338results about How to "Even consumption" patented technology

The present invention relates to a wireless station, in a wireless LAN, comprising a network interface to network interface means comprising receiving/transmitting means, antenna means, at least first power supply means or energy holding means, said wireless station further supporting transmission of data in frames of variable length. Frame fragmentation is implemented by dividing a (long) frame into a number of frame fragments. Each fragment is sent as a non-fragmented frame and means are provided for controlling the length of the time periods before/between transmission of (consecutive) frame fragments in order to decrease energy consumption during a predetermined time interval.

The invention discloses an internet of things (IoT) error sensor node location method based on an improved Q learning algorithm. The method is characterized in that the traditional Q learning method is improved to make calculated Q values adaptively change according to characteristic information such as residual energy of a sensor node, routing and transmission hop count, a routing path is established by means of a maximal Q value, meanwhile, a background server works out a network topological structure, when the node is attached or produces error data, an error range is set by comparison with the Q value of the node of the next period, and when the range is exceeded, the node is judged to be the error node and is located. According to the invention, extra energy of the sensor node does not need to be consumed, and when a wireless sensor network topological structure changes, higher robustness is also achieved; and the method has the advantages of intelligent property, low energy consumption, high adaptive degree and the like, can be used to not only routing, location and energy consumption performance evaluation of the sensor node but also accurate location of unknown error nodes, and has wide application values.

The invention discloses a data transmission method of a multilayer distributed wireless sensor network, belonging to the technical field of telecommunication. The data transmission method is characterized by comprising the following steps of: selecting a route cluster head based on local information of a wireless sensor network, and clustering the wireless sensor network through comprehensively considering factors including residual energy of a sensor node, communication price and the like; building a cluster head single chain in a cluster head set by means of greedy algorithm, using the cluster head with the maximum energy weight value of a base station as a chain head node directly communicated with the base station in the cluster head single chain so as to enable each cluster head to transmit the data to the base station by means of multi-hop communication. In the invention, the data transmission method not only can effectively solve the technical problem of prolonging life cycle of the wireless sensor network, but also can improve the energy utilization ratio of the wireless sensor network, thereby the invention is suitable for a large-scale wireless sensor network and has wide application prospect.

The invention relates to a network load balancing method based on energy information of a wireless sensor, comprising the following steps: (1) Sink broadcasts an energy report message; (2) nodes receive an energy report of the Sink and then update and maintain local load forwarding tables; (3) the load allocation proportion born by various forwarding nodes and the load born by the various nodes are calculated; (4) the message is forwarded when local nodes are far away from convergent nodes compared with the forwarding nodes or are brother nodes of the same layer with the forwarding nodes; (5) various field values in the message are modified by self energy information and the message is forwarded to all the lower-level neighboring nodes or all the brother nodes of the same layer except the forwarding nodes; (6) when all the nodes receive the energy report message, the message forwarding is stopped; (7) after the energy report message is forwarded within a single period, propagation paths which reversely use the energy report message establish a load convergent route from sensing nodes to the convergent node Sink hop by hop; and (8) the convergent node Sink periodically sends out the energy report message and completes allocation and convergence of sensing data. The method solves the problems of network load balancing and network life cycle of a large-scale wireless sensor.

The invention discloses a clustering method for efficiently utilizing energy in the perception layer of an environment monitoring internet of things, and is applicable to a hierarchical heterogeneous network structure. The clustering method comprises four stages as follows: 1) in region division stage, according to the best number of cluster heads, region in which wireless sensor nodes are randomly distributed is divided; 2) in the stage of selecting candidate cluster heads, the average distribution coordinate of the node in each divided region is calculated, then the coordinate is taken as the center of a circle to define a circular region, and the nodes in the circular region are taken as candidate nodes; 3) in the stage of determining the node of the cluster head, cluster node in each region is determined according to the residual energy of the candidate node; 4) in the stable data transmission stage, each cluster node transmits the data of own cluster to a base station. The invention has the advantages that by adopting the method, the distribution of the clusters is more uniform, and the energy consumption of the nodes is more even, so that the survival time of the network is effectively prolonged.

The invention provides a sensor network for environmental monitoring. The sensor network comprises one or more sensing nodes, a plurality of routing nodes and a center node, wherein the sensing node is used for acquiring sensing data and transmitting a sensing data packet to the plurality of routing nodes; the routing node is used for receiving the sensing data packet, setting delayed forwarding time for the received sensing data packet, and forwarding the sensing data packet to a parent node of the routing node at the delayed forwarding time under the condition that the sensing data packet is not forwarded by another routing node at a current moment; the parent node is the center node or another routing node; the delayed forwarding time is randomly selected; and the center node is used for summarizing the sensing data packets. The invention also provides a corresponding data transmission method. By the sensor network and the method, the problem of over-high 'hotspot' energy consumption speed in the network is effectively solved, thereby prolonging the service life of the network. The outdegree of each sensing node is far more than 1, so data loss can be completely avoided.

The invention relates to a cooperative clustering routing communication method based on grade area division in WSN. The method includes that WSN is subjected to grade area division to realize the distributed non-uniform clustering, an improved LEACH algorithm is adopted in each area to perform self-adaptive clustering, and meanwhile, through the combination with the improved PEGASIS algorithm, the in-cluster nodes of a discrete cluster far away from the Sink node form a chain structure, and after the clustering is completed, the inter-cluster data transmission is carried out through multi-jump routing and cooperative transmission technology. In addition, the optimal cluster number is determined in each area of WSN and the clustering strategy is carried out, the clustering in the areas is uniform, the in-cluster nodes of the discrete clusters in the far areas form a chain to guarantee the node in each cluster in each area to consume energy equally, and the equal node energy consumption in the whole network is realized at the end, the life period of the whole network is prolonged, and the work performance of the whole network is improved.

The invention discloses a charging method for a mobile robot in a wireless charging sensor network system. The system comprises a base station, sensor nodes with wireless power receiving devices and the mobile robot with a wireless charging function, wherein the base station is provided with a plurality of charging points. A moving strategy of the mobile robot, a network energy balance method and a sensor node data processing method are provided on this basis. Data interaction is carried out among the base station, the sensor nodes and the mobile robot in a wireless communication manner. The charging period and each charging quantity are determined according to the energy consumption state of each sensor node. The overall energy utilization efficiency is finally improved by the system; and different energy supplements are carried out on the nodes with relatively fast energy consumption and the nodes with relatively slow energy consumption, so that the network energy consumption is balanced.

Disclosed in the invention is an ant colony algorithm-based high-energy efficiency wireless sensor network routing method. The method comprises three parts: cluster establishment, transmission in cluster, and transmission between clusters. When a multi-hop relay node is selected, a heuristic ant colony intelligent algorithm is employed to search a multi-hop transmission route; and during the searching process, an expectation importance influence is eliminated and a probability for node selection is completely decided by the link pheromone concentration. And when a local link pheromone is updated, a dump energy minimum value of a collaboration zone node is multiplied by link pheromone increasing degree Q and then the result is divided by transmission energy consumption, thereby completing updating. According to the new pheromone updating method, the dump energy and the transmission energy consumption of the node are scaled appropriately and then are introduced to the link pheromone updating; and when the dump energy of the collaboration zone node at the next hop is increased and the transmission energy consumption is reduced, the node can be selected. Therefore, when the routing method is used, total energy consumption of the network can be reduced; the dump energy of the network nodes can be balanced; and the working life of the network can be prolonged.

The invention provides an uneven clustering collaborative routing algorithm based on the cooperative game, and aims at the hotspot problem caused by uneven energy consumption in a wireless sensor network. According to the algorithm, factors of the positions, residual energy and communication cost of nodes are comprehensively considered in clustering, a campaign function is constructed according to the factors, the weight of each factor is weighed by utilizing the cooperative game to search the optimal node to act as a cluster head, and common nodes joins corresponding clusters according to the distance between the common nodes and the cluster head and the distance between the cluster head and aggregation nodes. Besides, a collaborative forwarding node is selected in each cluster according to information of the node residual energy and position in the routing phase further, and the collaborative forwarding node is utilized to forward data transmitted by the cluster head so as to avoid excessively fast energy consumption of the cluster head. The simulation result indicates that energy consumption of the network can be effectively equalized and the hotspot problem of the network can be alleviated by the algorithm so that the life cycle of the network can be prolonged.

The invention discloses high-viscosity continuous casting protective slag for solving slag inclusion on the surface of low-carbon steel. The protective slag comprises the following raw materials by weight percent: 0%-7% of glass powder, 50%-70% of premelting material, 5.5%-8.5% of fluorite, 4%-8% of dietary alkali, 3% of N330 carbon black, 3.5% of graphite, 0%-3% of R agent, 0.5-2% of lithium carbonate, 2%-5% of manganese carbonate, 2%-5% of magnesite, 3%-7% of bauxite, 1%-3% of cryolite, 1%-3% of adhesive, and 0.3%-1% of water-reducing agent. By utilizing the high-viscosity continuous casting protective slag, mainly on the basis of CaO and SiO2, a certain amount of fluxing agents such as the lithium carbonate, the fluorite, the dietary alkali and the like and a certain amount of carbon materials such as carbon black and graphite are externally added, thus the viscosity is improved and the surface tension is increased; and under the same technique condition, slag inclusion on the surface of a steel billet can be effectively prevented.

The invention discloses a reconfigurable assembly line sequencing method based on an improved genetic algorithm. The method comprises the following steps of: determining a population size according to a minimum production cycle of a reconfigurable assembly production line, and executing genetic encoding according to a standard of taking a chromosome as a full array of all tasks; calculating the idleness of the minimum reconfigurable assembly line, the quantity of unfinished work, the uniform parts use rate and the minimum production adjustment cost of the individual; executing a grading operation, executing a Pareto solution set optimization filtering operation, calculating the fitness of each grade, executing genetic operations according to the fitness, executing an elite reservation strategy, and obtaining a Pareto optimal solution set and a corresponding objective function value by judging whether convergence is realized or the pre-set maximum number of iteration is achieved. In the method, three major factors influencing the optimized sequencing of the reconfigurable assembly line are comprehensively considered, a plurality of technologies are used in the genetic operation, population diversity is ensured, algorithm prematurity is avoided, and global optimal search ability of the algorithm is enhanced.

First, the method establishes potential field model (PFM) and activation probability update model (APUM) at each node end. Then, each node end determines current self-state based on own current sleep/activation probability. All activated node ends detect target. Host node end with intelligent body (IB) processes own collected data based on info process algorithm carried by IB in order to form intermediate result, as well as sends out own info. Receiving info sent from host node end, each node end detected the target calculates own effect potential on decision for moving path of IB respectively based on PFM as well as sends out related info. Based on the said effect potential, host node end determines the node end to be moved for next hop of IB. based on APUM and received info, each activated node end updates own sleep/activation probability so as to realize distributed coprocessing data.

The invention provides a low power consumption parking management system based on a wireless sensor network, and wireless network nodes, wherein the parking management system includes a display control device, a guide device and wireless network nodes. The wireless network nodes work based on three modes, namely a high energy consumption detection mode, a low energy consumption sleep mode and a monitoring mode. Every wireless network node is responsible for the management of the corresponding stall, a plurality of wireless network nodes constitute an area, each area has one wireless network node serving as the monitoring node which work in the monitoring mode, other wireless network nodes serve as detection nodes which all work in a high energy consumption detection mode or all work in a low energy consumption sleep mode. Due to the adoption of the wireless network nodes with the three working modes, the detection and the monitoring of the stalls can be realized, data about left available stalls can be updated in a real-time manner in the display control device, and the guide device is controlled to guide vehicles into the left available stalls. Therefore, the stalls can be completely managed.

The invention provides a simulated annealing-based WSN hierarchical routing method. The method is based on a hierarchical network topology. The hierarchical structure is maintained by cluster nodes, cluster head nodes and sink nodes in a network. The method comprises the steps of firstly, dividing levels of the WSN, constructing the hierarchical structure of nodes, and then conducting data transmission. In the constructing phase of the hierarchical structure of nodes, cluster head nodes are elected and backed up according to energy. In the data transmission phase, a combination of a negotiation mechanism, a multi-hop energy multi-path routing mechanism and a simulated annealing algorithm is used, cluster nodes use the negotiation mechanism to transmit data to cluster head nodes, after data fusion is conducted by cluster head nodes, the data are transmitted to sink nodes, the multi-hop energy multi-path routing mechanism is used between cluster head nodes and sink nodes, the simulated annealing algorithm is used for seeking out an optimal path, and the data are transmitted from cluster head nodes to sink nodes along the optimal path.

The invention discloses an Internet of Things sensing layer topology control method. According to the method, an Internet of Things sensing layer wireless sensor network topology structure is established, data transmission is conducted based on the Internet of Things sensing layer wireless sensor network topology structure, and the Internet of Things sensing layer wireless sensor network topology structure is maintained. Due to the fact that cluster head nodes are selected layer by layer by means of positioning nodes during cluster head election, the selected cluster heads are distributed more evenly and reasonably. A aggregation node does not need to know the global information of a network, only small-range broadcast is needed, the increase of the number of nodes has few impacts on the method, data are forwarded through replay nodes and the cluster head nodes together during data transmission, the optimal path for forwarding is already determined during election of the cluster head nodes and the relay nodes, seeking of the optimal path is not needed, and energy consumption of the cluster head nodes is saved.

The invention discloses a heterogenous cluster routing method of a wireless sensor network based on energy collection. The method comprises the steps that a round concept is adopted; when each round begins, a sensor node in the network elects cluster head nodes in the optimal quantity according to types and thresholds T(s) of the nodes, and determines cluster interior nodes; after network clustering, the cluster head nodes collect and fuse data information acquired by a cluster interior member, and select an optimal routing path according to a routing selection criterion; the path sends fused data to a Sink node; the Sink node analyzes and processes the collected data, and broadcasts to inform all nodes in the network with operating parameters of a network in a next round; the current round is accomplished; and the next round begins. The method is fully matched with the characteristic of the wireless sensor network based on the energy collection, is suitable for the wireless sensor network based on the energy collection, can effectively increase data throughout of the network, and reduces energy consumption of the network.

The invention provides a wireless sensor network topology control method based on an artificial neural network (ANN). The method is characterized in that the aim of saving energy is achieved by simulating an information processing system of a biological neutral network; when the total vector of the signals input by senor nodes is more than the threshold of a neurone, the neurone is activated and gives out pulses, thus outputting the signals; the nodes are selected to become the cluster heads according to the output signals and the dump energy to primarily form a network topology map; other nodes select the nearest cluster heads and join in the clusters and transfer own information to the cluster heads; the network topology map is optimized in combination with power control; and the transmitting power of the cluster heads is controlled so as to balance the number of the sensor nodes covered by the network, thus reducing collision during communication and improving the communication efficiency. The method has the following beneficial effects: under the condition of ensuring the network connectivity and coverage, the network energy is reasonably and efficiently used as far as possible, the life time of the whole network is lengthened and the nodes in each cluster are balanced to reduce communication interference among the nodes and improve the network communication efficiency.

The invention discloses a routing method, a device and sensor nodes of a wireless sensor network, which are used for balancing the energy consumption of the wireless sensor network and prolonging the lifetime of the whole wireless sensor network. Wherein the routing method of the wireless sensor network comprises that a first distance between the sensor node and a sink node is confirmed by the sensor node which need to retransmit monitoring data; in allusion to each neighbour node of the sensor node, second distances between the neighbour nodes and the sink node are confirmed respectively; in each neighbour node of the sensor nodes, whether a neighbour node of which the confirmed second distance is smaller than the first distance exists is judged; if the neighbour node exists, a neighbour node is chosen from all the neighbour nodes of which the second distances are smaller than the first distances for retransmitting the monitoring data; and if not, a neighbour node is chosen from all the neighbour nodes of the sensor nodes for retransmitting the monitoring data.

The invention proposes a hierarchical routing method of a wireless sensor network based on a flora foraging optimization algorithm by combining a bacterial foraging optimization algorithm with a hierarchical routing algorithm. The method comprises the following steps: firstly, clustering nodes by an adaptive clustering method; then selecting a node as a source node and a sink node as a target node; carrying out path search by loop iteration of the bacterial foraging optimization algorithm, and fully considering the factors such as path transmission energy consumption and node residual energy in a search process; and finally selecting an optimal path to finish information transmission between the source node and the target node. According to the hierarchical routing method of the wireless sensor network based on the flora foraging optimization algorithm, the factors such as path transmission energy consumption and node residual energy are fully considered, and the life cycle of the wireless sensor network can be effectively prolonged.

The invention discloses a mobile Sink data collection method applied to a wireless sensor network and used for node internal-memory resource sharing. A mobile Sink moves along a preset track at a constant speed, stops RP points uniformly distributed in the network and collects node data in a K jump generation tree formed by taking the RP point as a root. Caching emergency and time emergency are defined, and internal-memory pressure can be relieved by sharing internal-memory resources with adjacent nodes in a same tree when nodes are in caching emergency, and internal-memory pressure can be received by sharing internal-memory resources of adjacent trees when the tree is in caching emergency. Packet loss caused by overflow of internal memory of the nodes is reduced through internal-memory resource sharing among the nodes. During time emergency, the nodes actively upload data packets of time emergency to the mobile Sink, so that the data packets are disabled to exceed a deadline due to transmission delay.

The invention discloses a wireless links management method, device and system. The method comprises a target shunt secondary base station is selected by a main control anchor point base station from ashunt auxiliary base station set, the target shunt secondary base station is configured, and the configured target shunt secondary base station is taken as a secondary control anchor point base station; first type control operation for the secondary control anchor point base station and general shunt secondary base stations is supported by the main control anchor point base station, second type control operation for the general shunt secondary base stations is supported by the secondary control anchor point base station, and the first type control operation comprises the second type control operation.

The invention relates to an inhomogeneous clustering method based on node energy balance for a wireless sensor network. The method mainly comprises the following steps: performing multi-layer area division on a circular area by taking sink as a circle center; calculating cluster radius relationship between adjacent layers under an energy balance condition, and quantitatively calculating the cluster radius relationship between adjacent layers under an equality holding condition according to the equality of dividing the total node energy consumption amount of the adjacent layers by node number of each layer during every-time operation of the network; after obtaining the cluster radius relationship between adjacent layers, calculating the specific value of the cluster radius of each layer according to the specific network parameters, finally obtaining the optimal cluster head number of each layer, and determining a probability formula of node election cluster heads in each layer according to the optical cluster head number; and respectively adding nodes in each layer into the cluster in each layer when the node cluster head election between adjacent layers and clustering do not affect each other.

The invention discloses a wireless sensor network routing method, for forming a network of the wireless sensor network and transmitting & receiving the signal, which includes the following steps: pre-allocating independent ID for each node, then creating wireless sensor network from clustering nodes to outside, increasing the gradient in turn, calculating along the nodes efficiency N on the way, and in their own routing table, recording the communicated front gradient node ID and the corresponding efficiency N. If it need to send data, the data is transmitted along the decreasing gradient direction, with the transmission path decided by the node, based on the probability P, the front gradient node in the routing table is selected as a communications target, so as to average the node working times, uniform the node energy consumption and stablish the network.