18 results about "Survivability" patented technology

The invention relates to a multi-master election method and device based on an OpenHarmony soft bus, and the method comprises the steps: constructing six efficiency indexes according to the networking characteristics of the soft bus; operating system kernel state extraction: increasing a subsystem in an operating system layer, expanding system capability, obtaining index data of each device in a network in real time, storing the index data in a distributed database, and extracting required data from the distributed database by a multi-main election component to calculate and lift the device; performing analytic hierarchy process index weight construction and election formula derivation: establishing an efficiency index score system through an analytic hierarchy process, and calculating the weight of each index at the level to which the index belongs; and after the weights are determined, performing corresponding fuzzy judgment on each index by using a fuzzy comprehensive judgment method from the bottom-layer index, and finally obtaining a judgment score. According to the invention, the problem that the traditional open-source soft bus solves the problem that the single-center networking survivability of the traditional soft bus is insufficient is solved.

This invention proposes a method for assessing the resilience of heavy platforms based on the DA-PSR model and complex networks. Taking heavy platforms as the object, an objective resilience assessment system is constructed. An assessment index system with causal relationships is established, and a screening method for the assessment index system based on node betweenness values ​​in complex network theory and the k-means algorithm is proposed. This results in a simplified assessment index system where the remaining node betweenness values ​​account for 52.99% of the total betweenness values ​​and the remaining cluster center values ​​account for 90.55% of the total cluster center values. An index weighting method based on mutual information theory and an index calculation method based on extreme damage quantification are proposed. The PSR framework theory is improved through dimensional analysis, and a resilience DA-PSR assessment model is constructed. Considering the performance requirements driven by tasks, a criterion quantification and dynamic grading method based on task requirements is proposed. The assessment shows that a heavy platform with a resilience assessment value of 0.7373 exhibits different assessment levels of "excellent," "medium," and "poor" under different tasks.

The invention relates to the technical field of cloud computing and edge computing, in particular to a multi-cloud cooperative system based on edge computing. Comprising a data acquisition module for acquiring communication characteristic parameters and a current control topology state; the first processing module is used for identifying intermittent communication disturbance and calling a digital twinborn model to predict and control topological entropy increment; the second processing module is used for determining a lagging failure risk value for keeping the current control right affiliation unchanged; the third processing module is used for calculating an entropy increase-risk ratio for measuring the survival stability of the system; and the cooperative control module is used for generating a degradation operation instruction for switching the control node or maintaining the current connection based on a comparison result of the entropy increase-risk ratio and a survival threshold value. According to the method, routing oscillation and control right split brain are effectively avoided, physical collision accidents are prevented, and the survival probability of the system in a severe network environment is improved.

The present technology provides solutions for maintaining communications within a software-defined wide area network (SDWAN) when one or more devices in the SDWAN are isolated from one or more controllers. An example method includes receiving, at a static edge device associated with a static wide area network (WAN) Internet Protocol (IP) address in a data plane of the SDWAN, data from a first device communicating through an edge device of a first Internet service provider (ISP) of the SDWAN, where the first device is associated with a private IP address, associating, by the static edge device, the first device with the private IP address, and communicating, by the static edge device, with the first device at the private IP address. Systems and computer-readable media are also provided.

The invention discloses a cloud platform survivability assessment method, system and device and a medium. Comprising an acquisition module, a first determination module, a second determination module and a third determination module. The acquisition module acquires component information of each component in the cloud platform; the first determination module determines an autonomous controllable degree evaluation result of each component based on the component information; the second determination module determines the limit survival state level of the cloud platform based on the evaluation result; and the third determination module integrates the minimum cloud state of the cloud platform and the limit operation survivability evaluation result based on the level to obtain the survivability evaluation result of the cloud platform. According to the method, the evaluation indexes are extracted from the supply chain and the research and development production dimension, the evaluation range of the survivability of the cloud platform is expanded, the influence of the extreme environment on the cloud platform and the limit survival difficulty are comprehensively revealed, the survival feasibility and the survival quality of the cloud platform in the extreme environment are accurately determined, and the method has higher evaluation accuracy.

The invention discloses an unmanned aerial vehicle autonomous flight control method and system based on multi-vehicle cooperation and dynamic airspace distribution, and relates to the technical field of unmanned aerial vehicle autonomous flight control. According to the invention, a flight control processing strategy of a preset rule is adopted, each unmanned aerial vehicle has an autonomous decision-making capability, a single-point fault problem of a traditional centralized architecture is effectively overcome, even if part of nodes have faults, the system can still maintain stable operation, and the reliability and the survivability are significantly improved; according to the method, an airspace unit model mechanism is introduced, a basic unit of resource allocation is converted from a path line to an airspace unit, essential change of a flight path is realized in space and time dimensions, the mechanism can prevent conflicts fundamentally, and compared with a traditional method, the method has remarkable advantages.

The invention discloses a distributed unmanned cluster cooperative control system, which belongs to the technical field of unmanned system cooperative control, and comprises a heterogeneous cluster composed of various types of unmanned platform nodes, and the cluster comprises an unmanned aerial vehicle node, an unmanned ship node and an unmanned underwater vehicle node; the intelligent control units run on the unmanned platform nodes in a distributed manner and are used for realizing autonomous decision making and local collaboration of the platform; and the dynamic self-organizing communication network is connected with each node in the cluster and is used for realizing information interaction among the nodes. The system provided by the invention has extremely high robustness and survivability, a decentralized architecture eliminates single-point faults, failure or interference of partial nodes does not affect the core function of a cluster, the system is particularly suitable for an adversarial or severe environment, and a distributed task market mechanism enables tasks to be dynamically matched to the most suitable platform, so that the system has high robustness and survivability. The overall operation efficiency and the resource utilization rate are improved, and the cooperative logic of heterogeneous platforms such as air, sea and underwater platforms is effectively unified through a standardized task interaction protocol.

The invention provides a method and device for obtaining evaluation parameters, equipment and a storage medium, and relates to the technical field of information. According to the specific technical scheme, the method comprises the steps of obtaining time sequence index parameters of a target mechanism in historical duration; the time sequence index parameter comprises a first characteristic parameter and a second characteristic parameter of the target mechanism at a plurality of historical moments within a preset historical duration. And processing the time sequence index parameter through a multi-task prediction model to obtain a predicted first feature parameter and a predicted second feature parameter of the target mechanism. And processing the predicted first feature parameter and the predicted second feature parameter through a preset evaluation model to obtain an evaluation parameter of the target mechanism. The evaluation parameter is used for indicating the continuation value of the target mechanism at the current moment. The preset evaluation model has the capability of determining the survivability value of the target mechanism based on the predicted first feature parameter and the predicted second feature parameter. The obtained evaluation parameters can be more objective and better fit the actual performance of the mechanism.

The present invention provides a method and device for evaluating the survivability of unmanned marine systems based on complex networks. The method comprises: A, judging whether all typical survival models A in the survival situation diagram of the current j-layer system are δ Indicates that they all exist in the situation diagram. If they exist, go to B. If they do not exist, record the first stage identification stop layer information as γ layer and go to C. B, according to A δ Perform model recognition and extraction on the survival situation diagram of the j-layer system, extract the recognition results to the j+1 layer, and return A; C, determine whether there is one or several A in the survival situation diagram of the current γ+k layer system δ If it exists, go to D. If it does not exist, record the number of layers increased by the second-stage recognition stop layer γ+k relative to the first-stage stop layer γ as the second-stage recognition layer number information β and go to E. D, according to A δ Perform model recognition and extraction on the survival situation diagram of the γ+k layer system, extract the recognition result to the γ+(k+1) layer, and return it to C; E to obtain the system survivability assessment result W.

The invention discloses a USV combat strategy optimization method and system based on a dynamic game, and relates to the field of analog simulation. Comprising the steps of S1, constructing a comprehensive USV state space, determining constraint conditions of an action space and designing a reasonable revenue function, S2, comprehensively considering weapon stock and maneuvering characteristic limitation, and determining the USV action space and the constraint conditions of the USV action space, S3, dynamically constructing a particle speed updating formula according to ocean adaptability and communication network performance, and S4, judging whether the USV combat system reaches the hybrid Nash equilibrium or not by comparing income differences under different strategies, providing an effective convergence judgment basis for combat decision, and optimizing the combat strategy. Through the method and the system, the limitation of a traditional method can be broken through, a more scientific and efficient combat strategy is formulated for the USV, and the combat effectiveness and survivability of the USV in the modern sea battle are improved.

This invention provides a method to improve the survivability of domestically produced ruggedized computers in complex electromagnetic environments, relating to the field of electromagnetic protection technology for ruggedized computers. The method includes acquiring the computer's topology and electromagnetic parameters; establishing an electromagnetic energy flow network to identify high-risk areas; designing a multi-layered heterogeneous material non-uniform shielding structure and an energy flow guiding structure; adjusting the physical parameters of the filtering unit; setting up a hybrid grounding network; and configuring protective coordination parameters. This invention improves the survivability and reliability of computers in complex electromagnetic environments through precise electromagnetic energy guidance and multi-layered protection.

The invention belongs to the technical field of cluster unmanned aerial vehicle task allocation. The invention provides a task allocation method based on dynamic dual modes. According to the embodiment of the invention, through group-group-machine three-level role definition, hierarchical management of task coordination is realized, the system complexity is reduced, and the command efficiency is improved. And the group head and the group leader support a dynamic selection mechanism, so that system paralysis caused by failure of the central node is avoided, and the survivability of the system in high-confrontation environments such as a battlefield is improved. After the task is released, a distributed auction algorithm is preferentially adopted to carry out rapid negotiation, so that the real-time performance is ensured; if tasks are not allocated overtime, a centralized particle swarm algorithm is started for global optimization, and efficiency and optimality are both considered. Priorities of tasks are set according to attributes, bidding weights are dynamically adjusted according to the priorities in an auction algorithm, and reasonable resource scheduling is achieved. Task information is stored in a structured mode, the state is updated in real time, multi-task parallel management and cross-group coordination are supported, and the overall task throughput of the system is improved.

The subject of the application is a multi-engine coordinated artificial intelligence system with fractal architecture, precious metal denomination and session survivability protocol.A system for coordinating N commercially available artificial intelligence (AI) models from different vendors into one coordinated product consists of: (a) N AI engines from at least three different vendors operating at the consumer tier, where the cost of a single engine does not exceed $20 per month or is free of charge, (b) a central human node (N+1 engine) acting as a decision router orchestrating the flow of tasks between engines, (c) a complete K_N graph of emergent specialized connections between AI engines, where each pair of engines has a defined functional specialization, and (d) the emergent value of the system (capability / cost ratio) exceeding the sum of the values ​​of the individual components (superlinear scaling), with the total operating cost of the system not exceeding 1 ounce of silver per month at enterprise-grade capability.

The invention discloses an information physical cross-layer game three-party satellite confrontation method and system, and the method comprises the steps: constructing a motion model and a communication interference model of a maneuver-limited attacker-defender-communicator three-party non-cooperative satellite, and constructing a three-party optimal control problem; in consideration of energy consumption of three parties, communication interference efficiency of an information layer and pursuit behaviors of a physical layer, an optimal control problem of an attacker, a defender and a communicator is converted into a round system game problem and is decomposed into a series of simpler unilateral optimization sub-problems, a multi-targeting method is adopted to solve an optimal strategy, and the optimal control problem of the attacker, the defender and the communicator is solved on the premise of meeting a safe distance. In order to realize efficient solving of a cross-layer three-party strategy, an information-physics coupling system is constructed, a Stackelberg game idea and a multiple targeting method are adopted, a three-party differential game problem is converted into a turn system game problem, and then a large-scale nonlinear problem is solved, so that efficient solving of the cross-layer three-party strategy is realized. And the interference survival capability of attackers, the accurate interception capability of defenders and the anti-interference communication capability of communicators are improved.

An elastic cooperative inference architecture and method for UAV cluster can dynamically update the scheduling policy according to the status of each node, and can deal with the failure of some nodes. In addition, the elastic cooperative inference architecture and method can process larger scale complex models on the embedded devices with limited performance carried by UAVs by means of cooperative inference, so as to improve the accuracy of intelligent applications. At the same time, the elastic cooperative inference architecture and method can adaptively update the allocation strategy when some nodes are unavailable or recovered, and improve the survivability of UAV cluster through elastic coordination.

The embodiment of the invention provides an survivability test method and system based on a dynamic heterogeneous network, and the method comprises the steps: obtaining target data based on a multi-stage target smart grid; determining target survivability according to the target data; when it is determined that the target survivability is smaller than the preset survivability, executing a target operation to enable the target survivability to be larger than or equal to the preset survivability; wherein the target data comprises the target connectivity, the target fault tolerance, the target attack resistance and / or the target death degree of the multi-level target dynamic heterogeneous network. According to the method and the device, the sensing precision of the state of the dynamic heterogeneous network can be improved, so that the precision of the survivability test of the dynamic heterogeneous network is improved, and the robustness and survivability of the dynamic heterogeneous network are improved.

Systems and methods (50) for hitless readmittance of recovered traffic to a group supporting partial survivability include receiving (52) a plurality of components (16), wherein each component of the plurality of components is a traffic flow having a frequency and phase of associated frame position, and wherein the plurality of components represent an aggregate signal. The methods include equalizing (54) skew of the plurality of components (16); responsive (56) to one or more failed components of the plurality of components, replacing the one or more failed components with an associated replacement signal; and, subsequent (58) to the one or more failed components becoming one or more recovered components, hitlessly readmitting the one or more recovered components by modifying the skew until non-failed components and the one or more recovered components are phase aligned.

The application belongs to the technical field of aircraft terminal countermeasure system design, and particularly relates to an aircraft terminal countermeasure system, which simultaneously covers four links of observation, judgment, decision and execution in an aircraft countermeasure task, and an integrated architecture solves the problem of poor coupling of existing terminal countermeasure sensing and decision technology, shortens the response time of the countermeasure system to external air countermeasure situation changes, and compared with traditional terminal countermeasure technology, is realized based on a deep learning framework, has strong feature extraction and nonlinear mapping capability, and has good generalization capability after training due to a good neural network structure, and is more adaptable to the countermeasure system under complex air countermeasure situation conditions, and greatly improves the survival capability of the aircraft under complex situation conditions.