; and the universality is good.

The invention provides an energy data dynamic encryption method and system based on edge computing, and relates to the technical field of information security, and the method comprises the steps: dividing terminal equipment in a power grid into a plurality of equipment groups, and enabling each equipment group to correspond to an edge computing node; constructing a block chain network according to the edge computing nodes; acquiring data features of data to be sent to a second edge computing node by a first edge computing node, and network features of the first edge computing node and the second edge computing node; generating a first encryption strategy according to the data features; adjusting the first encryption strategy according to the network characteristics to generate a second encryption strategy; and generating a network load balancing parameter according to the load states of other edge computing nodes in the block chain network, and adjusting the second encryption strategy according to the network load balancing parameter to generate a target encryption strategy. The technical effect of the application is that the security of data transmission is improved.

The invention relates to the technical field of control, in particular to an intelligent valve positioner control method and system based on LoRa. The method comprises the following steps: determining LoRa communication parameters according to an operation state and a network environment of an intelligent valve positioner, constructing a data uplink, and when the communication parameters are determined, establishing a time sequence prediction model based on a historical signal-to-noise ratio and a packet loss probability sequence to obtain a predicted link quality index, the index is corrected by using an error value between a current control instruction and an actual position of the valve, a communication parameter combination is determined according to the corrected link index, and the access cost is calculated based on the received signal strength indication of the candidate father node, the residual electric quantity and the number of borne child nodes when the data uplink is constructed; and taking the node with the minimum access cost as a father node, and switching the father node by adopting a switching delay mechanism. According to the scheme, the key instruction transmission success rate can be increased, network load balancing is achieved, and the stability of network topology and the continuity of data transmission are ensured.

Techniques for load balancing secure network traffic are disclosed. A system, process, and / or computer program product for load balancing secure network traffic includes monitoring network traffic for one branch of a plurality of branches for an enterprise network, and splitting the network traffic of the one branch into a plurality of network segments based on a determination that the network traffic exceeds traffic capacity of at least one security processing node (SPN) of a plurality of SPNs using a network load balancer (NLB) in communication with a plurality of Network Processing Nodes (NPNs), the plurality of monitored branches being distributed to the plurality of SPNs via a plurality of tunnels.

The application discloses a quantum key distribution network routing method and system, comprising: dividing a quantum key pool in an SDN-QKD network; based on key service requests of different security levels and the divided quantum key pool, a maximum key service request success model is constructed, and the maximum key service request success model is used to approve the key service requests; based on a minimum key consumption model, the approved key service requests are screened; based on the screened key service requests, a key resource consumption routing optimization algorithm is used to generate a final path; and based on the final path, key distribution is performed. The application improves key resource utilization, guarantees high-priority business transmission success rate, and effectively improves network load balancing degree.

The invention discloses a dynamic working condition-oriented data-real fusion test consistency guarantee method, which comprises the following steps of: carrying out dynamic working condition sensing and data stream preprocessing, sensing network load and physical node states in real time, and preferentially processing high-timeliness data by adopting a self-adaptive traffic shaping mechanism; the method comprises the following steps: constructing an attention-enhanced distributed multi-agent Actor-Critic network architecture based on deep reinforcement learning, and carrying out collaborative decision making by taking a communication node as an independent agent; strategy iteration training is carried out in a digital twin training environment mapped with a physical environment, key state features are extracted by using a self-attention mechanism, and scheduling behaviors are optimized through a multi-target reward function comprehensively balancing delay jitter, multi-source data consistency and network load balance; and converting the global optimization strategy into a dynamic flow scheduling table and issuing the dynamic flow scheduling table to a physical node for execution. According to the method, the problems of time delay fluctuation and consistency deviation of a data-real fusion test in a dynamic network environment are solved.

The application provides a network load balancing algorithm based on a Xinyuan platform and a Xinyuan terminal, and relates to the technical field of Xinyuan, which comprises the following steps: collecting real-time traffic data from multiple ports; performing normalization, outlier elimination and protocol field standardization preprocessing on the collected data; performing multi-dimensional protocol fingerprint feature extraction on the traffic of each port based on a protocol analysis algorithm; modeling the historical and real-time traffic of each port using a time series neural network, and outputting traffic prediction values and abnormal traffic probability evaluation in a future short period; dynamically generating a multi-port distribution weight factor based on the protocol characteristics and traffic change trend of each port; inputting the prediction results and real-time load state into a reinforcement learning scheduling agent; and immediately performing feedforward load distribution adjustment when abnormal traffic trend is detected. The method can improve the data processing efficiency, realize the intelligence of load scheduling, ensure the resource allocation priority of the ports of the Xinyuan terminal, and guarantee service continuity.

The invention relates to an AODV routing protocol method, in particular to an AODV routing protocol method based on joint optimization of a three-dimensional weight hop count penalty mechanism. The invention aims to solve the problem that a single path selection standard neglects node residual energy, link quality and topology stability. The method comprises the following steps: based on position weight calculation of inter-node distance dynamic attenuation, suppressing a long-distance low-quality link; an energy weight is constructed by multiplying the ratio of the residual energy and the initial energy, and network load balancing is optimized; a movement weight in a speed difference square root reciprocal form is introduced, and a link life cycle is predicted; and a hop number punishment mechanism is newly added, so that nonlinear adjustment of multi-hop path quality is realized. And intelligent optimization of comprehensive score of the path is realized by combining a request message RREQ of an improved AODV routing protocol through normalization constraint and a hop punishment mechanism of a three-dimensional coefficient. The invention belongs to the technical field of wireless ad hoc networks.

This invention discloses a method and system for real-time data synchronization of multiple target libraries for power metering, belonging to the field of power metering data processing technology. Edge node devices collect and preprocess real-time data from power metering terminals, generating an energy consumption and resource status matrix before uploading it to the cloud. The cloud automatically detects the target library type and determines the adaptation priority through dynamic format conversion and hierarchical analysis. Based on the status matrix and priorities, a five-dimensional objective function is constructed, including business priority, cross-library adaptation success rate, system energy consumption, network load balancing, and data time-series consistency. An optimal scheduling scheme is generated using the DDPG algorithm. Transmission is completed by combining LSTM prediction, sliding window differential, and lightweight compression. After SHA-256 segmented verification, the hash value and device ID are written into the power industry consortium blockchain. This invention achieves multi-library collaborative adaptation, low bandwidth consumption, low energy consumption, and high time-series consistency, ensuring real-time, accurate, and secure synchronization of metering data.

Techniques for load balancing secure network traffic are disclosed. A system, process and / or computer program product for load balancing secure network traffic includes monitoring network traffic for each of a plurality of branches of an enterprise network, and using a network load balancer (NLB) in communication with a plurality of network processing nodes (NPNs), load balancing of a plurality of monitored branches is performed on a plurality of secure processing nodes (SPNs) executing in a cloud-based security service, the plurality of monitored branches being distributed to the plurality of SPNs via a plurality of tunnels.

This application discloses a CAN network load balancing method, apparatus, device, and medium, relating to the field of communication technology and applied to a master ECU node. The method includes: after power-on, sending a local clock timestamp to each slave ECU node at preset time intervals, so that each slave ECU node synchronizes its local clock based on the timestamp; obtaining the transmission load reported by each slave ECU node after synchronizing its local clock, and planning the transmission time points of each slave ECU node based on the transmission load to obtain a time schedule table; and sending the time schedule table to each slave ECU node so that each slave ECU node sends CAN messages at the target time points specified in the time schedule table according to its local clock. In this application, the master ECU node can uniformly schedule the time for slave ECU nodes to send CAN messages based on their transmission load, reducing the peak load of the CAN bus and ensuring the stability and real-time performance of signal transmission.

The application discloses a large-scale constellation hierarchical routing planning method for concurrent tasks, and belongs to the technical field of mega constellation management and routing planning.The application is used for solving the problem of constellation routing planning under large-scale concurrent tasks and large-scale nodes.The application comprises the following steps: dividing a large-scale constellation into constellation management domains, determining the shortest domain-level path from a starting constellation management domain to a terminal constellation management domain for each task, determining the initial entry domain endpoint and the initial exit domain endpoint of each constellation management domain based on a global routing reference direction, adjusting the exit domain endpoint of a congested node to obtain a final exit domain endpoint and a corresponding final entry domain endpoint, and dividing the tasks in the constellation management domain into rounds according to the estimated time sequence of the tasks to arrive at the constellation management domain, and selecting a low-load next-hop satellite node for each round of task.The application reduces the complexity of constellation routing planning under large-scale concurrent tasks and large-scale nodes, and realizes the optimization of network load balancing performance.

Techniques for multi-Content Delivery Network (CDN) load balancing are performed at a content steering server in a multi-CDN system, where the multi-CDN system includes a plurality of CDNs serving a plurality of clients. The content steering server receives from a first CDN of the plurality of CDNs a request to switch a first number of clients in the multi-CDN system. In response to receiving the request, the content steering server facilitates negotiations between the first CDN and at least one CDN of the plurality of CDNs, including determining a second number of clients in the multi-CDN system to be switched. Upon successful negotiations, the content steering server triggers the first CDN and the at least one CDN to switch the second number of clients between the first CDN and the at least one CDN.

A method for performing mobility load balancing includes receiving, at a server, current load data for a plurality of cells of a wireless communication network, selecting, from the plurality of cells, a target cell (s), wherein a value of the current load data for the target cell exceeds a first predefined threshold, and selecting, from a neighbor cell list corresponding to the target cell, a set of neighboring cells for the target cell. The method further includes calculating, a value of at least one utilization parameter for the target cell, determining, a CIO value and an E-tilt value for the target cell based on the value of the at least one utilization parameter for the target cell and configuring one or more physical layer parameters of the target cell based on the determined CIO and E-tilt values for the target cell.

Aspects of the disclosure are directed to dual layer load balancing. In accordance with one aspect, the disclosure includes executing a first layer network load balancing strategy for a client server task using a network load of each of a plurality of hubs; obtaining a network load of cloud terminal resources in a hub center on a hub-terminal side for the client service task; and executing a second layer network load balancing strategy for the client service task using the network load of the cloud terminal resources to select one hub.

The invention belongs to the technical field of communication, and particularly relates to a method for dynamically adjusting transmission parameters of distributed low-power-consumption Internet of Things equipment. The method for dynamically adjusting the transmission parameters of the distributed low-power-consumption Internet of Things equipment comprises the following steps that S10, a mobile node generates carrying inquiry information and sends the carrying inquiry information to a monitoring device node within a preset range distance, and the monitoring device node sends a stored monitoring log and a local address to the mobile node after receiving the carrying inquiry information; and S20, the mobile node acquires a locally stored mobile route and acquires the number of servers or data transmission nodes in a preset range distance in the mobile route as a first number, and if the first number is greater than 0, a first signal is generated during movement and broadcasted to other mobile nodes in the preset range distance. According to the scheme, the transmission cost is reduced and the service life of equipment is prolonged through a dynamic relay transmission mode, meanwhile, network load balancing and improvement of data transmission reliability are also realized, and good expandability is achieved.

The invention discloses a clustering network flow scheduling method, device and equipment based on star flash, which are suitable for solving the problem of scheduling periodic control flow of a star flash system in a clustering network scene, and the method comprises the following steps: collecting network state information and service flow information of nodes in a cluster; constructing a clustering network flow time slot scheduling model based on star flash; establishing a network traffic scheduling constraint optimization problem taking network load balancing and end-to-end time delay minimization as targets; constructing a Markov decision process of multi-management node cooperation based on the constraint optimization problem; the Markov decision process is solved; according to the method, a multi-management-node cooperative flow scheduling algorithm is operated for solving to obtain an optimal resource allocation result, and flow scheduling is performed on the star flash clustering network according to the resource allocation result, so that the load balancing capability of a star flash clustering network system can be improved, and meanwhile, the end-to-end transmission delay of a service flow is reduced.

The application provides a kind of based on core network traffic statistics, bearer network load balancing method, device and system, the method comprises: according to the statistical result of core network control plane network element SMF forwarding constructs bearer network traffic component diagram, wherein the statistical result is obtained by the traffic information statistics of core network user plane network element UPF to multiple GTP-U tunnels and the statistical result is sent to core network control plane network element SMF;When link congestion occurs in bearer network, according to the bearer network traffic component diagram, obtain the to-be-scheduled traffic for scheduling to other non-congestion links in the current congestion link, change the flow diversion rule of bearer network access router side and change the path of the to-be-scheduled traffic in the bearer network to schedule the to-be-scheduled traffic to other non-congestion links, realize bearer network load balancing.The application can realize the identification and load balancing of data stream granularity under the condition that bearer network equipment capacity is limited and bearer network does not identify GTP-U packet header.

This application discloses a network load balancing control method, apparatus, device, and storage medium. The method includes: a first network device sending a path probe request message to a second network device; receiving multiple path probe response messages returned by the second network device; determining the weight value of each link path based on the round-trip time (RTT) value of each path probe response message; and proportionally allocating service packets to the corresponding link paths and sending them to the second network device based on the weight values ​​of each link path. In this way, service packets can be proportionally allocated to the corresponding link paths and sent to the second network device based on the weight values ​​of each link path, thereby realizing a single-stream multi-path load balancing mechanism. Furthermore, by distributing service packets through multiple paths, it is beneficial to improve the utilization rate of link paths in the network, optimize the uniformity of network traffic scheduling, effectively avoid traffic congestion, and thus improve the overall network performance.

This invention relates to the field of remote control technology, specifically to a method and system for remote collaborative control of intelligent devices based on the Internet of Things (IoT). The method includes the following steps: based on an IoT platform, monitoring and adjusting the CPU utilization and memory usage of intelligent devices; optimizing data acquisition and network resource allocation; analyzing device performance and network load balancing indicators to achieve device connection priority ranking and task load management; and dynamically adjusting task execution and connection frequencies to meet real-time task requirements and improve system efficiency. This invention significantly improves data processing speed and reduces resource waste by dynamically adjusting data transmission intervals through real-time monitoring of device performance indicators. Real-time load analysis and optimization of network nodes ensure efficient use of network resources, avoiding data delays caused by network congestion. Regarding device connection management, an intelligent priority determination mechanism allows critical devices to quickly access the network in emergency situations.

This invention relates to the field of control technology, specifically to a LoRa-based intelligent valve positioner control method and system. The method includes: determining LoRa communication parameters and constructing a data uplink based on the operating status and network environment of the intelligent valve positioner; obtaining a predicted link quality index by establishing a time series prediction model based on historical signal-to-noise ratio and packet loss rate sequences when determining the communication parameters; correcting the index using the error value between the current valve control command and the actual position; determining the communication parameter combination based on the corrected link index; and calculating the access cost based on the received signal strength indication, remaining battery power, and number of child nodes carried by candidate parent nodes when constructing the data uplink; selecting the node with the lowest access cost as the parent node and switching the parent node using a switching hysteresis mechanism. In other words, the solution of this invention can improve the success rate of critical command transmission, achieve network load balancing, and ensure the stability of the network topology and the continuity of data transmission.

This invention proposes a distributed control method for distributed generation in a distribution network based on optimal spectral clustering. It employs an active power flow-based spectral clustering method to divide the distribution network into small clusters according to distributed photovoltaic (PV) power, generating balanced clusters and identifying the error between the reference net load and the measured net load. Then, a controller is assigned to each cluster to manage the distributed generation within the cluster. Based on an error minimization method, the DER (Distributed Generation Controller) scheduling dynamically compensates for local net load changes. This controller manages the distributed generation within the cluster to reduce the intermittency of the net load. To address constantly changing grid conditions, the clusters dynamically change to determine a new optimal cluster configuration. Through these dynamically changing clusters, the network load balance is further improved.

The invention provides an optical network multipath resource allocation method, system and device, and the method comprises the steps: obtaining a current preset routing table of an optical network according to each node pair in a current directed graph of the optical network; obtaining a service set comprising a plurality of service flows; inputting the preset routing table and the service set into a preset optical network multi-path resource allocation model, and solving the optical network multi-path resource allocation model based on a preset constraint condition and a gradient descent method to obtain a continuous solution representing the allocation proportion of each service flow on different paths and an integer allocation matrix corresponding to the continuous solution; and performing conversion processing on the integer distribution matrix to obtain a corresponding flow table used for recording the distribution relationship between each service flow and each path resource, and issuing the flow table to each network device. The network load balancing degree can be improved, so that the network throughput is increased, the network time delay is reduced, and the network load balancing is realized.

Embodiments include hardware and software resources of a distributed computing system for routing user data traffic to computing resources organized using a shuffle sharding arrangement. Layer 3 (L3) network load balancers proxy or route user data traffic requests to layer 4 (L4) transport load balancers. A L4 transport load balancer proxies and routes the requests to certain ingress cells that are assigned or mapped to the hosted computing services of the user requests according to proxy or routing functions and mapping data. The assignments between cells and computing services may be implemented by a cell manager program when onboarding the computing services in accordance with the shuffle sharding arrangement and configuration. The transport load-balancer may impose and enforce the shuffle sharding by routing user data to ingress cells assigned to the computing services using previously determined mappings data stored in a mappings database (or data file).