290 results about "Distributed algorithm" patented technology

Embodiments of the invention employ a distributed algorithm to enable sensor nodes in a sensor network to adaptively self-configure into sensor clusters to provide a desired higher-level functionality.

A centralized resource distribution is described where the decision portion of partitioning data among cluster nodes is made centralized while the actual mechanics to implement the partitioning remain a distributed algorithm. A central distribution coordinator is used to create an extensible central strategy that controls how the data will be partitioned across the cluster. The work to implement this strategy is performed by all of the members individually and asynchronously, in accordance with a distributed algorithm. The central strategy can be communicated to all cluster members and each member can perform the partitioning as it relates to itself. For example, in accordance with the distributed algorithm, one node may decide that it needs to obtain a particular partition in light of the central strategy and carry out the necessary steps to obtain that data, while other nodes may be asynchronously performing other individual partition transfers relevant to those particular nodes.

The invention discloses a recommendation system building method based on cloud computing, which belongs to the field of cloud computing and recommendation system building. In the method, a Hadoop cloud platform with a plurality of nodes is built firstly; then a Mahout middleware is built on the Hadoop; a Mahout algorithm library is customized according to business demands; a traditional advancing algorithm, a pseudo-distributed advancing algorithm, and a distributed algorithm are realized on the Mahout middleware; and finally a recommended application framework is built according to the demands of users. With the invention, as a serial recommended algorithm and MapReduce are combined to realize a parallel algorithm, the processing efficiency can be effectively improved; a large quantity of data which can not be processed under the condition of using a single machine can be completed; and the recommendation results can be supplied to users very quickly.

Various systems and methods that synchronize local copies of a variable used in a distributed algorithm, such as that used in distributed policing, are disclosed. For example, one system includes several distributed algorithm participants that are coupled to communicate with each other. Each of the each of the distributed algorithm participants maintains a shared variable in order to implement the distributed algorithm. One of the distributed algorithm participants is a synchronizer. The synchronizer is configured to calculate a new value of the shared variable and to communicate the new value to each of the other distributed algorithm participants. The distributed algorithm can be a distributed policing algorithm, and the shared variable can be a global bucket.

The invention relates to the cross field of geographic information and information technology, in particular to a distributed algorithm for quickly establishing a massive remote sensing image pyramid applied to the construction of National Spatial Data Infrastructure. The method realizes the algorithm for quickly establishing the massive remote sensing image pyramid by means of data distribution storage and parallel computation capabilities based on a PC (Personal Computer) cluster, through the steps of dividing N*M grids, performing pyramid establishment task distribution and scheduling and pyramid establishment and correctly dividing grids and computing grid information, and by means of a communication transfer task between a control node and a computation node; and the method mainly aims to solve the related technical problem of how to divide the N*M grids, etc. The distributed algorithm for quickly establishing the massive remote sensing image pyramid has the following advantages that: based on the data distribution storage and parallel computation capabilities, the speed of generating the massive remote sensing image pyramid is increased; and the problem of black edges causedby image block documents crossing grids is solved; therefore, the purpose of increasing the pyramid establishing speed is achieved and the pyramid establishment accuracy is ensured.

A system for the distributed diagnosis of a physical system includes serveral local diagnostic subsystems that generate local diagnoses based on observations of a component of the physical system. An interface is defined by which the local diagnostic subsystems communicate. Further, an algorithm for assembling a global diagnosis from the local diagnoses is fined.

The invention discloses a wireless network sensor network coverage distributed method. Assigned task completion time is set as a fixed value, and a mathematic model is established aiming at how to enable coverage of nodes-to-point positions to be maximum; the assigned task completion time is divided according to turns to solve the model, how to select the most suitable working node in each turn and close other redundant nodes at the same time is achieved, and the actual network service life is made to be longer than the assigned task completion time; in addition, how to select the optimal working time scheme of the working nodes in each turn to enable the coverage of nodes-to-point positions to be maximum is achieved; therefore, an improved distributed algorithm is proposed. According to the wireless network sensor network coverage distributed method, through simulation experiments, the performance of the improved algorithm exceeds that of an original algorithm and that of a random algorithm in the aspects of total effective coverage time, network service life, average weighting event detectivity and network node residual energy evenness.

The invention relates to a hardware multiply-accumulate algorithm and particularly relates to a signed multiply-accumulate algorithm method using an adder tree structure. According to the method, data are divided into two parts, i.e. coefficient items and data items, by adopting a complement form, the data items are decomposed into bit units according to a binary principle, the coefficient items are subjected to binary multiplication with bits of the data items according to an addition allocation principle, and the products are subjected to binary accumulation so as to obtain a final output result. The signed multiply-accumulate algorithm method using the adder tree structure overcomes the disadvantage of fixed coefficients of the original DA distributed algorithm and does not need a large number of ROMs (Read Only Memories) to serve as a coefficient table, the occupied area of a chip is smaller, the multiply-accumulate calculation of signed numbers is realized, and the extension is convenient, so that the signed multiply-accumulate algorithm method is especially suitable for the realization of a programmable logic device.

The invention provides an adaptive augmented interference-resisting fault tolerance method for aiming at active segment flight of a vertical take-off and landing carrier, wherein the method belongs tothe field of aerial vehicle control technology. The method comprises the steps of 1, designing a basic PID controller; 2, designing an adaptive gain regulating law; 3, executing an interference compensating algorithm; 4, executing an optimal control distributing algorithm; and 5, executing a quick fault detecting and adaptive fault tolerance control algorithm. The method can satisfy an actual flight control requirement and realizes simple control parameter designing and detailed control performance indexes for representing. Furthermore the method has advantages of higher robustness, higher adaptability, simpler control structure, etc.

The invention discloses a distributed type digital beam formation network which completes parallel multiply-accumulate operation by using memory resources to replace hardware multiplier resources according to a distributed algorithm, is especially suitable for hardware system framework with rich memory resources, such as a FPGA (Field Programmable Gate Array), and the like and also can be realized by configuration of a flash memory, and the like, and therefore, the invention greatly reduces the requirement of hardware resources and the difficulty of hardware design and uses lower cost to process complicated large-scale beam formation.

The invention discloses a virtual resource dispatching system for related task requests and a dispatching and distributing method for the related task requests. Operation performance can be effectively guaranteed when the communication related tasks exist, and meanwhile an effective balance point is selected from a system load. In addition, by the adoption of dominant_share evaluation features based on a DRF, it can be prevented that too many resources are distributed, and fragments of partial resources are generated. By the adoption of a distributing strategy based on greed, compared with a linear programming algorithm, the distributing algorithm has a great time performance advantage, the dispatching time delay is reduced, and good user experience is obtained. Finally, the dispatching algorithm can improve the resource utilization condition of a platform, reduce the number of available tasks in waiting, increase the resource utilization rate of the cloud computing platform, and improve the performance of the platform and the overall processing performance of the platform.

The invention discloses a WSN (Wireless Sensor Network) anomaly detection method based on an MEA-BP neural network. The method comprises the following steps: initializing various distributed sensor nodes, and starting to acquire data by various sensor nodes; using a K-means algorithm to perform space clustering on the various sensor nodes to obtain a plurality of cluster structures; using a mind evolutionary algorithm to perform parameter optimization on a BP neural network, optimizing the weight and threshold of the BP neural network through a convergence and dissimilation operation, obtaining optimal weight and threshold, inputting the optimal weight and threshold, and establishing an MEA-BP neural network model; and adopting a distributed algorithm to execute anomaly detection on the sensor nodes in each group of clusters independently, after anomaly detection is finished, transferring a detection result to cluster head nodes of the group of clusters for further verification by the sensor nodes. The WSN anomaly detection method based on the MEA-BP neural network provided by the invention improves the algorithm performance of the BP neural network, accelerates the learning rate of the BP neural network, effectively improves the accuracy of the abnormal data detection and reduces the false positive rate.

Embodiments of the present invention relate to a data processing system and method and, in particular, to a distributed computing system and method that uses a globally distributed data structure comprising an indication of local state information associated with at least some of the processes constituting a distributed algorithm in influencing at least one of the execution and the termination of those processes.

The invention discloses an interference management self optimization method based on non-orthogonal multiple access, and belongs to the field of wireless network. The method comprises the following steps: firstly, in a super dense scene, for a fixed sub-bandwidth, each small base station separately calculates a signal to noise ratio to a respective request user, deletes the adjacent interference base stations of the present base station according to the sensed interference signal intensity of the adjacent base stations, and independently constructs a dynamic local interference map; then, each small base station independently accomplish resource allocation by comprehensively considering the communication demand and the information of the local interference map, in order to reduce the interface among the networks, the interference optimization problem is modeled as a game problem based on satisfaction, a resource allocation result is obtained by using a distributed algorithm, each small base station reasonably allocates different power and sub-bandwidths to respective request users, so that the system interference is maximized. By adoption of the interference management self optimization method, the network interference is reduced, ensures the communication needs of the user is ensured, and the convergence is good.

The invention discloses a self-organizing cognitive wireless network routing method, relating to the problem of a self-organizing (Ad Hoc) network routing strategy based on cognitive radio. No control center is provided in the network, each node determines the next hop node as well as the channel communicated with the next hop node only based on local information, and chooses the optimal route to realize the communication from a source node to a destination node according to defined routing standard. According to the routing strategy of the invention, the transmission rate of multiple links obtained by distributed algorithm in the Ad Hoc network is closer to the optimal value obtained by the centralized algorithm, and simultaneously ensuring that more links can find communication paths.

A computer system comprising a plurality of computers coupled through a network, the computer system performing service by using a database constructed by a storage area of each of the plurality of computers, wherein a plurality of pieces of data are located in the plurality of computers constructing the database based on a distributed algorithm for distributing and locating the plurality of pieces of data in the plurality of computers, wherein the computer system comprises: a load information management part to manage load information on a load of each of the plurality of computers constructing the database; an algorithm management part to switch the distributed algorithm of the computer system based on the load information; and a relocation processing part to relocate the plurality of pieces of data stored in each of the plurality of computers based on the switched distributed algorithm.

The invention discloses a real-time mining method and device based on distributed data. The method comprises the steps that centralized serial data is decomposed into executable parallelly-operated data; when the executable parallelly-operated data is accumulated to reach a predetermined quantity, and data modeling is performed according to a distributed algorithm based on a memory to obtain a data model; processing is performed according to the data model and auxiliary data to obtain a data processing result.

The invention discloses a short message gateway with better isomerous network communication property and the short message isomerous network communication processing method adopted by the same. The short message gateway comprises a interface machine and a plurality of service processors, wherein the interface machine takes the charge of transmitting and receiving short messages and distributing the received short messages to each service processor for processing according to the specific distributed algorithm; when the interface machine transmits the short messages, the number of TCP (Transmission Control Protocol) connection between the interface machine and other short message gateway is more than one and is dynamically adjusted. The invention provides two adjustment ways including the set constant flow threshold adjustment and the self-adapting adjustment according to each connection load; when one of the multiple connections with non-maximum code is disconnected, all disconnected connection codes reduce one; and one of the service processors is selected as the main service processor, and then the present network services and the short message service in the transmission direction are processed by the main service processor.

The invention discloses a multi-cell coordinated distributed robust beamforming method. A central problem is converted into a form of multiple subproblems and a main problem through a dual decomposition theory, and the subproblems are converted into semi-definite programming (SDP) problems through the semi-definite relaxation (SDR) and S-procedure technology in a complex field and then solved. The main problem is solved through a sub-gradient algorithm, the lagrangian dual problems of respective subproblmes are solved to obtain the lagrangian multipliers and are exchanged through a return link at each base station, and the base station calculates the sub-gradient of the main problem at a disturbance item between cells according to the obtained multiplier information of other base stations, so that the main problem can be rapidly solved through the sub-gradient algorithm. The distributed algorithm is simulated and displayed through an actual cellular system, the performance close to the central algorithm can be achieved through a little iteration, and the algorithm is high in convergence rate when the channel error is low.

A method to provide a cyber attack resistant and fault tolerant precision clocking scheme for wide area critical infrastructure networks through what is called Distributed Time Source Validation, DTSV, is provided, which is a distributed algorithm and signaling mechanism for a network to detect a compromised time source or sources in a multiple master clock system. The method includes providing a local clock signal, receiving in a node R1 an external clock signal from an external source, C or S1, estimating based on the local clock signal and the external clock signal timing parameters associated with the first node and the external source, comparing the timing parameters to detect any Mutual Clock Discrepancy (MCD) between the first node and the external source, and distributing any detected MCD in the network.