104 results about "Topology control" patented technology

A wireless communication method and system enabling dynamic multi-path data transmission and reception across heterogeneous radio access networks. The method includes selecting between sequential, concurrent, or redundant multipath transmission strategies based on real-time measurements of link quality parameters, including signal-to-interference-plus-noise ratio (SINR), reference signal received power (RSRP), delay, and spectrum availability. The system further enables adaptive transmission power control, modulation scheme selection, and carrier configuration based on physical layer feedback, minimizing interference and optimizing spectral efficiency. Peer-to-peer communication between terminals is supported without base station mediation, reducing RAN load. Multi-base station connectivity is enabled, allowing terminals to simultaneously transmit through multiple nodes and aggregate at the core network. The architecture supports real-time topology control, dynamic link adaptation, and transmission parameter adjustment based on physical-layer constraints.

The invention is suitable for the technical field of unmanned aerial vehicle information transmission, and provides a self-adaptive multi-unmanned aerial vehicle information transmission system and method based on channel estimation, and the system comprises a channel modeling module, a communication scheduling module, a topology control module and a terminal sensing layer. The channel modeling module is used for estimating and predicting a wireless link state in a complex environment in real time through an improved Kalman filtering method; the communication scheduling module constructs a transmission decision module based on a reinforcement learning strategy, and realizes joint dynamic optimization of a communication link and a task execution path by introducing a Q-learning algorithm; the topology control module introduces a multi-objective optimization strategy based on a utility function to realize dynamic reconstruction of the network topology; the terminal sensing layer is used for multi-unmanned aerial vehicle distributed cooperative detection and multi-modal sensing data fusion; according to the invention, the edge collaborative fusion perception of multiple unmanned aerial vehicles replaces the traditional single-point detection, and the target recognition precision and the shielding robustness are significantly improved.

The invention relates to the field of underwater target positioning, and discloses an underwater target cooperative positioning method and system based on unmanned aerial vehicle topology control, and the method comprises the steps: constructing an unmanned aerial vehicle cluster, and achieving the topological reconstruction of an unmanned aerial vehicle cluster structure through a virtual force topology control algorithm; performing preprocessing and time synchronization on the signals received by each unmanned aerial vehicle of the unmanned aerial vehicle cluster so as to calculate an accurate time delay inequality; calculating the specific position coordinates of the underwater target according to the underwater target signals received by the unmanned aerial vehicles and the calculated time delay inequality; compared with a traditional scheme, the unmanned aerial vehicle cluster is dynamically deployed in a self-organized and self-adaptive mode through the virtual force topology so as to ensure stable communication of the cluster structure and expand the sensing coverage range, and the method has the advantages of self-adaptive adjustment and control, good communication robustness and high positioning precision; and underwater collaborative search and accurate positioning of the unmanned system can be realized.

A dynamic grid allocation system for power distribution in the development of integrated circuits in the sub-five-nanometer range, wherein the system comprises the following: a placement processor unit configured to receive a synthesized netlist comprising a variety of standard cells and macros, each associated with switching activity data derived from simulation or synthesis activity profiles, and to generate a spatial cell placement arrangement by grouping cells into microzones based on activity correlation, time sensitivity, and connection proximity; a power density calculation unit coupled to the placement processor unit and configured to calculate the local power density and instantaneous current demand for each microzone based on the spatial distribution of switching operations, capacity load, and effective switching frequencies; a dynamic network generation unit coupled to the power density calculation unit and configured to generate a multilayer power distribution network with variable network topology, where the width, spacing, via density and metal layer assignment of the power network are adaptively determined as continuous functions of the localized power density and power demand calculated for each microzone; a topology control processor configured to monitor voltage drop and electromigration data obtained from signoff analyses or predictive models in real time and dynamically adjust the power grid topology parameters to ensure compliance with predefined reliability thresholds for voltage drop and electromigration; a predictive current modeling unit configured to receive historical switching and voltage data, train a predictive model for transient current peaks, and provide predictive power boost instructions to the dynamic grid generation unit before power integrity violations occur; and A feedback synchronization controller is communicatively connected to the placement processor unit and the topology control processor, whereby the feedback synchronization controller continuously exchanges updated power density information and placement constraints, so that cell placement and network topology adapt together in real time, thereby minimizing routing congestion, ensuring a uniform voltage distribution, and guaranteeing compliance with electromigration and IR drop regulations under various activity conditions.

The invention provides a self-adjusting dialogue type multi-agent system and interaction method based on dynamic topology, and the system comprises a scheduling module which is used for receiving user input and routing a task to a corresponding field task agent in a conventional state; the domain task intelligent agents are used for processing the received tasks, evaluating the cognitive states in real time and sending out assistance signals when the cognitive states meet preset conditions; the shared knowledge management module is used for maintaining a dynamically updated distributed semantic knowledge graph; wherein the distributed semantic knowledge graph is used for sharing, associating and persisting structured knowledge entities and context information generated in the session process among all modules in real time; the topology control module is used for dynamically switching the communication control topology of the system from a first topology structure to a second topology structure in response to the received assistance signal; and when the assistance signal is eliminated, the communication control topology is recovered from the second topology structure to the first topology structure.

The invention provides a high-voltage frequency converter control system, and relates to the technical field of power electronic control, the high-voltage frequency converter control system comprises a phase-shifting transformer, a multi-level inverter, an SPWM modulation module, a fuzzy PI current limiting controller and a virtual master-slave topology controller, the phase-shifting transformer is used for performing phase-shifting isolation on power grid input voltage and inhibiting input current harmonics; the multi-level inverter is in cascade connection with the output end of the phase-shifting transformer and used for inverting the direct-current voltage into multi-level alternating-current high voltage to be output. The SPWM modulation module is electrically connected with the multi-level inverter; the phase-shifting transformer is combined with the multi-level topology, so that the harmonic content of the input current is reduced to 1.5% or below, the standard can be met without an additional filter, the output voltage THD is controlled within 2% through the asymmetric rule sampling and tangent approximation method by the SPWM modulation technology, and motor heating and electromagnetic interference are remarkably reduced.

The invention provides a distributed robust topology control method and system for cluster unmanned aerial vehicles, and the method comprises the steps: carrying out the construction of a midpoint coverage circle with a node as a center for each node of a cluster unmanned aerial vehicle network, and judging potential key nodes; acquiring local topology through k times of neighbor information exchange for potential key nodes, generating a simplified block tree model based on depth-first search, traversing connected components by taking the simplified block tree model as a root node to form block point sets, and judging that the root node is a key node when the number of the block point sets to which the root node belongs is greater than 1; and constructing an enhanced edge candidate set which is arranged according to a cost ascending order by the determined key nodes, selecting the edge with the minimum cost to communicate different blocks, sending a moving instruction to controlled nodes in k hops to establish a communication link, and finally enabling the network topology to meet vertex 2-communication. According to the method, the key nodes in the network are detected, and the key nodes are eliminated in a node moving mode, so that the stable and reliable unmanned aerial vehicle cluster network topology is constructed at low cost.

The invention relates to the technical field of wireless communication testing, and discloses an automatic detection and evaluation method and system for the radio frequency performance limit of multi-antenna wireless equipment, and the method comprises the steps: defining a target port and an interference port for multi-port equipment, constructing an automatic detection topology through a program-controlled radio frequency switch matrix, and carrying out the automatic detection of the radio frequency performance limit of the multi-antenna wireless equipment; and controlling the equipment to enter a full-port synchronous concurrent transmission state with a high duty ratio. In this state, power search is performed on the target port to lock the initial limit power point, and further multi-dimensional evaluation including thermal steady state drift analysis and environmental isolation verification based on a silent window is performed to confirm an effective limit power value. And traversing all ports by the system, repeating the steps, summarizing data, and calculating the consistency range and the rated power of the whole machine. According to the invention, through physical reproduction, heating accumulation and electromagnetic crosstalk environment, accurate evaluation of radio frequency performance of equipment under extreme working conditions and automatic attribution of a thermal failure mechanism are realized.

The invention provides a polarization agility and topology control combined optimization anti-interference system in a low-altitude self-organizing network, which is constructed on a multi-layer collaborative architecture and comprises (1) a multi-dimensional environment sensing layer used for collecting and processing multi-source information such as interference polarization, signal quality, network topology and node dynamics in real time; (2) a joint optimization decision-making layer which intelligently determines an optimal node polarization configuration and network topology strategy according to perception information by adopting an innovative model and an algorithm; and (3) the coordination action execution layer is used for accurately and quickly executing a decision instruction and adjusting antenna polarization and network topology parameters. According to the system, a quantitative polarization-topology coupling interference model is introduced, and a joint optimization controller based on deep reinforcement learning is designed, so that the anti-interference performance, the network effective throughput, the energy efficiency and the response speed to dynamic interference are remarkably improved.

The invention discloses a power distribution network-micro-grid collaborative dual-time scale scheduling method in combination with topological optimization. According to the method, a long-time-scale scheduling period is set at the hierarchy of the power distribution network, a scheduling model combining topology reconstruction and active optimization is adopted, and unified regulation and control of global operation characteristics such as grid power flow, line heavy load and node voltage are achieved; an ultra-short time scale real-time scheduling period is set in a micro-grid level, and new energy fluctuation is rapidly tracked and compensated based on rapid adjustable resources; and through a multi-level information interaction mechanism, power distribution network scheduling constraint downloading and micro-grid feedback uploading are realized, and friendly interaction and cooperative operation between the power distribution network and the micro-grid are realized. According to the method, the flexibility and the new energy consumption capability of the power distribution system are remarkably improved through a topology flexible regulation and control means, meanwhile, the rapid response capability of the system to the time-varying uncertainty is enhanced through a double-level scheduling mode, the operation loss and the safety risk of the power distribution network are reduced, and the method has good engineering application value.

This invention relates to the field of industrial automation control technology, specifically to an automatic control system for a multi-station collaborative surface treatment equipment, comprising a process gene mapping module, a predictive trajectory interlock module, and a bus closed-loop feedback module. This invention constructs a process topology control chain, utilizes a virtual control entity and a global resource occupancy table for advance simulation on the control system clock axis, triggers a hardware / software interlock mechanism and generates a spatiotemporal decoupling control signal when occupancy conflicts are identified; and uses the bus closed-loop feedback module to verify the spatial consistency between the measured feedback vector and the virtual control entity, triggering emergency stop protection and forcibly reconstructing the control signal when the deviation exceeds the virtual-real mapping residual limit. This invention achieves global asynchronous parallel scheduling and closed-loop safety control of multiple tasks on the production line, effectively solving the problems of low collaborative efficiency and equipment resource deadlock.

The invention discloses a low-delay and high-efficiency WSN (Wireless Sensor Network) topology control method based on fusion clustering, which is a fusion clustering algorithm and fuses an improved density peak algorithm and a butterfly optimization algorithm for clustering. The method comprises the following steps: firstly, obtaining two optimal solution sets through the two algorithms, then solving an intersection of the two solution sets, then carrying out descending sort on the solutions except the intersection through a decision function, and finally adding the solutions into a final cluster head set from high to low. The method combines the advantages of excellent performance of a density peak value algorithm in a large-scale network and rapid iteration of a meta-heuristic algorithm from a global perspective, improves a routing cost function in the aspect of routing construction, carries out delay constraint on a routing path, directly transmits a path which does not meet the delay constraint in a single-hop mode, and improves the routing efficiency. And the network time delay is reduced as much as possible.

The application discloses a chip bottom layer topology control method and system based on discrete space-time dual mapping, and belongs to the technical field of integrated circuit bottom layer intelligent control. In view of the bottom layer defects of traditional chip hardware and information being split, relying on external driving, architecture being solidified, scheduling being redundant, and lacking self-adaptive evolution capability, the application is based on the original TPS-CCC discrete space-time information-physical dual theory, constructs a three-dimensional topological dual mapping system, establishes hardware native topological evolution driving logic, and realizes chip computing power autonomous scheduling, hardware self-adaptive reconstruction, error self-healing correction and dynamic power consumption optimization. The application overturns the software passive control paradigm of the traditional chip, creates the next-generation chip bottom layer general paradigm of hardware-level autonomous intelligent control, has extremely high bottom layer theoretical barriers and full-coverage protection range, can be adapted to all types of high-end semiconductor chips, and has extremely strong industry monopoly and industrialization value.

The invention relates to the technical field of heat pump systems, and discloses a transcritical cycle-based heat pump waste heat recovery system, which comprises a compression module, a heat exchange scheduling module, a phase state separation module, a flow control module, a heat absorption module and a flow path topology control module, according to exhaust pressure and exhaust temperature parameters of a compression module, rehearsing a candidate communication state to generate a target communication feature set, calculating a configuration transition deviation value of the target communication feature set relative to a current communication feature set, determining a physical switching constraint weight and introducing thermodynamic efficiency evaluation logic, and when an evaluation result meets a migration criterion, determining a physical switching constraint weight; according to the method, the physical deviation cost of flow path configuration transition is quantified, dynamic matching of a refrigerant heat release track and a heat source side temperature gradient field is achieved, the problem of heat transfer temperature difference distortion is solved, and disordered oscillation of a physical flow path is restrained.

The invention discloses a multi-shell inclined orbit-oriented satellite-ground integrated topology control method and system, and the method comprises the steps: carrying out the ground service domain division of each shell satellite of an inclined orbit giant constellation, and obtaining a ground service domain set; solving the same-rail switching time, different-rail switching time and phase compensation time; therefore, the mapping relation between each shell satellite and the corresponding ground service domain at a certain moment is obtained; calculating satellites between adjacent shell layers and a cross-layer candidate link set of the satellites to obtain a total candidate communication relation of the satellites between the shell layers at the moment # imgabs0 #; calculating a one-to-one communication relationship of the corrected satellites of the adjacent shell layers at a certain moment; obtaining a total actual topological relation between the inclined orbit giant constellation and the ground service domains at a certain moment by combining a mapping relation between each shell satellite and the corresponding ground service domain at the certain moment; and the user judges the ground service domain where the user is located according to the latitude and longitude information, and generates a route according to the target service domain, the total actual topological relation and the load state of the satellite.

This invention discloses a heterogeneous wireless converged network topology control method and its application for unmanned swarms, belonging to the field of wireless network communication technology. Addressing the problems of selfish behavior of network nodes and poor robustness of network topology in existing network topology control methods, this invention utilizes a network model, a wireless communication energy consumption model, and a node reliability model of the heterogeneous wireless converged network to construct a heterogeneous wireless converged network topology quality assessment model with node reliability, network connectivity, and lifespan as indicators. This model is used to evaluate node power control schemes and incorporates blockchain technology to achieve control over the network topology. The heterogeneous wireless converged network topology control method of this invention can effectively limit the potential selfish behavior of network nodes while ensuring the coverage and connectivity of the heterogeneous wireless converged network.

An embodiment causes inserting, into kernel code of an operating system, during execution of the operating system, a traffic monitoring code module. An embodiment extracts, using the traffic monitoring code module, from a plurality of messages between components of a cluster management system managing a first cluster of systems, a first message relating to a resource object, the resource object representing a resource within the first cluster of systems, the traffic monitoring code module triggered by receipt of each of the plurality of messages at a socket of the kernel code. An embodiment constructs, using the first message, a controller-resource object topology, the controller-resource object topology identifying a relationship between the resource object and a controller associated with the resource object.

The invention discloses a WSN (Wireless Sensor Network) topology control method based on dynamic fuzzy trust and an artificial bee colony algorithm, which only performs security detection when malicious activities exist in a network. Firstly, a sliding time window mechanism is introduced into trust value calculation to ensure the dynamism and timeliness of trust values. And then, by introducing a forwarding delay judgment mechanism, a serious security problem in the network can be quickly identified. And meanwhile, the indirect trust value is calculated by utilizing a fuzzy comprehensive evaluation method, so that the comprehensiveness and the accuracy of trust evaluation are enhanced. And finally, detecting and isolating dishonest recommended nodes by adopting an artificial bee colony algorithm, thereby further improving the accuracy of trust evaluation and the overall security of the network. According to the method, for the large-scale wireless sensor network, unnecessary energy consumption is effectively reduced, the credibility of the malicious node recognition rate is improved, and the misjudgment rate is low. And the comprehensive capability in energy consumption, safety and other performances is better.

The present application relates to the technical field of distributed resource operation regulation, in particular to a distributed resource operation regulation simulation integrated system for a new power distribution system, which comprises a regulation service control, a simulation service control, a topology service device, a topology control service device and a topology adjustment service device. The system receives real-time monitoring equipment operation data, performs power distribution network simulation analysis, and draws a dynamically adjusted simulation topology structure diagram. By integrating various simulation scene algorithms, the system can flexibly adjust the monitoring equipment configuration, perform load prediction and voltage analysis based on the current operation state, automatically generate a topology adjustment strategy, and realize efficient operation regulation of the power distribution network. The present application realizes efficient and intelligent operation regulation and simulation analysis of the power distribution system, and improves the management level and operation efficiency of the power distribution network.

The invention discloses a charging pile system and a power distribution method and system. The system comprises a charging module array, a power distribution network, a switch matrix and a charging gun. The method comprises the steps of collecting module power, charging gun requirements, switch states and bus loads in real time; constructing a topology model reflecting physical connection, and solving connection topology covering requirements by taking minimization of the use cost of a switching device as a target; an optimization model is constructed based on the topology, and a power distribution scheme is solved with the purposes of meeting the charging requirement and reducing the system loss; and finally, controlling on-off of a switch according to the connection topology, and setting module output according to a power distribution scheme. Through a step-by-step optimization strategy, the problems of physical connection and energy flow are solved successively, dynamic response to variable charging requirements is realized, and resource waste caused by a fixed connection mode is avoided.

The application discloses a kind of high reliability and flexibility routing methods for strong confrontation self-organizing network, mainly solve the problem of low business delivery rate and slow routing convergence speed in strong confrontation scene using traditional routing algorithm.The implementation scheme is divided into topology control and routing two parts:Among them, routing includes: using the node information obtained by topology control to complete the routing discovery process, and constructing the whole network routing table;Through routing-topology joint, periodic and active two ways are used to jointly maintain the whole network routing table.Topology control includes:1) constructing the network topology structure of bidirectional link;2) maintaining one-hop routing table according to logical neighbor list;3) repeating 1)-2) until the network stops running.The application can maintain high end-to-end business delivery rate in strong confrontation scene, quickly complete the routing discovery process, improve the routing convergence speed, improve the stability and reliability of path, and can be used for mobile self-organizing network business data transmission.

The invention discloses an electric energy quality control method and system based on a distributed electric power system, and relates to the technical field of electric energy quality control, and the method comprises the following steps: obtaining an initial micro-grid topological structure and key features of each node, constructing an electric energy quality index model, and judging whether to carry out topological control or not; solving and converting the initial microgrid topological structure into a simplest topological structure based on a Prim algorithm, and recording a residual edge set; sorting the residual edge sets based on a neural network scoring model, and screening the residual edge sets according to system computing power; reconstructing the simplest topological structure based on the screened residual edge set to obtain a to-be-controlled topological structure set; and obtaining an optimal micro-grid topological structure in the topological structure set based on the electric energy quality index model, comparing the optimal micro-grid topological structure with the initial micro-grid topological structure to obtain a control instruction, and realizing efficient topological reconstruction control of the distributed power system micro-grid so as to regulate and control the electric energy quality.

The application discloses a kind of based on topological control and MPR selection optimization's heterogeneous self-organizing network OLSR protocol implementation method, this method is first by calculating link quality factor LF and is clustered, to form stable cluster structure.Subsequently, using AOW clustering algorithm, according to the node's various factors Selection suitable node assumes cluster head, reduces the frequency and related overhead of cluster head replacement.In addition, to ensure the connectivity between each cluster and form a complete network topology, based on the design concept of cross-layer routing, introduce the multi-frequency clustering inter-cluster connection algorithm based on TDMA protocol.Through continuous maintenance topological routing.Introduce a link stability factor based on laser transceiver device scanning angle, to optimize MPR selection mechanism.Has been realized in EXata network simulation environment, and is verified by experiment.The optimized protocol of the application is more excellent in the environment of high transmission rate requirement, high mobility and atmospheric attenuation, effectively improves the performance and reliability of network.

This application provides a self-regulating dialogic multi-agent system and interaction method based on dynamic topology. The system includes: a scheduling module, used to receive user input and route tasks to corresponding domain task agents under normal conditions; several domain task agents, used to process the received tasks and evaluate the cognitive state in real time, and issue assistance signals when the cognitive state meets preset conditions; a shared knowledge management module, used to maintain a dynamically updated distributed semantic knowledge graph; wherein, the distributed semantic knowledge graph is used to share, associate and persist the structured knowledge entities and context information generated during the conversation in real time among all modules; and a topology control module, used to dynamically switch the communication control topology of the system from a first topology to a second topology in response to the received assistance signal; and to restore the communication control topology from the second topology to the first topology when the assistance signal is eliminated.

The application provides a new energy grid-connected topology based on a resolver, a control system and a method, which comprise an inverter (1), a resolver (2) and a grid-connected switch (3), wherein the AC side wiring terminal of the inverter (1) is led out from the three-phase bridge arm midpoint to be connected to the primary side three-phase wiring terminal of the resolver (2); the primary side wiring terminal of the resolver (2) is connected to the inverter (1), and the secondary side wiring terminal is connected to the grid-connected switch (3); and the grid-connected switch (2) is connected in series between the resolver (2) and the power grid. The technical problems of poor electromagnetic oscillation suppression effect, lack of inertia support, difficult grid-connected system design, low power system operation safety, high technology use cost and small short-circuit current during short-circuit fault of the existing new energy grid-connected technology are solved.

This invention discloses an adaptive optimization method for edge optical links in a data center based on deep reinforcement learning. Using a fixed fat-tree electrical switching plane as the underlying architecture, it achieves adaptive addition and deletion of direct optical links between edge switches through topology control (DQN) and optical path switching. The DQN and packet-by-packet routing (DQN) form a two-layer collaborative decision-making structure. This invention models the optical link addition / deletion decision as a constrained Markov decision process, employing a dynamic candidate set mechanism to construct a low-dimensional state and action space, significantly reducing model computational complexity and training overhead. Compared to a pure electrical fat-tree architecture, the provided dynamic candidate set DQN scheme effectively reduces average on-network latency, packet rejection rate, and maximum queue length under high-load scenarios. Under the same link resource constraints, the dynamic candidate set scheme outperforms the all-optical link pair scheme, exhibiting higher training efficiency, decision stability, and network scalability. This invention can adaptively sense traffic distribution and schedule optical link resources on demand, making it suitable for real-time control and performance optimization scenarios in high-dynamic and high-throughput hybrid optoelectronic data center network topologies.

The invention discloses a distributed intelligent power distribution network reliability influence factor analysis method and system, and relates to the technical field of influence factor analysis, and the method comprises the following steps: obtaining the operation state of a power distribution network in a target region, and constructing a topology-control mode table; performing uncertainty labeling on the key equipment to form a structural uncertainty matrix; coupling the structural uncertainty matrix with node operation data, establishing a reliability model, calculating the sensitivity of each uncertain structural unit to the reliability index of the whole system, and generating a structural sensitivity vector; and combining the structural sensitivity vector with real-time operation data to form a dynamic reliability influence factor table, and constructing a topology-control mode table. According to the method, the dynamic reliability influence factor table is generated by establishing the structure-state coupling reliability model, so that the problem that key influence factors are inaccurately identified due to the fact that the influence of topological change and control mode switching on the system reliability is not comprehensively considered in the prior art is solved.

The present invention relates to the field of topology control for unmanned aerial vehicle (UAV) swarms. It mainly studies a task-oriented topology control method for unmanned swarms. The main process is that after a node receives a task, it determines the task level and decides at which level the task will be executed. Intra-cluster control mainly includes cluster center selection and execution of low-level tasks. Inter-cluster cooperative control mainly includes selection of the inter-cluster cooperative control center and execution of medium-level tasks. Overall network control mainly includes selection of the network center and execution of high-level tasks. Finally, a task-oriented topology control method for unmanned swarms with intra-cluster determination, inter-cluster cooperation, and overall network control is formed. In the present invention, the node selection adopts a dual-criterion selection method of geographical center + location center, which can ensure the efficiency and quality of executing communication tasks, and the network can adapt to various communication guarantee tasks.

The application discloses a distributed intelligent power distribution network reliability influence factor analysis method and system, relates to the technical field of influence factor analysis, and comprises the following steps: obtaining the operation state of a target area power distribution network, and constructing a topology-control mode table; marking uncertainty of key equipment to form a structure uncertainty matrix; coupling the structure uncertainty matrix with node operation data, establishing a reliability model, calculating the sensitivity of each uncertain structure unit to the overall system reliability index, and generating a structure sensitivity vector; and combining the structure sensitivity vector with real-time operation data to form a dynamic reliability influence factor table. The topology-control mode table is constructed. By establishing a structure-state coupled reliability model and generating a dynamic reliability influence factor table, the application solves the problem that the influence of topology changes and control mode switching on system reliability is not comprehensively considered in the prior art, and the problem of inaccurate identification of key influence factors is solved.

The invention discloses an OLSR routing method for optimizing time slot resources. The method comprises the following steps of: interactively maintaining neighbor and topological information through a HELLO message, and calculating and announcing an MPR set according to the neighbor and topological information; the core lies in that the sending interval of topology control messages is dynamically triggered and calculated based on an exponential formula by monitoring the change of an MPR selector list, and intelligent adjustment of control overhead is achieved; at a receiving end, performing message forwarding judgment based on an MPR selector list, and calculating retention time for a learned topology entry by adopting an adaptive formula to enhance robustness; and finally, iteratively generating a routing table based on the updated topology table. According to the invention, the occupation of the routing protocol control message on the constant air interface time slot resource is reduced, and the transmission capability of the service data is improved on the premise of ensuring the network stability.