145 results about "Network emulation" patented technology

The invention provides a multi-level service priority dynamic scheduling simulation method and device, a medium and a product. The method comprises the following steps: constructing a priority label system; establishing a dynamic binding relationship between the service flow and the priority label; when a service layer generates a data packet, embedding a priority label for the data packet based on the dynamic binding relationship; extracting a priority label carried by the data packet on a protocol stack MAC layer, and ensuring that the priority label is unvarnished to a lower layer protocol in a lossless manner; and based on the priority labels carried by the extracted data packets, classifying the data packets into logic queues with corresponding priorities, and executing a differentiated scheduling strategy. The method can adapt to diversified requirements of data services of different types and priorities for network resources, effectively improves the simulation model accuracy, improves the simulation experiment efficiency and simulation real-time performance and reliability in a multi-service priority 5G communication network simulation scene, more accurately reflects the performance of a real network, and improves the simulation experience of the 5G communication network. And meanwhile, the simulation platform has higher expansibility and flexibility.

The invention provides a network simulation method, device and system based on digital twinning, and belongs to the technical field of network simulation, and the method comprises the steps: receiving real-time operation data of a physical layer device group in an actual network environment; performing preliminary analysis on the real-time operation data; uploading the real-time operation data and the preliminary analysis result to a network cloud decision platform under the condition of determining that the physical layer equipment group has a fault risk according to the preliminary analysis result; receiving a fault solution issued by the network cloud decision platform; performing simulation test on the fault solution by using a digital twin topology module; and a test result is uploaded to the network cloud decision-making platform, so that the network cloud decision-making platform determines the feasibility of the fault solution. According to the invention, all edge computing nodes are utilized to carry out simulation testing on the fault solution, full-architecture simulation based on the actual network environment is realized, and the deviation between the simulation result and the actual operation condition is reduced.

The invention provides a node allocation method in distributed network simulation, which comprises the following steps: an initialization step: according to a network topology structure of a distributed network, obtaining resource occupation parameters of each simulation node and bandwidth occupation parameters of links between the nodes, and obtaining resource parameters of each physical machine; a combination generation step of generating an allocation combination for allocating the simulation node to the physical machine based on the resource occupation parameter and the resource parameter; a node allocation step: based on the bandwidth occupancy parameter, obtaining the maximum bandwidth occupancy value of each allocation combination in the inter-machine link; and performing simulation node allocation by taking the allocation combination corresponding to the minimum value in all the maximum bandwidth occupation values as an optimal allocation scheme. The invention further provides a node distribution device in distributed network simulation, a computer readable storage medium and electronic equipment.

The invention provides an automation system for network simulation and a computing device, and the automation system comprises a business model automation module, a simulation execution automation module, a simulation analysis automation module, a simulation analysis automation module and a simulation analysis automation module. The business model automation module receives the abstracted topology description and the abstracted traffic description analyzed according to the business model, and respectively generates specific detailed topology description and full traffic detailed description; the simulation execution automation module receives the detailed topology description and the full-flow detailed description, generates configuration information, automatically runs network simulation and accelerates execution; and the simulation analysis automation module is used for automatically capturing and archiving important intermediate results for data analysis. According to the technical scheme, complex simulation configuration tasks can be completed through simple structured configuration change or script parameter option adding execution, meanwhile, simulation efficiency is improved, and automatic, efficient and flexible data processing and analysis capacity is provided.

The invention discloses a virtual-real combined sky-ground multi-domain heterogeneous network cooperative computing simulation system and a virtual-real combined sky-ground multi-domain heterogeneous network cooperative computing simulation method. The system comprises a heterogeneous computing power prototype subsystem, a virtual simulation subsystem, a satellite-borne general computing terminal, a programmable network simulator, a heterogeneous resource management subsystem and a simulation verification system interface. Real hardware computing power characteristics are introduced through a physical board card, large-scale expansion is realized through virtual nodes, and authenticity and large-scale performance of simulation are considered; link parameters are generated according to a high-precision orbit dynamics model, and the fidelity of sky-ground network simulation is greatly improved; based on a mixed container arrangement technology, unified management and intelligent scheduling of sky, air and ground heterogeneous resources are realized, and a powerful platform is provided for verifying an advanced cross-domain collaborative algorithm; one set of system can support various simulation verification requirements of networking routing, task unloading, distributed cooperative computing, constellation cluster management and control and the like, and the research and development cost and complexity are reduced.

A container simulation network system based on a link autonomous agent is composed of a visual interaction module, a control plane module, a network simulation module and a resource management module. The modules perform information interaction and task collaboration through a uniform interface so as to realize automatic construction and management of the simulation network, a two-layer architecture design of network bridge containers and user containers is adopted, and each user container corresponds to one network bridge container; a link autonomous agent module is deployed in the network bridge container and is used for collecting a link state, calculating a performance adaptation degree and executing a scheduling operation bit; the visual interaction module realizes visual monitoring and interaction control of a simulation state; the control plane module is responsible for simulation scene analysis, link parameter generation and global scheduling management; and the network simulation module is responsible for calling a container generation tool to generate a specific container instance and carrying out resource monitoring and adjustment on the container.

The invention relates to a system (10) for emulating a variable-topology network, comprising a controller (20), a switching system (30) and network nodes (40). Each node comprises an emulation module for emulating a physical layer, and an application module with higher-level protocol layers to be tested. During execution of a test scenario, the emulation module of each node is configured to compute instantaneous information concerning the state of the node and instantaneous characteristics of the links from and to the node. The application module of the node is designed to transmit and receive packets via the emulation module, and to route the packets depending on the instantaneous information concerning the node and the links. Each emulation module is configured to control the transmission and reception of packets depending on the instantaneous characteristics of the communication links.

The invention discloses a progressive event-driven synchronous control method, which comprises the following steps of: performing parallel simulation, simultaneously starting a plurality of simulation processes, respectively simulating each core particle in a multi-core particle system, and managing the synchronization among the simulation processes by a global manager; on-demand synchronization: when the core particles simulated by the simulation process are in inter-core-particle communication, the global manager synchronizes the related processes; the process is synchronized, and the global manager ensures that other cross-process communication events earlier than the request are simulated; if a simulation process does not reach the time point, the process initiating the request is suspended by the global manager until the request can be executed; and network simulation and time sequence simulation: when the request can be executed, the global manager starts the inter-chip network simulator and simulates the communication event. According to the method, the accuracy and the operation efficiency of multi-core particle parallel simulation are remarkably improved, and the method is suitable for function verification and performance analysis of large-scale complex multi-core chips.

The invention discloses a malicious traffic confrontation sample generation method based on fine-grained network simulation, and the method comprises the steps: constructing a simulation network through an NS-3 network simulator, and transmitting and receiving malicious traffic of a real application program in a Docker container through a TapBridge mechanism; the method comprises the following steps: collecting network environment parameters, protocol stack state information and data packet header data in real time in a transmission process of malicious traffic in a simulation network; based on a Markov decision process, a state transition diagram is constructed to limit an execution sequence and conditions of confusion actions, confusion operation is performed on malicious traffic in combination with network environment parameters, protocol stack state information and data packet header data which are acquired in real time, a confusion strategy is dynamically optimized in combination with a reward function, and a malicious traffic confrontation sample is obtained. The malicious traffic confrontation sample with excellent escape detection capability is stably generated in a complex dynamic network environment on the premise of ensuring normal communication, and the protocol compliance, the transmission effectiveness and the network environment adaptability of the malicious traffic confrontation sample are improved.

The invention discloses an implementation method of an ad hoc network anti-interference system based on deep reinforcement learning, and the method comprises the steps: 1, constructing a simulation network environment based on a network simulator 3 (NS-3) simulation platform and an OpenAI Gym interface, and enabling the simulation network environment to be used for collecting a channel state in real time and feeding back the channel state to an intelligent agent; and 2, after receiving the network state, the intelligent agent feeds back a decision result obtained by learning to a network node to guide channel switching in real time. And step 3, fusing mechanisms such as a long short-term memory (LSTM) network, a competition network structure, a double deep Q network, a double deep Q network, a prioritized experience replay (PER) and the like, designing a PER-D3RQN algorithm, and carrying out efficient prediction on an interference time sequence rule. According to the method, the accuracy of channel selection can be remarkably improved in multiple interference modes, the network performance and the anti-interference robustness are improved, and the performance superior to that of a traditional deep Q-network (DQN) and a traditional frequency hopping strategy is shown.

The invention relates to the technical field of network simulation, and discloses a distributed network node evolution simulation method and system based on a time-delay grid model. The method comprises the following steps: establishing a spatial distribution time-delay model of distributed network nodes, configuring a dynamic time-delay calculation model for each node, and fusing a real-time physical distance, communication link quality, resource load and packet loss rate; defining a node state evolution rule, and dynamically adjusting an evolution process based on a node state, a historical state and a neighbor node state; a future time delay value is predicted, and simulation deviation caused by time delay is compensated in real time through a PID control mechanism; and constructing a plurality of network environments for simulation, quantitatively analyzing independent influences and comprehensive influences of various delay factors, and optimizing the distributed network based on an analysis result. According to the invention, the accuracy and stability of distributed network simulation can be effectively improved.

The present invention provides a method, device, electronic device and storage medium for realizing a virtualized network, wherein the method comprises: obtaining a file to be virtualized in a target format; the file to be virtualized stores the corresponding field content configured for each device in the network topology diagram to be virtualized; the target format is the corresponding data format when the target network simulation simulator draws and stores the network topology diagram; based on the file to be virtualized, the instance interface of the target network simulation simulator is called, and the network simulation experiment topology diagram generated by the target network simulation simulator using the file to be virtualized is obtained. With this solution, there is no need to perform the topology drawing process and manual configuration process in the network simulation simulator. Even if multiple network simulation experiments need to be carried out, the network simulation experiment topology diagram can be quickly obtained by simply calling the instance interface of the network simulation simulator, thereby improving the efficiency of the network simulation experiment.

The invention relates to the technical field of digital twinning technology and network communication optimization, in particular to a method and a system of a digital twinning network simulation driven NAT (Network Address Translation) optimization engine, comprising the following steps: constructing a virtualization mapping model of a physical network; simulating an NAT (Network Address Translation) process in a digital twin environment through a real-time simulation engine; dynamically adjusting an NAT (Network Address Translation) rule and a load balancing strategy of a physical network based on a simulation result; executing safety protection operation in combination with a machine learning algorithm; the method has the beneficial effects that a digital twinning technology and NAT optimization are deeply fused, and a visual and visual management platform is provided for network management personnel. Management personnel can monitor the network state and the NAT performance in real time through the platform and deeply analyze the network problem root by means of a simulation result, and complex field troubleshooting and manual strategy adjustment do not need to be carried out. Therefore, the difficulty and the cost of network management are reduced, the accuracy and the timeliness of management are improved, and the network management is promoted to develop towards the intelligentization and automation directions.

Embodiments of the present application provide a chip system simulation method and device and related equipment, wherein the method comprises: obtaining connection data of a chip system; the connection data comprises physical connection data, which is formed based on the physical connection relationship between each chip in the chip system; performing chip system power network simulation node extraction on the physical connection data, and constructing a power network structure of the chip system based on the extracted power network simulation nodes; and simulating the chip system based on the power network structure. The technical solution provided by the embodiments of the present application can improve the reliability of the pressure drop electromigration simulation result.

The invention provides a financial industry low-code platform development method and system based on credential adaptation, and relates to the technical field of credential industries, and the method comprises the steps: 1, mapping interactive interfaces of a core business entity and three associated business entities into four control points in a three-dimensional business topological space, so as to determine a continuous business curved surface, and calculating the normal vector directions of the continuous service curved surface at the four control points, adjusting the connection strength and the data flow direction between the service entities corresponding to the four control points according to the included angle relationship between the normal vector directions of the four control points, and constructing the closed service object network. According to the method, the business network, the simulation model and the adaptation assembly of the credential creation adaptation are constructed, the reusable assets are formed, low-code visual arrangement and credential creation environment full-process testing are combined, efficient development, asset reuse and stable landing of the financial industry credential creation adaptation application are achieved, and business process compliance and system operation reliability are guaranteed.

This invention relates to the fields of network security and network simulation technology, and discloses a method for reshaping malicious traffic based on feature serialization. By collecting traffic data from the target network environment, serialized features of load and time intervals are extracted, and session flow features are further statistically obtained. Then, based on Pareto, normal, log-normal, and Poisson probability distribution models, serialized features conforming to the target network traffic characteristics are generated, and the probability distribution model with the highest similarity to the target network traffic is selected by calculating Euclidean distance. Finally, based on this model, the load and time interval sequences of malicious traffic are reshaped to generate network attack traffic that is difficult to detect. This invention effectively improves the concealment of malicious traffic, making it more difficult for existing detection systems to identify; the generated malicious traffic can effectively test and evaluate the capabilities of network intrusion detection systems.

The invention provides an RPKI deployment influence assessment method and system based on virtual-real combination network simulation, and relates to the technical field of network communication security. The method specifically comprises the following steps: constructing a dynamically configurable high-fidelity network simulation environment based on a network simulation platform, a public internet data source, a routing protocol suite, an RPKI tool suite and a load test tool suite; constructing a data collector outside the network simulation environment, and carrying out protocol data collection, network flow collection and index data collection; and starting an abnormal event, and carrying out ROV verification analysis based on a Patricia tree and anomaly detection based on combination of K-Sigma and mode matching according to the collected data. According to the technical scheme, the potential influence of any ROA change can be accurately simulated, and the efficiency and accuracy of ROV verification analysis and the accuracy of abnormal event monitoring judgment during large-scale ROA deployment are improved.

The invention provides for testing large-scale networks such as data centres by providing a test environment comprising network emulation platforms (NEPs) emulating switching fabric and testing physic

This application relates to a method, system, and medium for simulating the physical layer of an underwater acoustic network in a network simulator. It includes: a mirror event scheduler monitoring transmission events at the physical layer; when any node triggers a transmission event, the mirror event scheduler adds the transmission event to a preset micro-batch buffer for buffering; when preset conditions are met, the mirror event scheduler performs micro-batch aggregation processing on all current transmission events in the micro-batch buffer; the mirror event scheduler generates a transmission signal based on the micro-batch aggregation result; the mirror event scheduler generates an uplink parameter file based on the transmission signal and sends it to the channel simulation end; the channel simulation end determines the target channel impulse response; the channel simulation end generates a downlink parameter file based on the target channel impulse response and the transmission signal and returns it to the network simulation end; the mirror event scheduler in the network simulation end processes the corresponding reception events based on the downlink parameter file. This application can avoid the interference underestimation and collision misjudgment caused by traditional packet-by-packet processing.

The invention discloses an efficiency evaluation method and system based on air-ground integrated network analogue simulation confrontation, and relates to the technical field of network simulation and efficiency evaluation. The method comprises the following steps: constructing a space-ground integrated network topology simulation model by using a simulation engine; injecting a confrontation event, and simulating a confrontation scene; collecting network performance index data in the confrontation scene; on the basis of the collected index data, a weighted average method is adopted, and project weights included in all levels in a pre-constructed two-level performance evaluation system are utilized, a second-level score is firstly calculated, and then a first-level score is calculated on the basis of the second-level score; based on the score of the first level, utilizing a fuzzy evaluation method to obtain a fuzzy efficiency level of the space-ground integrated network; and taking the score of the first level and the fuzzy efficiency level as an efficiency evaluation result. According to the method, accurate reproduction of a multi-dimensional dynamic scene and closed-loop integration of simulation evaluation can be realized. And meanwhile, a multi-algorithm fusion method is adopted, so that the accuracy and robustness of evaluation are improved.

This application relates to real-time high-speed clock signals for industrial network simulation. An industrial simulation system exchanges data between a virtualized industrial system and an industrial controller at high frequency and high accuracy without requiring additional network simulation hardware. Rather than using an operating system clock to time the sending of simulation device data packets from the simulation system to the industrial controller, the simulation system uses the arrival event of a data packet received from the industrial controller as a driving clock signal for sending data packets from the virtual system to the controller. Using the arrival time of a data packet from the industrial controller as a clock signal rather than the operating system's system clock can produce high-accuracy, low-jitter data exchange during simulation.

The invention is suitable for the technical field of network security, and provides a network simulation platform tree structure model topology-based arrangement display method and system, and the method comprises the steps: obtaining target service region information in response to a frame selection operation, and then traversing a topological graph, according to the method, neighbor parent-level service area information and neighbor child-level service area information are quickly determined, then related identifiers are updated based on the neighbor parent-level service area information, finally hierarchical structure tree information is effectively generated, and folding events and unfolding corresponding to service areas and hierarchical structure tree child nodes are continuously monitored. According to the method and the device, the nodes can be divided and the combined topology with the tree structure model can be constructed during simulation topology scene arrangement, so that the structure association relationship of the topology can be more intuitively and clearly embodied for a user, the method and the device have the advantages of friendly interactive display and support of multi-level nesting, and the use experience of the user is greatly improved.

The invention relates to a verification system and a verification method for a security protection application. The system comprises a network attack simulation engine and verification equipment, the network attack simulation engine is connected with the verification equipment through a network; the network attack simulation engine comprises a behavior mapping module, a logic mapping module, a three-link linkage module and a zero-day effect substitute module; the behavior mapping module is respectively connected with the logic mapping module and the three-link linkage module; and the logic mapping module is connected with the three-link linkage module. According to the verification system, through the zero-day effect substitute module, the verification system of the security protection application can simulate and test the influence of unknown vulnerability attacks under the condition that no real vulnerability codes exist, and the coverage of network simulation attacks of the verification system of the security protection application is improved; the verification system of the security protection application ensures that the defensive performance of the security protection application can be comprehensively evaluated when the network simulation attack is coped with through the linkage of the network attack simulation engine and the verification equipment.

The invention belongs to the field of satellite network security, and discloses an attack and defense drilling system construction system and method based on a satellite network terminal side target range, and the system comprises a firmware vulnerability mining module, a satellite network simulation module, an attack generation module, a drilling verification module, and a threat intelligent portrait module. And attack and defense drilling is completed through the attack and defense drilling system. According to the method, high-precision verification and quantitative evaluation of the security risk of the satellite network terminal side can be realized through combination of the satellite-ground integrated simulation environment and the firmware vulnerability-driven attack drilling.

The invention discloses a network simulation method, device and equipment based on digital twinning and a medium. The method comprises the following steps: carrying out initial simulation deployment of a target network on a pre-constructed three-dimensional digital scene containing a virtual entity; acquiring multi-source state data of a corresponding physical entity in real time, so as to drive the virtual entity to move in the three-dimensional digital scene in real time through the multi-source state data, and acquiring virtual state data of the virtual entity, so as to update channel parameters of a target network in real time according to the virtual state data; and driving a target network to operate through the channel parameters, continuously monitoring performance data of the target network, and optimizing the target network according to the performance data to realize network simulation. According to the method, the accuracy of a network simulation result can be improved by constructing a network digital twin environment interacting with a real physical world in real time.

The application relates to the technical field of computing power scheduling, in particular to a computing power scheduling method and system applied to a large-scale network simulation system.The method comprises the following steps: acquiring a resource occupation state information set of all computing power nodes; constructing a task queue of all computing power nodes; setting deep reinforcement learning parameters and initializing a neural network; interacting with the environment to generate experience samples by taking the computing power node as an agent; training the neural network by using a deep reinforcement learning method to obtain a preliminary task scheduling strategy; further optimizing the preliminary task scheduling by using an ant colony algorithm to obtain a final task scheduling strategy; and scheduling simulation tasks by using the final task scheduling strategy.In the task scheduling, not only the real-time resource state of the computing power node is considered, but also the particularity of the task, the priority of the task and the dependency relationship between the tasks are considered, so that the utilization efficiency of the computing power is improved, and the simulation time is reduced.

This invention provides a modeling method and simulation system for complex mobile communication networks, belonging to the field of communication network simulation technology. The system includes a communication network model initialization module, a scenario data parsing module, a communication network state update module, a communication network model data management module, a communication link connectivity calculation module, a communication link seed edge selection module, a classical graph theory algorithm module, and an information communication performance calculation module. This invention first uses a seed edge algorithm to select the primary link, reducing redundant communication links to backup links. Then, it uses a classical graph theory algorithm to abstract the communication network in operation into a weighted undirected graph, thus simplifying, abstracting, and modeling complex mobile communication networks, reducing the complexity of topology analysis, and simplifying communication network solution. This invention supports communication performance calculation during the simulation process, effectively meeting the needs of communication network models in the simulation field.

The invention provides an interactive drilling system and method for a shipping network security simulation environment, and relates to the field of network security. The simulation environment layer is used for constructing a high-fidelity shipping network simulation environment, integrating a ship communication protocol simulation module and a key service system virtualization module, generating a standardized data stream and simulating a real shipping network operation state; the cooperative control layer is used for supporting parallel operation of multiple roles in a unified virtual environment and executing a preset task based on a task-driven multi-user cooperative platform; attack behaviors and system responses are dynamically generated through a real-time event triggering mechanism, and interactive drilling is achieved; the multiple roles comprise commanders, technicians and red and blue confrontation teams; the interaction feedback layer is used for realizing a real-time event triggering and dynamic feedback mechanism, and dynamically adjusting attack intensity, a response strategy and drilling difficulty according to behavior performance in a drilling process; a drill evaluation report is generated through behavior data analysis, and key indexes are quantified.

The invention discloses a test system for a remote diagnosis platform. The test system comprises an upper computer, a programmable power supply, a CAN network simulation board card and an entity ECU (Electronic Control Unit), such as a TBOX and a gateway, wherein the upper computer is used for locally running a remote diagnosis platform and a test program; the programmable power supply is used for supplying power to the entity ECU; the CAN network simulation board card is used for simulating a real vehicle network environment; the entity ECU is used as a test object, the TBOX and the gateway are connected through a plurality of diagnosis CAN network segments, and each diagnosis CAN network segment is provided with a plurality of virtual controller nodes. According to the invention, a rack system is established, a core controller related to remote diagnosis is subjected to physical carrying, other controllers are virtualized, and interaction is carried out by establishing a controlled simulation model, so that multi-dimensional system-level testing is carried out on the whole remote diagnosis platform; and full coverage of fault code reading and fault code simulation and reporting scenes of multiple controllers can be realized.

The invention provides a model training method and device, a network simulation method and device, equipment and a medium, and is applied to the technical field of wireless communication, and the method comprises the steps: inputting the state data of a first sample cell into a pre-trained first comparison learning model, and obtaining the state features of the first sample cell; inputting the geographical environment picture data of the first sample cell into a pre-trained second comparison learning model to obtain geographical environment characteristics of the first sample cell; inputting the state feature, the geographical environment feature and the simulation time data of the first sample cell into an initial diffusion model, and obtaining a prediction performance index based on the simulation time data through the diffusion model; and training the diffusion model based on the predicted performance index and the actual performance index to obtain a trained diffusion model. According to the method, the efficiency of the whole network simulation process can be improved by comparing the general characteristics of the cells extracted by the learning model.