6 results about "Node deletion" patented technology

The invention provides a distributed workflow task scheduling method and system, and relates to the technical field of computers, and the method comprises the steps: defining a scheduling task node and a dependency relationship in a dragging manner through a visual canvas, and storing the scheduling task node and the dependency relationship; the Worker nodes with the ZooKeeper center hop state being normal are screened, node weights are calculated based on dynamic load balancing, and tasks are distributed to the Worker node with the highest weight to be executed; when the Worker node has a fault, monitoring a ZooKeeper node deletion event, and identifying an IP (Internet Protocol) and a port of the fault Worker; marking an unterminated task state on the fault node as a state needing fault tolerance and redistributing; when the Master node fails, the surviving Master takes over the workflow instance of the failed Master based on a slot allocation mechanism; and updating the task reporting address in the Worker to the current Master, and re-distributing the uncompleted tasks. The usability, efficiency and stability of workflow scheduling are integrally improved, and diversified business requirements are met.

The invention discloses an unstructured data multi-way tree chain table storage method, which comprises the following steps of: 1, defining a data structure, and establishing a dynamic multi-way tree node structure; step 2, maintaining a target chain node, and maintaining an index relationship of the node through a directory chain table; step 3, node insertion adjustment: dynamically adjusting a pointing relation of a linked list pointer array during node insertion to form a multi-way tree topological structure; step 4, recombining pointers, and updating child node pointers of the target nodes to reconstruct a local hash table; 5, deleting and recovering the nodes, marking the nodes to be deleted as invalid nodes and recovering the storage space of the invalid nodes; step 6, carrying out data fault tolerance and recovery, and storing data by multiple copies to ensure data integrity; through the innovative unstructured data multi-way tree chain table storage method, efficient, flexible and reliable data management is achieved, a layered compression structure is adopted, memory mapping, pre-read caching and asynchronous persistence technologies are combined, and storage occupation is remarkably reduced.

The application discloses a distributed industrial wireless network deterministic transmission scheduling system, which comprises the following modules: a synchronization module for time slot synchronization between nodes; a data transmission module for data transmission between nodes; and a node management module for node deletion and addition management. The application uses distributed negotiation scheduling design, reduces overall energy consumption and delay of the network, and avoids network paralysis caused by failure of a central control node.

The invention discloses an incremental updating method for a Graphrag community, which belongs to the technical field of information technology specially suitable for supervision purpose, and comprises the following steps: monitoring a change event of a knowledge graph, and defining an affected local sub-graph based on an N-order neighborhood expansion algorithm; for node deletion, key context information of deleted nodes is converted into semantic heritage vectors through a semantic heritage vectorization method, and the semantic heritage vectors are associated to an original community; local subgraphs and semantic heritage vectors are loaded into an iterative collaborative optimization engine to be initialized, a candidate community division scheme is proposed based on current topology and historical semantic feedback in an optimization loop, a draft digest is generated, and the community structure is adjusted by quantitatively evaluating the consistency score of community cohesion and semantic tension between communities, so that the candidate community division scheme is obtained. Iteration is carried out until convergence; finally, an optimization result is atomically solidified to a graph database and an abstract index. According to the method, high overhead of total reconstruction and semantic drift of local updating are avoided.

The application discloses a method for identifying key nodes of a heterogeneous Internet of Things (IoT) topology based on mutation theory, and belongs to the field of computers and information. First, an initial topology of the heterogeneous IoT is constructed, a topology set is generated by random disturbance, and performance indexes such as robustness, redundancy, communication efficiency and global clustering coefficient are calculated. Then, the indexes are normalized by using a mutation series method, the correlation between the indexes is evaluated based on a Pearson correlation coefficient, and a network performance mutation value is obtained by layer-by-layer fusion. Next, a deliberate attack process is simulated, a corresponding relationship between a node deletion sequence and performance evolution is established, and a performance evolution function is fitted. Finally, a cusp mutation model is established, critical nodes causing network performance mutation are identified by analyzing the equilibrium state, singular set and bifurcation set of the model, and the application breaks through the limitations of traditional static network indexes, can accurately capture the mutation behavior of network performance, is objective, and provides a theoretical basis for topology optimization and fault-tolerant design of the IoT.

The application provides a distributed workflow task scheduling method and system, and relates to the technical field of computers. The scheduling task nodes and dependency relationships are defined and stored in a drag-and-drop manner through a visual canvas. The Worker nodes with a normal ZooKeeper center hop state are screened, the node weights are calculated based on dynamic load balancing, and the tasks are distributed to the Worker nodes with the highest weights for execution. When a Worker node fails, the ZooKeeper node deletion event is listened to, the IP and port of the faulty Worker are identified, the task states of the un-terminated nodes of the faulty node are marked as needing fault tolerance and are re-allocated. When a Master node fails, the surviving Master takes over the workflow instance of the faulty Master based on a slot allocation mechanism. The task reporting address in the Worker is updated to the current Master, and the uncompleted tasks are re-dispatched. The overall usability, efficiency and stability of the workflow scheduling are improved, and the method is suitable for diversified business requirements.