1237 results about "Transmission network" patented technology

The invention discloses an optical transmission network hidden danger detection method and device and a computer program product, which can realize dynamic adjustment of differentiated bandwidth requirements by acquiring optical network state information in real time, evaluating service priority and establishing an optical channel resource allocation model. And when a topology anomaly is detected, constructing a service quality evaluation model by using a long-short-term memory neural network, and quantitatively analyzing the influence of the anomaly on the service. When a fault occurs, distributed link fault detection and a fault diagnosis engine based on a decision tree are adopted, and fault hidden dangers are quickly positioned and classified. And then, through an elastic recovery mechanism oriented to service sensitivity, the service quality level of a standby optical path is adjusted, and an optical layer topology connection relationship is optimized. According to the method, the resource utilization efficiency, the fault recovery capability and the service quality of the optical network are remarkably improved, and an innovative solution is provided for intelligent optical network management.

The invention relates to the technical field of atmospheric pollutant detection, and discloses a method and a system for detecting excessive emission of atmospheric pollutants. The method comprises the following steps: acquiring pollutant concentration data of multiple monitoring points in a target area to form an original data set; abnormal value detection and correction are carried out on the data set, sensor fault outliers are eliminated, and a preprocessed data set is obtained; extracting concentration change trend characteristics in a preset time window of each monitoring point, and constructing a spatial-temporal characteristic matrix; inputting the matrix into a pollutant diffusion model, calculating a transmission path and strength between monitoring points, and generating a regional transmission network; identifying a potential source region of abnormal fluctuation of pollutant concentration based on a network, and marking the potential source region as a candidate region to be checked; performing multi-scale concentration gradient analysis on the candidate area, and determining a key monitoring area; arranging mobile equipment in the key monitoring area, and collecting high-precision component data; and comparing the data with a standard emission source feature library, matching emission source types of which the similarity exceeds a threshold value, judging whether the emission exceeds the standard or not, and generating a detection report.

The present application discloses a calculation method for multi-scale electric-carbon energy efficiency optimization for a power system, which includes designing a carbon flow calculation improvement model of the power system that takes into account a photovoltaic cluster auxiliary service, converting a power lossy transmission network of the power system equivalent to a lossless power consumption network, and calculating a carbon flow of the power system that takes into account a photovoltaic reactive power cluster auxiliary service; designing a decision-making system for low-carbon operation of the power system based on a coupling of electric-carbon energy efficiency, and calculating a correlation between electric quantity and the carbon flow of the power system that takes into account the photovoltaic cluster auxiliary service; the output varies in the range of 0-1, larger values represent a stronger correlation between electric-carbon energy efficiency.

The invention discloses a mechanical arm digital twinning system for deep space exploration, and relates to the technical field of digital twinning simulation. The mechanical arm comprises a physical layer, a data acquisition and transmission layer, a digital twin model layer and an application layer, the physical layer comprises a mechanical arm body and a sensor network, and the sensor network is used for acquiring operation state information of the mechanical arm body; the data acquisition and transmission layer comprises data acquisition equipment and a data transmission network, wherein the data acquisition equipment is respectively connected with the sensor network and the data transmission network. According to the invention, the physical layer, the data acquisition and transmission layer, the digital twinborn model layer and the application layer of the mechanical arm are constructed, so that the actual mechanical arm body can be guided to perform related actions through virtual simulation data, and virtual and real body configuration comparison can be completed through a visual interface; and the digital twinning requirements of various spacecraft operations in the future deep space exploration field are met.

The invention provides an edge fusion diagnosis system and method for multi-source heterogeneous power transmission monitoring data, and belongs to the technical field of power transmission line monitoring. The multi-source heterogeneous power transmission monitoring data edge fusion diagnosis system comprises a multi-source heterogeneous data access module, a data preprocessing and standardization module, an edge computing node, an edge node collaborative diagnosis module, a data compression and feature extraction module and a cloud fusion analysis platform. The method comprises the following steps: accessing multi-source heterogeneous data, preprocessing and standardizing, locally diagnosing by an edge computing node, triggering multi-node collaborative diagnosis when the credibility is insufficient, and uploading key feature data to a cloud for global analysis and model optimization. According to the method, comprehensive integration and efficient processing of multi-source data are realized, the real-time performance, accuracy and comprehensiveness of power transmission monitoring diagnosis are improved, and the efficient monitoring requirement of a complex power transmission network can be met.

The invention belongs to the technical field of power systems, and particularly relates to a transmission and distribution cooperative scheduling optimization method based on multi-agent deep reinforcement learning. The method comprises the following steps: firstly, establishing a transmission and distribution cooperative scheduling distributed framework, and respectively establishing distributed optimization models taking the minimization of the operation cost of a power transmission network and the minimization of the operation cost of each active power distribution network as targets; secondly, converting a transmission and distribution collaborative scheduling problem into a Markov game model with a multi-agent benefit balance characteristic, and designing a collaborative multi-agent architecture; then interacting with a transmission and distribution interconnection environment through each agent to obtain historical interaction information, storing the historical interaction information into an experience pool, and training by using an MADDPG algorithm to realize iterative updating and optimization of an Actor network and a Critic network of each agent; and finally, realizing local optimization control of the power transmission network and each active distribution network by using an Actor network.

The invention, which relates to the technical field of traffic safety dispersion, discloses an anti-vehicle-blocking traffic safety dispersion method for reconstruction and expansion of an expressway, and the method comprises the following components: S1, constructing a multi-dimensional information collection system, S2, establishing an information intelligent transmission network, S3, carrying out a traffic jam prediction algorithm, and S4, carrying out precise early warning and intelligent guidance. According to the invention, rapid and efficient transmission of information is realized through the converged communication technology, the communication technology not only improves the speed and stability of data transmission, but also can realize intelligent switching in different signal environments, thereby providing timely and reliable traffic information for a traffic management center, enabling the traffic management center to make a response rapidly, and improving the traffic management efficiency. Accurate early warning and intelligent guidance are implemented, and traffic jam and safety accidents are effectively avoided.

The invention discloses a transmission path planning method and system for a box-type logistics system, and the method comprises the steps: constructing a four-dimensional space-time transmission network model which comprises the three-dimensional space coordinates of the box-type logistics system and department operation time window constraints, and quantifying the node traffic capacity; a hierarchical planning architecture is adopted, and a dynamic Bayesian network is introduced to predict the node congestion probability; a multi-agent cooperation mechanism is established, an online layer adjusts a path weight in real time by improving an ant colony optimization algorithm, and an offline layer optimizes global strategy parameters by using deep reinforcement learning and constructs a knowledge distillation channel to realize cross-period experience migration; and a multi-objective evaluation function is applied, transmission time cost, system energy consumption indexes and path load balance degree are synchronously optimized, a conflict resolution mechanism based on the game theory is designed, and transmission path planning of each box body is realized. According to the invention, through dynamic path planning and real-time flow monitoring, materials can be rapidly and accurately delivered to a destination, and the overall efficiency of a logistics system is improved.

In some implementations, a network device may receive an indication of a next-next-hop of the network device and link quality information of the next-next-hop. The network device may transmit network traffic based on the indication of the next-next-hop and the link quality information of the next-next-hop.

The invention relates to the technical field of network communication security, and discloses a real-time encrypted transmission network communication security guarantee system, which comprises a dynamic fragmentation quantum resistance encryption module, a flow perception-based adaptive encryption engine, a zero-handshake continuous identity authentication module and a hardware acceleration fragmentation processing architecture, and the dynamic fragmentation quantum resistance encryption module is configured to segment a data stream into a plurality of fragments according to a time window, and independently generate an unassociated key for each fragment based on a quantum security NTRU algorithm. According to the network communication security guarantee system for real-time encryption transmission, the traditional network communication security guarantee technology is comprehensively innovated, and the problems of static key management, encryption algorithm adaptation, data fragmentation encryption, identity authentication and encryption cooperation, quantum computing threat response and the like are successfully solved; and the performance of the system in key performance dimensions such as security, real-time performance, adaptability, reliability and anti-attack capability is obviously improved.

The invention provides an ecological environment dynamic monitoring method based on big data, and relates to the technical field of environmental pollution detection, and the method comprises the steps: collecting multi-source sensor data of a fixed monitoring station in an urban region, and carrying out the time alignment and space registration of the multi-source sensor data, thereby generating a standardized environmental monitoring data set. And on the basis of the data set, constructing a pollutant transmission network between the monitoring points to obtain a regional pollutant distribution characteristic graph, calculating a diffusion trend coefficient of pollutants in combination with regional wind direction data, constructing a pollutant migration path network, and generating a key supervision region map. According to the method, the pollutant concentration distribution can be dynamically partitioned, and the mobile monitoring equipment is scheduled to carry out gradient type point distribution monitoring, so that the accurate positioning of the pollution source is realized; the accuracy of pollutant diffusion trend analysis and the precision of pollution source positioning are improved, dynamic supervision of key areas is facilitated, the efficiency of environment monitoring and the fine management level are improved, and therefore the risk of environmental pollution is effectively reduced.

The invention discloses an asynchronous motor energy-saving monitoring and dynamic early warning method based on situation awareness, and relates to the technical field of asynchronous motor energy-saving monitoring. The method comprises the steps that S1, multi-source heterogeneous data are synchronously collected, power supply parameters and operation parameters are obtained in real time, and a frequency conversion working condition self-adaptive deviation value and a current stability coefficient are obtained; s2, generating four-dimensional situation factors including an overtemperature danger value, a current stability coefficient, a voltage stability coefficient and a frequency deviation value; s3, constructing a fourth-order transmission network, and generating a primary early warning signal based on the path mark combination; s4, calculating the motor efficiency in real time, triggering an efficiency abnormity mark, fusing the efficiency abnormity mark with the primary early warning signal, and reconstructing a final early warning instruction; and S5, executing hierarchical control according to the final early warning instruction. Through multi-parameter coupling and dynamic early warning transmission, the early-stage capture capability of the composite fault is improved, the early warning response delay is shortened, energy-saving optimization and fault protection of the motor are realized, and the method has a remarkable practical value.

The present disclosure relates to data transmission methods. In one example method, a first gateway device obtains a RoCEv2 packet to be sent to a second gateway device, generates a target request, and sends the target request to a network controller. The two gateway devices perform data transmission based on an SRv6 network. The network controller obtains a path computation result based on the target request, and returns the path computation result to the first gateway device. The path computation result includes a network path between the two gateway devices and a reserved network resource. The first gateway device extends the RoCEv2 packet based on the path computation result. An extended RoCEv2 packet carries a first identifier and a second identifier representing RDMA data. The network controller performs bandwidth assurance based on the second identifier and a QoS policy. An extended RoCEv2 packet is forwarded on the network path.

Provided in the present application are a power load regulation and control system and method based on a high-speed wireless transmission network. The power load regulation and control system comprises a regulation and control resource layer, an aggregation transmission layer and a load terminal layer, wherein the load terminal layer is connected to each terminal device, and is used for collecting information of each terminal device and fusing the information of the terminal devices, and also issuing a control instruction to each terminal device or transmitting fused information to the aggregation transmission layer; the aggregation transmission layer is used for transmitting the fused information to the regulation and control resource layer by using multi-service multi-hop access technology and secure transmission technology, and transmitting to the load terminal layer the control instruction issued by the regulation and control resource layer; and the regulation and control resource layer is used for generating the control instruction for each terminal device on the basis of the fused information, and transmitting the control instruction to the aggregation transmission layer. The present application can realize the unification of a stable connection and a high transmission rate, can also meet the high requirements for data collection and the transmission rate, and can also cope with complex and variable channel transmission scenarios.

The invention relates to the technical field of cable fault diagnosis and positioning, in particular to a cable fault positioning method and system based on multi-source data space-time correlation, and the method comprises the steps: obtaining partial discharge, traveling wave and temperature multi-source monitoring data from a high-voltage cable-overhead line hybrid power transmission network; on the basis of space-time correlation analysis of partial discharge and temperature data, heat-electricity associated defect points are calibrated; comparing traveling waves of the cable and the overhead line, and identifying and inhibiting cross-domain propagation interference; positioning the traveling wave data which are not identified to obtain temporary coordinates, judging fault characteristics by fusing information such as sheath ring current and the like, and comparing the temporary coordinates with defect points to generate matching identification; and inputting multi-dimensional information such as fault features, defect matching identification and temperature into the fusion model, calculating the confidence coefficient of a fault mode, and outputting a cross validation positioning result. According to the invention, high-reliability positioning of mixed line faults and active early warning of insulation defects are realized by carrying out space-time correlation and fusion decision on multi-source monitoring quantities such as traveling waves, partial discharge, circulation, temperature and the like.

The invention discloses a production enterprise-oriented pollutant degradation scheme recommendation method and system and a medium, and relates to the technical field of environmental protection, and the method comprises the steps: collecting multi-source pollution related data in real time in an enterprise production area, and uploading the data to a data processing center through an Internet of Things transmission network; a pollutant prediction model is constructed, pollutant generation prediction is carried out according to the preprocessed multi-source pollution related data, and the migration and diffusion trend of generated pollutants is analyzed; a pollutant generation prediction result and a pollutant migration and diffusion trend are used to construct a pollution portrait, a degradation technology is selected, and a degradation scheme is generated; and executing the degradation scheme to degrade pollutants, and acquiring operation parameters and degradation effect data of degradation equipment to perform equipment fault monitoring and degradation scheme optimization. According to the invention, through real-time monitoring, accurate data analysis and dynamic adjustment of a degradation scheme, and in combination with a novel composite degradation technology, continuous, efficient and stable treatment of pollutants is realized, and the influence of the pollutants on the environment is effectively reduced.

The invention provides a communication and interaction method of a digital twinning system in a compressor blisk machining process, and relates to the technical field of digital twinning and aeronautical manufacturing, and the method comprises the steps: collecting vibration, temperature and acoustic emission data in the compressor blisk machining process in real time, analyzing machine tool machining data, carrying out the alignment and noise reduction of the collected data, and obtaining a digital twinning result; then time-frequency domain mixed feature extraction is carried out, and time-frequency domain mixed feature data are optimized and uploaded in a graded mode; a deterministic transmission network is constructed, data transmission priorities of 5G communication and LoRa dual channels are dynamically adjusted according to a network load, and intelligent switching between 5G communication and a LoRa protocol is realized based on a switching decision model; analyzing normal processing data of the whole stage of the processing process, and establishing a processing data thread; and predicting the abnormal processing risk in the processing process, and updating the model parameters. According to the method, the communication and interaction efficiency of the digital twin system in the machining process of the compressor blisk in the aero-engine can be improved.

The invention discloses a static IR Drop intelligent prediction system based on heterogeneous feature fusion, and aims to solve the problems that a traditional IR Drop analysis method is high in calculation complexity and an existing deep learning method cannot effectively capture global spatial features and unit instance topological information of a power transmission network (PDN). According to the framework, double branches of a convolutional neural network (CNN) and a graph neural network (GNN) are combined, and effective extraction and feature fusion compensation of PDN multi-scale global to local space power features are realized through a long-distance and local detail encoder (LLE) and a hierarchical and adjacent compensation group (HACG) module of the CNN branches; pDN topological features of heterogeneous neighbors of different orders are adaptively aggregated through a unit instance voltage aware (CVA) module of a GNN branch. Experimental results show that compared with an existing advanced method, the framework has remarkable advantages in prediction precision, and prediction errors are greatly reduced.

The invention belongs to the technical field of power supply transmission, and relates to a POE-POF power supply transmission method and system, and a storage medium. The method comprises the following steps: collecting electric quantity data of POE-POF power supply transmission network nodes in real time, and extracting a dynamic power feature set; identifying an abnormal power loss event based on the feature set and extracting an abnormal mode feature; abnormal path nodes are positioned by combining a POE-POF power supply transmission network topological structure, voltage and current distribution parameters are optimized, and an optimized power distribution scheme is generated; dynamically adjusting voltage and current values of a power supply path, evaluating an energy consumption trend and generating a trend data set; and adaptively adjusting the electric quantity acquisition parameters according to the energy consumption trend, updating the acquisition configuration and circularly executing the steps. According to the invention, intelligent detection, accurate positioning and dynamic optimization of abnormal loss of the power grid are realized, the stability and energy efficiency of the power supply network are improved, and the method is suitable for fine management and energy-saving optimization of the intelligent power grid.

The invention discloses an anti-interference method for electric power data acquisition communication equipment, which comprises the following steps of: constructing an electricity utilization information transmission network, setting electricity utilization acquisition nodes, and acquiring electricity utilization information of the electricity utilization acquisition nodes through the electricity utilization information transmission network to obtain electricity utilization acquisition information; continuously detecting the collected signal power to judge whether the network is interfered, if the network is interfered, extracting various characteristics of an interference signal from a time domain and a frequency domain, and realizing identification of an interference type by using a support vector machine model; the communication error rate is calculated by cognizing the type, power and frequency band parameters of interference suffered by current communication, interference offset and spectrum spreading are selected according to the type and number of the interference, and the error rate is reduced, the invention further discloses a corresponding system, and belongs to the technical field of electric power data acquisition. A more reliable technical guarantee is provided for electric power information acquisition and transmission in an intelligent power grid, and the acquisition and transmission efficiency of the electric power information can be optimized.

The invention provides a transient voltage stability control method and system based on transmission and distribution cooperation. The method comprises the following steps: constructing a power distribution network reactive power support capability quantification model; quantizing a reactive power support capability boundary in real time by solving a power distribution network reactive power support capability quantification model, and determining a reactive power support power feasible region capable of being provided; and based on a quantitative evaluation result, dynamically adjusting a reactive power interaction value between the power transmission and distribution networks by adopting an improved droop control strategy, and realizing power transmission network transient voltage stability control based on active support of the power distribution network. Power distribution is carried out according to the dynamic reactive power margin of the reactive power regulation equipment by considering the transient voltage support requirement of the power transmission network and the reactive power transmission loss of the power distribution network; and obtaining a reactive power regulation instruction, and coordinating reactive power resources at the power distribution network side according to transient voltage stability control and power distribution of the power transmission network to realize cooperative control. Based on the method, the invention further provides a transient voltage stability control system based on transmission and distribution cooperation. The optimal transient voltage support is provided for the power transmission network.

The invention provides a voltage control strategy modeling and voltage online regulation and control method and system for a power distribution network, and is applied to the technical field of power distribution network regulation and control. The method comprises the steps that region division is carried out on the power distribution network based on the electrical distance between nodes of the power distribution network, multiple regions are obtained, and one region corresponds to one virtual power plant; determining the regional electricity price of each region based on the marginal pricing of the distribution region; taking each region as an object of energy transaction with the power transmission network, and constructing an optimization model by taking profit maximization of each region as a target on the basis of considering the safety of circuit elements in each region; performing optimization strategy modeling on the optimization model based on an observable Markov decision process to obtain an optimization strategy model; and training an optimization strategy model based on the regional electricity price of each region and a maximum entropy reinforcement learning algorithm. The method solves the problem that the complexity of the power distribution network affects the optimality and efficiency of the collaborative optimization problem of a plurality of virtual power plants in the power distribution network.

The invention discloses a low-altitude meteorological early warning method and system based on the Internet of Things, and relates to the technical field of low-altitude flight traffic control, and the low-altitude meteorological early warning method comprises the steps: arranging a plurality of Internet of Things sensor devices in a low-altitude flight region, and collecting meteorological data in real time, including temperature, humidity, wind speed, air pressure and the like; uploading the collected meteorological data to a cloud server by using a data transmission network; performing real-time analysis and prediction on a low-altitude meteorological condition in combination with a meteorological prediction model and historical big data; and when abnormal or potential dangerous meteorological conditions are detected, early warning information is sent to related users through multiple communication modes. According to the invention, the accuracy and timeliness of low-altitude meteorological early warning are improved, and the safety of air traffic in low-altitude flight is effectively guaranteed.

Transport networks, network elements, and methods of use are described herein, including a transmitter comprising a client-side input, transmitter circuitry, and antennas. The client-side input is configured to receive baseband signals having client data encoded therein. The transmitter circuitry is configured to receive the baseband signals from the client-side input and generate antenna feed signals based on the baseband signals. The antennas are configured to receive the antenna feed signals from the transmitter circuitry, generate radiated signals based on the antenna feed signals, and couple the radiated signals into a hollow waveguide. Each of the radiated signals is a radiated electromagnetic wave configured for coherent detection and has a frequency in a range between 300 Gigahertz (GHz) and 10 Terahertz (THz).

The invention is applicable to the technical field of power distribution network monitoring, and provides a power grid monitoring-oriented power adaptive congestion control method, which comprises the following steps of: acquiring a network performance index and a power grid operation parameter of a power grid monitoring data transmission network, and determining a congestion state of a current network through a preset congestion evaluation model; a 5G ad hoc network node connection strength coefficient, a new energy monitoring data priority label, a west-to-east transmission channel power flow fluctuation coefficient and a regional vulnerability index are used as decision variables, and the minimum weighted transmission delay, the packet loss rate and the maximum new energy consumption responsivity are used as objective functions. Generating a control strategy corresponding to the current network congestion state according to the hybrid intelligent optimization model fusing reinforcement learning and a genetic algorithm; executing the control strategy to dynamically adjust the network resources; monitoring the execution effect of the control strategy, and feeding the result back to the model to update the parameters; and therefore, the requirements of multi-target optimization and differential service quality in a complex power grid monitoring scene can be met.

The invention relates to the technical field of telecommunication. By providing the multi-domain strategy collaborative dynamic decision optimization method, system, equipment and medium, the method comprises the following steps: extracting cross-domain common characteristics of network layer topology, equipment state and alarm information, retaining differential characteristics of a transmission network and a data network, and generating a uniform resource data set; on the basis of the unified data set, a global optimization strategy is generated through linkage decision making of a three-level collaboration module; matching the strategy into an atomic instruction set executable by a heterogeneous network manager by utilizing semantic ontology mapping and syntax tree matching; and according to the instruction execution feedback data, dynamically adjusting the strategy weight and carrying out iterative optimization, and generating an updated global strategy, so as to achieve the technical effects of improving the cross-domain resource perception precision, enhancing the hierarchical decision collaborative efficiency and reducing the multi-manufacturer instruction conversion error rate.

Sidelink positioning of user equipments (UEs) is supported by exchanging sidelink positioning messages between the UEs, where the messages may include sidelink positioning capabilities, sidelink positioning resources, sidelink Positioning Reference Signal (PRS) configurations, sidelink measurements and / or location results for one or more of the UEs, and may be used for determining the location results. Location results may include ranges, directions, locations, velocities, relative locations and relative velocities. Groups of UEs may be formed for sidelink positioning based on group criteria parameters that are used for determining UE inclusion or exclusion in a group, in a centralized or distributed group management procedure. Group management may additionally remove and add UEs and transfer UEs between groups. Network supported sidelink positioning may transfer sidelink positioning messages between a UE and a location server where a sidelink positioning message may be embedded in an LPP and / or SUPL message.

The invention relates to a supplier behavior real-time sensing and monitoring method and device and electronic equipment. The method comprises the steps of collecting and preprocessing supplier multi-source heterogeneous data in real time, dynamically capturing a Binlog of a MySQL database through a Flink CDC framework, obtaining service behavior data in real time, collecting text log data through a Flume framework, and transmitting network behavior data in real time. Integrating the structured data, the unstructured data and the semi-structured data, and constructing a unified data transmission channel; constructing a multi-dimensional user portrait; comparing the semantic similarity between the bidding file and the bidding requirement, and triggering compliance early warning when the matching degree is lower than a threshold value; analyzing a supplier cooperation network, and marking a cluster group with abnormal transaction frequency and irrelevant business fields as a cross-bidding risk; and analyzing the access behavior sequence, and detecting a malicious access pattern to generate a malicious access alarm. According to the supplier behavior monitoring system and method, real-time performance, accuracy and multidimensional performance of supplier behavior monitoring are achieved through the architecture of multi-source heterogeneous data real-time integration, multi-dimensional portrait construction and intelligent risk identification.

The invention discloses a flood risk propagation assessment method, device and equipment and a storage medium, and the method comprises the steps: calculating a flood risk value of each sub-basin in a research region according to an obtained flood risk assessment index variable of the research region; grading the flood risk value to obtain a flood risk grade of each sub-basin in the research area; constructing a Markov chain space-time model; determining a flood risk space-time propagation rule according to the Markov chain space-time model; fitting a flood risk propagation function according to a flood risk space-time propagation rule; according to the flood risk propagation function, the flood control water conservancy project operation information data and the historical flood data, determining a flood risk transfer blocking effect of the flood control water conservancy project; constructing a flood risk space-time propagation network model with a space-time dependency relationship; and according to the flood risk space-time propagation network model, evaluating the research area to obtain a flood risk propagation evaluation result.

A method for supporting virtual machine (VM) mobility between network devices connected to a network includes: selecting a first type of route for interconnecting VMs that are connected to the network devices; and adding a feature of a second type of route to the first type of route to enable the network devices to execute proxy address resolution protocol (ARP) for transmitting network traffic between the VMs without requiring each of the network devices to store a physical address of each of the VMs in respective ones of a network address table.