12 results about "Maximal independent set" patented technology

The invention discloses a quantum-classical collaborative wireless link scheduling optimization method based on a divide-and-conquer QUBO model and inverse non-adiabatic driving, and belongs to the technical field of quantum computing and wireless communication. According to the method, link interference in wireless communication is modeled into a conflict graph, namely, vertexes represent links, interference represents edges, utility functions on the links represent weights of the vertexes (numbers on the left of the vertexes are numbers of the vertexes, and numbers on the right of the vertexes are weights of the vertexes), and optimal wireless link scheduling is a weighted maximum independent set (WMIS) on the conflict graph. According to the method, a divide-and-conquer QUBO model is provided, the whole space is divided into Dicke state subspaces with different Hamming weights, XY-Mixer is adopted as a hybrid operator, and evolution of QAOA in the subspaces is limited. On the basis, a DQAOA algorithm is provided; a greedy algorithm and an expanded Lov-alpha-sz positive semidefinite plan are called to obtain a lower bound and an upper bound of a WMIS solution respectively; an anti-non-adiabatic driving item is introduced to modify a QAOA evolution formula, an XY-Mixer angatz is matched to enable the algorithm to be subjected to parallel evolution in a subspace, convergence is accelerated, and an optimal wireless link scheduling scheme is obtained.

The present invention relates to a method for solving a maximum-independent-set problem using a Rydberg quantum wire. The Rydberg quantum wire is an auxiliary wire atomic chain for synthesizing a wire graph G0+W from an initial graph G0 and mediating interactions between distant atoms. The present invention makes it possible to easily approach the MIS problem of non-planar or high-degree graphs.

The embodiment of the invention provides a traffic scheduling method in a time-sensitive network and related equipment, and belongs to the technical field of communication networks. According to the method, a TSN scheduling problem is modeled as a maximum independent set solution problem on a dynamic conflict hypergraph, and decoupling of accurate constraint and efficient solution is realized by maintaining a double-graph structure of a reference hypergraph and a sparse working hypergraph. And dynamically maintaining the working hypergraph quality by adopting a semi-static sparse strategy combining global reconstruction based on semi-definite programming and heuristic local updating. The resource occupancy index is utilized to realize nearly linear increment construction of the conflict hypergraph, and approximate optimal scheduling is quickly solved on the working hypergraph through a flow sensing parallel greedy algorithm. And finally, the feasibility of the scheduling scheme under accurate constraint is ensured by verifying a repair mechanism. According to the method, the expandability bottleneck in large-scale TSN network scheduling is solved, the computing efficiency is improved while the scheduling quality is ensured, and the method is suitable for scenes such as the industrial Internet of Things and the Internet of Vehicles which have strict requirements on deterministic communication.

The invention discloses a distributed wireless sensor network key node identification method and device and a medium. The method comprises the following steps: modeling a distributed wireless sensor network topology into an undirected graph G; a maximum independent set MIS is obtained on the basis of a Reduction-Peeling framework in combination with a constraint rule; obtaining a K-order adjacent matrix of the graph G according to the topological structure; for all nodes in the maximum independent set, if a common adjacent node c exists between every two nodes, c is a key node influencing the connectivity of the distributed wireless sensor network; if the common adjacent nodes do not exist among the nodes in the maximum independent set, expanding to a higher-order adjacent matrix for re-judgment until the adjacent nodes exist; and if the adjacent nodes are unique, taking the nodes as key nodes of the distributed wireless sensor network. The distributed wireless sensor network key node identification method solves the problems that an existing key node identification method is not suitable for a distributed wireless sensor network and the calculation complexity is too high, and accurate and efficient distributed wireless sensor network key node identification is achieved.

This invention discloses a method for mitigating social propagation risk and selecting robust groups based on extreme value dependency networks and maximally independent sets. The method includes: acquiring user interaction data from a social network and constructing a graph structure based on the user interaction data; obtaining target node pairs from the graph structure for a preset propagation activity period and calculating the extreme value dependency of the target node pairs; constructing propagation networks with target nodes as vertices and extreme value dependency as the edge construction criterion under different dependency thresholds, evaluating the propagation networks, and determining the extreme value dependency propagation network based on the evaluation results; dividing the extreme value dependency propagation network into communities and determining central nodes from the divided communities; constructing a minimum extreme value dependency group based on the extreme value dependency propagation network; and identifying high-risk node groups in the minimum extreme value dependency group using a propagation loss index to obtain the identification result. This invention can achieve the identification, isolation, and control of tail propagation linkage relationships.

The invention relates to the technical field of graph data processing, and provides a graph data processing method based on cache optimization, which comprises the following steps: constructing a cache optimization representation of graph data, and distributing a bit vector GT-vector with a fixed length of k for each vertex in a graph, each bit representing whether the vertex belongs to a pre-calculated maximum independent set; reserving adjacency list representation of the graph data, and storing the adjacency list representation as reference data in a memory; for an edge query request, reading GT-vectors of two vertexes from a CPU cache, and executing bit and operation; if the bit and the result are non-zero, judging that the edge is non-edge and immediately returning a first Boolean result indicating that the edge does not exist; and if the bit and result is zero, querying the adjacency list in the memory for verification, and returning a second Boolean result indicating that the edge exists or does not exist. According to the method and the device, the hybrid architecture combining the bit vector representation of cache optimization and the adjacency list is constructed, so that the magnitude order improvement of the graph data processing performance is realized on the premise of ensuring that the query result is completely accurate.

An embodiment of the present invention provides a communication network node optimization method, comprising: optimizing the communication network node utilization problem as a maximum independent set problem; converting the maximum independent set problem into a QUBO model; constructing a corresponding QUBO graph for the QUBO model; using a graph neural network to characterize the structure and characteristics of the QUBO graph to construct a deep learning model CONQUER; and training the deep learning model CONQUER to explore the optimal solution to the communication network node utilization problem, thereby obtaining a trained deep learning model CONQUER. This method can quickly and accurately optimize independent nodes or groups in the network, thereby improving the connectivity of the communication network and the efficiency of information transmission.

The application discloses an automatic routing method and system of a very large scale integrated circuit and a storage medium, and comprises the following steps: establishing a corresponding routing frame for each wire net; constructing a frame connection graph; splitting the frame connection graph into two or more subgraphs according to the edge weight and minimum of each subgraph; calculating the number of paths in conflict and the conflict coefficient between each wire net in the same subgraph, and constructing a track conflict graph of the same subgraph according to the number of paths and the conflict coefficient; and solving the maximum independent set of the track conflict graph to obtain the routing track of each wire net. The application can not only meet the DRC constraints such as routing line width and spacing when routing, but also can convert the routing layering problem into a multiple partitioning problem of subgraphs to process, thereby improving the rationality and efficiency of automatic routing.

The invention relates to an information propagation blocking method and system based on a MinMaxC model, and the method comprises the steps: obtaining an initial network diagram; a maximum independent set is searched through a fast heuristic algorithm, the maximum independent set is a secondary node set, nodes in the secondary node set are not adjacent to one another, and the maximum independent set is initialized; and selecting an important node from the cutting point set and inserting the important node into the cutting point set, executing node insertion through a greedy algorithm with a minimum increment, deleting the remaining nodes in the residual image after the minimum increment is completed, and outputting the cutting point set. The invention also provides two improved greedy algorithms, namely an IG + algorithm and an IG-PR algorithm, which improve the calculation efficiency of the node insertion step in the method. Network control personnel can correspondingly delete the communication nodes in the social network according to the cutting point set generated by the method disclosed by the invention, so that distortion information circulation is blocked.

According to a first aspect, the present disclosure relates to a method to find an approximate or exact solution to a maximum independent set problem of a graph, the method comprising: rearrange said input graph (12) onto a 3D orthogonal grid; determining, in the rearranged graph (13), for each pair of main nodes (202, 204) that are connected by a main edge (214), an ancillary path arranged along grid edges, using a pathfinding algorithm; generating an augmented 3D graph (14) by adding, in each ancillary path of the rearranged graph (13), an even number of ancillary nodes (221-224); providing a 3D array of neutral atoms comprising main atoms and ancillary atoms arranged to reflect the augmented 3D graph; applying a light shift pulse to the ancillary atoms in order to introduce at least one predetermined detuning of the resonance frequency of the ancillary atoms; applying a driving light pulse to all main atoms and all ancillary atoms to drive the 3D array of neutral atoms towards a predetermined final state; detecting the excited main atoms in the predetermined final state in order to obtain an independent set of the input graph.

The invention belongs to the technical field of biological computing, and discloses a general graph problem solving method and system based on DNA strand displacement, and the method comprises the steps: S1, carrying out graph structure modeling, and carrying out graph representation module based on DNA strand displacement; s2, constructing a detection module, and realizing parallel biochemical identification of constraint conditions by using a detection gate D (u) containing a fluorescence label; and S3, carrying out parallel detection on candidate solutions, supporting a unified solution framework of problems such as a minimum control set and a maximum independent set, and realizing rapid screening of the solutions through candidate solution enumeration and a fluorescence signal criterion. The method and the system provided by the invention adopt a modular cascade structure, realize direct solution of a complex problem on the premise of not depending on electronic calculation conversion, compress a solution space in combination with a graph feature value preprocessing technology, have the technical advantages of high neighborhood recognition accuracy, strong leakage reaction inhibition, strong experimental process universality and the like, and have a wide application prospect. And the application efficiency and stability of DNA calculation in the field of combinatorial optimization are remarkably improved.

The embodiment of the application provides a traffic scheduling method in a time sensitive network and related equipment, and belongs to the technical field of communication networks. The method models the TSN scheduling problem as a maximum independent set solving problem on a dynamic conflict hypergraph, and realizes decoupling of accurate constraints and efficient solving by maintaining a double-graph structure of a reference hypergraph and a sparse working hypergraph. A semi-static sparsification strategy combining global reconstruction based on semi-definite programming and heuristic local update is adopted to dynamically maintain the quality of the working hypergraph. The resource occupation index is used to realize near-linear incremental construction of the conflict hypergraph, and a flow-aware parallel greedy algorithm is used to quickly solve the approximate optimal scheduling on the working hypergraph. Finally, the verification repair mechanism ensures the feasibility of the scheduling scheme under accurate constraints. The application solves the scalability bottleneck in large-scale TSN network scheduling, improves the calculation efficiency while ensuring the scheduling quality, and is suitable for industrial Internet of Things, Internet of Vehicles and other scenes with strict deterministic communication requirements.