579 results about "Node deployment" patented technology

The invention relates to a self-adapting positioning method for mobile nodes of a hybrid sensor network. The system mainly comprises a plurality of common static nodes, mobile nodes, convergent nodes and a background monitoring center, wherein the common static nodes and the mobile nodes are communicated by the ZigBee mesh network protocol. The positioning process for the mobile nodes are mainly divided into the following three stages including node deployment, calibration and real-time positioning; and the method is characterized by making on-line correction of the attenuation model of wireless signal prorogation in a spot monitoring environment by utilizing a method that the mobile nodes self deploy or artificially deploy new nodes, eliminating the positioning error caused by the conditions of node self energy, data loss, small measured RSSI (Received Signal Strength Indication) value and the like, and simultaneously eliminating the participation of lineal children nodes into the positioning calculation of the mobile nodes on a great attenuation communication link caused by barriers and the like, thereby improving the self adapting positioning ability and the positioning accuracy of the mobile nodes of the hybrid sensor network, and the new nodes deployed can improve the robustness and the reliability of the entire network.

The invention relates to a method for positioning a mobile node of a wireless sensor network based on a crossed particle swarm. After the deployment of anchor nodes is finished, the mobile node enters a greenhouse area, and broadcasts and sends a positioning request to all anchor nodes in a network; the mobile node receives the broadcast information of normal anchor nodes, measurement distance between the mobile node and the corresponding anchor node is obtained by calculation, and the measurement distance is corrected by using error coefficients of each anchor node; the mobile node substitutes the information of the normal anchor nodes and the corrected distance into a crossed particle swarm positioning algorithm for optimal calculation; and the algorithm outputs a cluster optimal position as an estimated coordinate of the mobile node. The coordinate of the mobile node is accurately estimated. The method is high in convergence speed, low in calculation complexity, perfect, and high in positioning performance.

A methods and apparatus for remote management of switching network nodes in a stack via in-band messaging are presented. Switching nodes in the stack default to reserved switching node identifiers and stacking ports default to a blocking state upon startup, restart, and reset. Each command frame received via a blocking state is forwarded to a command engine at each switching node and is acknowledged with the current switching node identifier. Each acknowledgement frame bearing the reserved network node identifier triggers configuration of the acknowledging switching node. Switching nodes and the management processor track interrupt state vectors regarding events. An interrupt acknowledgement process is employed to track raised interrupts. Configuration of switching node is performed via command frames transmitted by the management processor and destined to a command engine associated with the switching node. Services provided by the management processor are requested via control frames destined to the switching node to which the management processor is attached and destined to the management port thereof. The advantages are derived from engineered switching node deployments wherein an appropriate number of management processors, less than the number of switching nodes in the stack, are employed to provide services to corresponding switching nodes in the stack, based on processing, control, and configuration bandwidth requirements. The in-band configuration and control of the switching nodes in the stack reduce deployment, configuration, management, and maintenance overheads.

The invention discloses a method for deploying services in cloud computing environment. The method the following steps: a developer describes the provided service through using a cloud platform service definition language conceptual schema definition language (CSDL) defined by the invention, submits the service to a cloud platform; the cloud platform selects an optimal node deployment server according to the cloud node and the load of the service, and generates a search rule according to the CSDL; and a service user searches available services and calls the available services through accessing a cloud service warehouse. The system also provides a standby deployment system for ensuring the robustness, and periodically inspects the operation condition of the cloud node; the redeployment service reaches optimization; and by utilizing the method, the cloud platform is enabled to have higher service efficiency and fault tolerance; and in the cloud environment, the service provider does notneed maintain the environment of service operation by self, and submits the service to the cloud environment.

The invention proposes a visual modeling method for a distributed simulation platform and aims to provide a visual modeling method capable of lowering the development complexity of all nodes of distributed simulation. The method is realized by the following technical scheme: creating a simulation platform framework and visual modeling related components; performing distributed simulation deployment visually; dividing the simulation platform framework into an application layer, a management layer, a service layer, an interaction layer, a resource layer and a simulation model resource pool from top to bottom, wherein the management layer comprises a model interaction component and a node deployment component; generating an icon arranged in the simulation model resource pool by the model interaction component according to an interface attribute of a simulation model; seamlessly connecting logic deployment and physical deployment of simulation system nodes; automatically generating corresponding software interfaces and corresponding service components by simulation sub-nodes participating in distributed simulation through a node deployment graph; and performing visual modeling in a model interaction view to construct a visual model convenient for a user to design the simulation model interaction view.

The invention discloses an optimal deployment method of a large-scale industrial wireless sensor network based on differential evolution algorithm, which ensures the system reliability through carrying out optimization deployment on nodes, and relates to two fields of industrial wireless sensor network and intelligent computation. The method comprises the following steps of: carrying out automatic coordination on spaces according to actual spaces of industrial sites, obstacles, wireless sensor power and accurate requirement; and using the total number of nodes and minimum load standard difference of cluster heads as targets, wherein a node deployment model is established for restriction conditions based on the redundancy requirement, '1' represents arrangement of the cluster heads corresponding to mesh points, and '0' represents no arrangement. The invention provides a new binary differential evolution algorithm for optimizing and solving the model. By using a new probability prediction operator, the population is updated by a generated binary variation individual. The method can ensure the system reliability, and can reduce the construction cost of the system at the same time, balances the system energy consumption and prolongs the network life cycle through the optimization deployment of the nodes.

The invention relates to a wireless sensor network node deployment and power supply method. The method comprises the steps of establishing a network node topological structure communicated with and covered by a network, determining the positions of energy consumption hotspots in a current network node topological structure by utilizing a preset data routing path selection algorithm according to the network node topological structure, carrying out deployment of renewable energy source nodes according to the positions of the energy consumption hotspots, and carrying out deployment of battery nodes on other network nodes in the current network node topological structure, dynamically adjusting power supply strategies of the battery nodes according to the power supply states of the renewable energy source nodes. Through the wireless sensor network node deployment and power supply method, under the restriction of limited number of the renewable energy source nodes, according to the positions of the energy consumption hotspots of the network, the number and the positions of the renewable energy source nodes can be determined, the combined deployment of different energy source nodes can be completed, the work tasks and the states of different nodes can be determined according to the conditions of collection and transformation of renewable energy sources, and the continuous stable work of the network and the maximized utilization of the renewable energy sources can be achieved.

The invention discloses a building and energy-saving deployment method of a network model based on internet of things and belongs to the field of internet of things communication technologies. The invention provides a three-layer network framework and network energy consumption optimization model based on the internet of things. The energy-saving deployment method includes the steps: firstly, eliminating alternative relay nodes which cannot communicate with any sensor node according to the distance between the sensor nodes and the alternative relay nodes, then choosing i relay nodes in the rest of the relay nodes, equating the sum of sending energy consumption of sending nodes in each section of link and receiving energy consumption of receiving nodes in each section of link with a weight of the section of link when the i relay nodes meet the condition that whether topology which is formed by all standing sensor nodes and a station is a connected graph, obtaining a minimum value of energy consumption and survival time of a network in an improved Dijkstra method, and taking the network node deployment method under the energy consumption as an optical energy-saving deploy method.

The application suitable for the technical field of cloud provides a cluster deployment method and device, terminal equipment and a storage medium. According to the cluster deployment method, a node to be deployed of a cluster host is determined and a preset first configuration file is invoked; a deployment environment of the cluster host is initialized according to the first configuration file; asecond configuration file of a to-be-deployed node of the cluster host, is generated so as to generate a corresponding configuration file for the to-be-deployed node of the cluster host without manually configuring node parameters for each node by a user; according to the second configuration file, a node corresponding to the cluster host is deployed in the initialized deployment environment, sothat the system can deploy the node of the cluster host according to the second configuration file to complete cluster deployment. Therefore, according to the cluster deployment method provided by theembodiment of the invention, manual configuration of a user is not needed from environment deployment of the host to node deployment of the host, one-key cluster deployment is realized, and the deployment efficiency is improved.

The invention relates to a similarity based wireless sensor network mobile node positioning method. The method includes the steps: after anchor node deployment is finished, each anchor node uploads a data package including self node ID (identity) and position to a sink node, and the sink node collects the data packages of the anchor nodes to establish a digital link list; according to anchor distribution information in the digital link list, the sink node performs virtual grid division for a greenhouse and returns to a coordinate of grid vertexes except for those outside a zone boundary; the sink node collects a group of RSSI (radio signal strength indication) values of communication of mobile nodes with the anchor nodes and coverts the values into distance vector by the aid of a simplified lognormal shadow model; similarity among the distance values corresponding to the mobile nodes and the grid vertexes except for those outside the zone boundary is computed through a similarity function; and a centroid of a zone enclosed by a grid vertex set with the highest similarity serves as an estimated coordinate of the mobile nodes. The method is accurate in estimation of mobile node coordinates, low in computation complexity, perfect, and excellent in positioning performance.

A method and apparatus for deploying a plurality of seismic sensor units into a water column is described. The method includes providing a length of flexible cable from a cable storage device disposed on a vessel to a powered sheave, the cable having a plurality of spaced apart attachment points, routing the cable from the powered sheave to pass adjacent a workstation disposed on the vessel, deploying a free end of the cable into the water column while increasing the motion of the vessel to a first speed, operating the vessel at the first speed while providing a deployment rate of the cable at a second speed, the second speed being greater than the first speed, decreasing the second speed of the cable as an attachment point approaches the work station, and attaching at least one of the plurality of seismic sensor units to the attachment point at the workstation.

The invention discloses a wireless sensor network relay node deployment method. The method comprises the following steps of 1) obtaining deployment positions of base stations and sensor nodes as well as deployment candidate positions of relay nodes and constructing a heterogeneous communication diagram; 2) selecting a first set XA of the least relay nodes which can perform k-coverage of all the sensor nodes based on the heterogeneous communication diagram; 3) constructing a forwarding communication graph with edge weight based on the first set XA, the deployment positions of the base stations, and the deployment candidate positions of the relay nodes; 4) obtaining a second set XB of the least relay nodes which can connect the first set XA and the base stations based on the forwarding communication graph; and 5) combining the first set XA and the second set XB and constructing a final solution. The wireless sensor network relay node deployment method is capable of ensuring the network connectivity, guaranteeing that each sensor node has at least one path to connect with the corresponding base station, and also ensuring that the fewest possible relay nodes are deployed on the premise of ensuring the network connectivity.

The invention relates to a node deployment and election method of a block chain. The node deployment and election method of the block chain introduces a super node, each master node can be a candidatefor the super node as long as it meets the eligibility criteria. The stochastic algorithm selects the miner super node for PoW mining under the same probability. The method reduces the redundancy among nodes and improves the throughput of transaction verification and the computational performance of workload certification.

The invention provides a cluster unmanned aerial vehicle ad hoc network clustering method which can improve the stability of the whole network. The method comprises the steps that a cluster head is initialized, and the cluster head broadcasts cluster head invitation information to surrounding nodes; a surrounding region is divided by a cluster head according to a region-based division method imitating a bird flock, and dividing a cluster structure in a self-organizing network into a cluster head region, a node attraction region and a node rejection region; Wherein the nodes in the cluster head area are cluster head candidate nodes; Wherein the node attraction area comprises a gateway area and a member area, nodes in the gateway area are gateway nodes in the cluster, and nodes in the member area are member nodes in the cluster; Wherein the nodes in the node rejection area comprise idle nodes and nodes in other clusters; And when the idle node receives invitation information broadcastedby a plurality of cluster heads in a preset first time period, marking the state of the idle node according to the signal intensity of the received invitation information to complete node deployment.The invention relates to the field of unmanned aerial vehicles.

The invention discloses a charging and settlement method of international roaming communication, a charging device, a settlement device, and a distributed system. The charging method comprises the following steps: generating a communication bill and billing data when the international roaming communication occurs, sending data to one or multiple equal operator nodes, and storing the data to a block chain. The charging and settlement device of the international roaming communication is deployed in one or multiple operator nodes in the distributed system, so that each operator node in the distributed system can verify the truth and the integrity of the communication bill and the billing data; meanwhile, the user can instantly query the communication consumption data, and the communication service experience of the user is improved.

The present application discloses a virtual resource arrangement method and apparatus, and belongs to the technical field of computers. The method comprises: acquiring an arrangement template, wherein the arrangement template comprises configuration parameters of relationship indication information of at least a first to-be-arranged virtual resource and a second to-be-arranged virtual resource between which a dependence relation exists, and the first to-be-arranged virtual resource and the second to-be-arranged virtual resource both can be a virtual machine or a container, and the relation indication information of the first to-be-arranged virtual resource and the relation indication information of the second to-be-arranged virtual resource can jointly indicate a specified parameter for the second to-be-arranged virtual resource to depend on the first to-be-arranged virtual resource; creating a corresponding first virtual resource and second virtual resource based on the configuration parameters of the first to-be-arranged virtual resource and the second to-be-arranged virtual resource; and transmitting a parameter value of a specified parameter in the first virtual resource into the second virtual resource. The method disclosed by the present application can improve efficiency of application node deployment and simplify the process of application node deployment.

The embodiment of the invention discloses a blockchain node deployment method, device and equipment and a storage medium. The method comprises the following steps of calling an Ansible tool to establish communication connection with a target node, and establishing a Kubernetes cluster in the target node; and calling the Ansible tool to obtain a target block chain version mirror image file, creating a container in the Kubernetes cluster of the target node according to the target block chain version mirror image file, and deploying the block chain nodes in the container. According to the embodiment of the invention, by calling the Ansible tool, the nodes to be deployed are prevented from being invaded, by building the Kubernetes cluster in the target node, and utilizing the characteristic that the Kubernetes cluster supports multiple container technologies, the cross-platform block chain node deployment is achieved, and the deployment efficiency of the block chain nodes is improved.

The embodiment of the invention discloses a node deployment method and a node of a sensor network. The method comprises the following steps of: deploying sensor head nodes at fixed positions of a perception area, wherein all sensor node information in the perception area is prestored in the sensor head nodes; moving other nodes which are randomly deployed to the head nodes according to a fence line until other nodes are directly or indirectly communicated with the head nodes; determining movable nodes and uncovered areas according to information which is exchanged by communicating the nodes; and diffusing the movable nodes to the uncovered areas so as to ensure coverage rate. By the method and the node, the coverage rate of the nodes in the movable sensor network can be improved, the moving distance of the nodes can be reduced and the network connectivity can be ensured when the nodes of the mobile sensor network are deployed.

The invention provides a content route managing method of a fusion type content distribution network, belonging to the technical field of internet. The invention aims to provide a two-layered content node deployment mechanism aiming at ISP-CDN (Internet Service Provider-Content Distribution Network) and design an indexing and synchronization mechanism to improve a content route policy under a CDN environment; a flow settlement cost and data transmission quality are considered. The network data is singly processed, namely the flow cost consumed by primary transmission is only related with a passed route hop count and the size of the data is not considered; an inverse ratio relation is formed between the node quantity selected from a core route node set F and the repeated flow; a synchronous cost is in direct proportion to the node quantity; a synchronous initial source is an inter-domain router node; with regard to an inter-domain route node t, a breadth first search algorithm is used for generating k content nodes covered by a minimum spanning tree TR which takes the t as a root; the k notes are found and an RC+SC minimum is realized by adopting an algorithm based on a greedy strategy.

The invention discloses a sensor-network-based low-energy-consumption ecological environment monitoring node deploying method and relates to the Internet of Things. The method comprises the following steps: firstly determining factors to be monitored and key points with relative factors; building an optimal mathematic monitoring model according to the monitored factors and the key points; then solving the mathematic model and finding a key point with most attributes and taking the key point as a pre-selection point; invoking an attribute optimizing method for selecting the key points with all the attributes which are close to an attribute mean value if the number of the pre-selection points is greater than 1; invoking a crop growth factor weighing method for determining monitoring points if more than two pre-selection points exist after the treatment; randomly determining that the pre-selection points processed by the crop growth factor weighing method are taken as the monitoring points by using a random algorithm; finally processing a matrix T formed by the key points and the attributes by using a matrix optimizing method of the key points and the attributes to obtain the number of the final monitoring nodes and the distribution positions of the monitoring nodes.

The invention provides a private cloud deployment method. The method comprises steps: a container cluster environment is deployed according to acquired container cluster environment deployment information, a container mirror corresponding to OpenStack module service set for the node by a user is acquired from a container service mirror warehouse, and a corresponding container is started according to the acquired container mirror in the container cluster environment; a cluster node set by the user is received, and the cluster node is announced to deploy a specified operation system according to the specified operation system deployment information issued according to the node; and after the cluster node deploys the specified operation system, the cluster node is announced to deploy the container cluster environment according to the container cluster environment deployment information issued according to the node, and thus, after the cluster node deploys the container cluster environment, the corresponding container is started. Thus, a cluster mode and a container technology can be adopted for private cloud deployment, the stability and the expansibility for the private cloud deployment can be improved, and the private cloud deployment efficiency is improved.

The embodiment of the invention discloses a block chain node deployment method and related equipment, and the method comprises the steps: obtaining a node deployment mirror image file which comprisesa communication safety agent script, a node bottom layer script and a node service script; running the communication security agent script to establish a security connection with the node management device, and receiving a node configuration file through the established security connection; running a node underlying script to obtain node information of all nodes in the target blockchain from the node configuration file, and determining the node information of all nodes in the target blockchain as attribution blockchain node information; running a node synchronization script according to the attribution block chain node information, obtaining node state synchronization information from any node of the target block chain, and updating the node state of the first device according to the nodestate synchronization information; and running the node service script, and responding to the received blockchain service request of the user. According to the invention, the deployment efficiency ofthe blockchain nodes can be improved.

The invention discloses a decentralized mobile edge computing resource discovery and selection method and system. The method and the system are used for solving the problems of how to select servicesrequested by a mobile edge computing node to deploy Internet of Things equipment with optimal service quality by a service provider and how to discover existing services in adjacent mobile edge computing nodes so as to avoid repeated deployment and save edge resources. Through a three-layer layered mobile edge computing network topology, mobile edge computing nodes are put into a plurality of clusters / groups according to geographic positions, each cluster is controlled by regional cloud, and the computing overhead is reduced compared with the adoption of a centralized controller. Based on a content center network, through expanding a content center network table, a unified protocol is introduced, and service autonomous discovery and autonomous deployment are realized. The computing servicequality such as transmission delay and node performance is comprehensively considered through a mathematical model, and service discovery and deployment decisions are made, so that the service quality of the node where the requested service instance is located is optimal for the Internet-of-things equipment requesting the service.

The invention discloses a covering method for a three-dimensional directional movement-based underwater wireless sensor network. The covering method comprises the following steps: (1) transmitting information to neighbor nodes by underwater wireless sensor nodes; (2) performing statistics on the number and the positional information of the neighbor nodes by each node, and meanwhile, computing the distance from each neighbor node to the nodes; (3) computing virtual distance vectors that the nodes need to move for all the neighbor nodes in sequence according to the positional information of the neighbor nodes; (4) computing the distance from each node to the boundary of a deployment area and the virtual distance that each node needs to move to keep away from the boundary according to node coordinates; (5) performing weighted summation on the virtual distance computed in the step (3) and the virtual distance computed in the step (4), and performing optimization on all the underwater nodes in the whole network in sequence according to the order of ID (identity) numbers of the nodes. According to the covering method disclosed by the invention, fine adjustment optimization is performed on positions of the nodes, and therefore, node deployment in the network approaches to uniform distribution so as to optimize and improve the coverage rate of the whole underwater three-dimensional network.

The invention relates to a bridge-type-based wireless sensing network key management scheme. The bridge-type-based wireless sensing network key management scheme includes the following steps that firstly, key pre-allocation is carried out, and namely allocation information is preset onto each sensor node by a starting server before node deployment; secondly, in the clustering phase, after cluster head nodes are selected, the clustering phase begins immediately, and each sensor node is added to the corresponding nearest cluster in the clustering process; thirdly, in the neighbor node discovery phase, whether other nodes are to be recorded as neighbor nodes or not is determined by each sensor according to the included angle calculation formula; fourthly, intra-cluster matched keys are built, wherein matched keys between each sensor node and other neighbor nodes are worked out through the bridge type; fifthly, inter-cluster matched keys are built, wherein matched keys between each cluster head node and other cluster head nodes are worked out through symmetric bivariate polynomials. By means of the scheme, on the premise that a certain connection rate is guaranteed, information transfer safety and effectiveness can be guaranteed, and the memory space of a memory is well saved.

A customized template cloud platform dynamic spread deploying method applied under distributed environment comprises the steps that a basic deploying environment is created, different templates are customized based on input, a central node distributes the customized templates and manages clusters, a seed node selects the optimal deploying subnode on the basis of the templates according to the dynamic spread rule, the clusters are deployed rapidly, and a distributed type state sensing and fault-tolerant mechanism is implemented between the nodes. A new source node is generated dynamically on the basis of the central node deployed in the distributed environment, distribution loads of the central node are shared continuously, and a newly deployed node is allowed to obtain content needed in node deployment from one or more sources, so that the deploying efficiency of a cloud platform under the distributed environment is greatly improved.