10 results about "Binary decision diagram" patented technology

The invention discloses a data processing method and device of a data center network, equipment, a medium and a product, and relates to the technical field of data processing, and the method comprises the steps: obtaining network topology information and a data forwarding table rule corresponding to each equipment subnet in the data center network; performing parallel coding on each piece of network topology information and each data forwarding table rule based on a network parallel binary decision diagram to obtain a data forwarding path structure between subnets on each piece of equipment, the network parallel binary decision diagram being generated based on a lockless index and hierarchical cache; based on the path connectivity corresponding to the data forwarding path structure, constructing a data forwarding graph corresponding to the subnet on each device; and verifying the data reachability between the subnets on each device according to the data forwarding graph, and generating a data reachability verification result. According to the technical scheme, the concurrency limitation is overcome, high concurrency can be achieved, and the data plane verification efficiency of the data center network is improved.

The invention relates to the technical field of unmanned aerial vehicles. Particularly relates to an unmanned aerial vehicle cluster multi-stage task reliability analysis method and system, a storage medium and a program. According to the method, a task stage process, a subsystem dependency relationship and reliability parameters are embedded into a SysML architecture model, a fault tree of each stage is automatically generated and converted into a binary decision diagram (BDD), and single-machine multi-stage task reliability calculation is achieved. On this basis, the reliability of the cluster in each stage and in the whole task is evaluated in combination with a k-out-of-n system model and a Monte Carlo simulation method, and the minimum delivery quantity is automatically optimized based on a reliability target. Finally, simulation and optimization results are automatically written back to the MBSE model through a parameter diagram, and design-simulation-decision closed-loop linkage is achieved. The method has the advantages of high modeling consistency, high calculation efficiency, optimal resource configuration and the like, and is suitable for reliability evaluation and optimal configuration of unmanned aerial vehicle cluster tasks in a complex environment.

The invention discloses a human-computer interaction task failure evolution path identification method based on a binary decision diagram, and aims to solve the problem that a task failure path in a complex human-computer interaction system is difficult to accurately identify. The method comprises the following steps: constructing a man-machine interaction task event tree and converting the man-machine interaction task event tree into BDD; determining a top event based on the event tree, constructing a fault tree and converting the fault tree into BDD; integrating the event tree BDD and the fault tree BDD to form a unified BDD corresponding to the ET-FT model; and traversing and identifying a failure evolution path based on the integrated BDD. Unified modeling of static logic and dynamic evolution is achieved through BDD, the causal relationship is quantified by combining Shannon decomposition and the ITE method, and the method has the advantages of being accurate in modeling, efficient in analysis and high in expansibility, can be widely applied to the fields of aerospace, medical equipment and the like and provides support for system reliability optimization.

The invention provides a firewall policy processing method and device, equipment, a storage medium and a program product, and is applied to the field of information security. The method comprises the steps that ni firewall policies of each target device in m target devices are acquired, and each firewall policy comprises a source internet protocol address, a source port number, a destination internet protocol address, a destination port number, a protocol type and a policy action; converting each firewall policy into binary symbol representation; according to ni binary symbol representation, same nodes are merged, a multi-terminal binary decision diagram of each target device is constructed, a source internet protocol address, a source port number, a target internet protocol address, a target port number and a protocol type are represented as intermediate nodes, and a strategy action is represented as a terminal node; performing aggregation operation on the multi-terminal binary decision diagrams of the m target devices, and merging the same nodes to obtain a global decision diagram; and exporting a firewall policy set table according to the global decision diagram.

A program according to one embodiment of the present disclosure causes a computer to execute: a first input procedure for inputting a first nonterminal node and a second nonterminal node on a zero-suppressed binary decision diagram; a second input procedure for inputting at least designation of a first function representing a condition to be satisfied by a set pair of a set included in a set group represented by the first nonterminal node and a set included in a set group represented by the second nonterminal node; and a calculation procedure for executing a set group calculation of the set group represented by the first nonterminal node and the set group represented by the second nonterminal node, on the basis of the first nonterminal node, the second nonterminal node, the first function, and a template of an algorithm for achieving the set group calculation.

Data is encrypted using only first and second stages of only 3-bit gates, that are linear, and non-linear, respectively. Each 3-bit gate for a function is conjugated by the first stage, i.e., straddled with the first stage and its inverse, to form a set of gates that are replaced using a finite set of substitution rules to form an ordered set of daughter gates. The daughter gates are conjugated by the second stage to form for each output bit of each layer of a daughter gate, a binary decision diagram (BDD). A module chip is formed by combining all BDDs for each daughter gate. The obfuscated module is configured by combining the module chips. The obfuscated module is sent to an unsecured device for execution thereon.

Methods and systems for network verification are described. An input binary decision diagram (BDD) is defined to represent an input header space for querying a network property of interest. The input BDD is provided as input to a device-level BDD representing a source device in a logical topology representing connections between devices in the network. Each device in the network is represented by a respective device-level BDD in the logical topology. An output BDD is computed, the output BDD representing an output header space output by a destination device in the logical topology. The output BDD is computed by sequentially applying each device-level BDD in a logical path from the source device to the destination device to the input BDD. The output BDD is then reported and the reported output BDD is compared to an expected output BDD to verify the network property of interest.

Data is encrypted using only first and second stages of only 3-bit gates, that are linear, and non-linear, respectively. Each 3-bit gate for a function is conjugated by the first stage, i.e., straddled with the first stage and its inverse, to form a set of gates that are replaced using a finite set of substitution rules to form an ordered set of daughter gates. The daughter gates are conjugated by the second stage to form for each output bit of each layer of a daughter gate, a binary decision diagram (BDD). A module chip is formed by combining all BDDs for each daughter gate. The obfuscated module is configured by combining the module chips. The obfuscated module is sent to an unsecured device for execution thereon.

The application provides a train control system reliability model construction and analysis method based on operation task division. The method comprises the following steps: determining a plurality of stage sub-tasks of a train according to a train transport organization process and a train operation task; establishing a plurality of stage reliability models of a train control system with the train as the core according to the plurality of stage sub-tasks; constructing a fault tree of a basic task reliability model of each stage, and converting the fault tree into a binary decision diagram (BDD) representation; obtaining a failure path leading to a basic task of each stage according to the BDD representation of the basic task of each stage, and calculating the reliability of the basic task of each stage according to the failure path of the basic task of each stage and a fault distribution of each specific device; and calculating a reliability index of the entire train transport task based on the reliability of the basic task of each stage. The method can process system behaviors under real-time dynamic running of a train, and can also perform reliability evaluation on the entire train running process, thereby providing technical support for efficient completion of a train transport task.

Methods and systems for partial or full distributed network verification are described. In partial distributed network verification, each network device generates a respective device-level binary decision diagram (BDD) that represents the logical behavior of the respective network device with respect to a network property of interest. The device-level BDD from each network device is received by a verification service that performs verification by generating an input BDD that represents an input header space, applying each device-level BDD in a logical path from a source device to a destination device, and reporting an output BDD. In full distributed network verification, each network device is responsible for computing a device-specific output BDD by applying a device-specific BDD that represents the logical behavior of the network device to a device-specific input BDD.