5 results about "Maximal independent set" patented technology

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.

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.

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.

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.