80 results about "Distributed decision" patented technology

A lightweight application server for use on portable or embedded devices includes an application manager and services containers. Each of these is managed by an admin server allowing for remote and rapid deployment and maintenance of applications, objects and features associated with the server-enabled portable or embedded devices. This permits portable devices like PDAs to provide server functionality to each other, in a fully portable network if desired. A system including such server-enabled portable or embedded devices may include, among other things, a decision flow server for facilitating distributed decision flow processing.

Methods, apparatus, and computer software product for making a decision based on the semantics of formal logic are provided. In an exemplary embodiment, two custom computing apparatuses are used to resolve the satisfiability of a logical formula and provide an example. In this embodiment, the two custom computing apparatuses operate in concert to explore the space of possible satisfying examples. This Abstract is provided for the sole purpose of complying with the Abstract requirement rules. This Abstract is submitted with the explicit understanding that it will not be used to interpret or to limit the scope or the meaning of the claims.

A Session Admission Control (SAC) for negotiating admission control in a multi-services communications network including multicast services is described. The module distributes the admission process between a centralized decision function (SAC-PDP) and a distributed decision function (SAC-M) in a fashion that solves admission control scaling problems. The mechanism for interaction between the SAC-PDP and SAC-M is defined. Mechanisms are defined for the SAC-PDP to discover or learn the network capacity against which the admission control decisions will be made. Systems are also described for incorporating SAC-M in multicast replication points in the network, allowing multicast replication points to participate in the admission control process.

The invention relates to an EHV (Extra-High Voltage) power grid fault rule mining method based on a rough set association rule. According to the method, a distributed data mining idea is adopted, historical fault data of an EHV power grid is subjected to fault rule mining by using an association rule mining method based on a rough set theory, a distributed decision table is subjected to attribute reduction by using an attribute reduction algorithm based on an information entropy, and then, an Apriori algorithm in association rules is applied to the decision table, which is subjected to reduction, so as to carry out fault rule extraction. According to the method, the problem of inadaptability to large-data-volume historical fault databases of traditional data mining methods can be solved effectively, the complexity of rule extraction is lowered, and the method has the advantage of high fault rule mining efficiency.

The invention belongs to the blockchain technology field and discloses a distributed energy dispatching transaction method based on a global energy blockchain. By constructing a global energy Internetsystem based on a global energy blockchain, the global energy blockchain may have an effect of a distributed ledger. By using the global energy blockchain, low-cost channels for direct communicationare established between massive smart devices. Further, through a decentralized consensus mechanism, the security and privacy of the global energy Internet system is improved. A reliable mathematic encryption algorithm is used to protect the user's privacy. Through distributed decision, various organizations participate together to enhance recognition degree. Ultimately, the self-management and maintenance of the global energy Internet system is achieved, the global energy Internet system is converted into a decentralized, self-organizing, and self-regulating system, point-to-point value transmission without the intermediary trust and secure distributed data sharing are achieved, and a global energy Internet distributed platform is constructed.

An OFDM communication system employs a cell time division time frame for a plurality of overlapping cells wherein the time frame comprises time slots with each time slot allocated to one of the overlapping cells and each time slot being either an information exchange time slot or a data time slot. Remote nodes (101-105) transmit resource requests for at least one subcarrier in a data time slot to one or more of the central nodes (107, 109) in the information exchange time slots of those nodes (107, 109). The central nodes (107, 109) broadcast information of uplink channel characteristics received in the request messages and the remote nodes (101-105) use this to determine whether to abandon or continue the resource request. Eventually, the remote node may decide to use the resource and thus to transmit in the associated data time slot. A distributed multi-cell resource allocation can be achieved based on distributed decisions in the remote stations.

A distributed decision support system is described for use in the area of problem discovery and capacity planning for database applications. The use of data navigation, particularly drill down, roll up, and pivot for application management tasks are described. The system presents data collected from components of an application server system by various cartridges to users in a way that facilitates the identification of problems in the application server system and provides for an efficient way to do capacity planning of such systems.

Pre-charging two or more sets of nodes to set a differential output of a multi-input summation latch connected to the two or more sets of nodes in a pre-charged state, the two or more sets of nodes comprising a set of data signal nodes and a set of DFE correction nodes, in response to a sampling clock, generating a differential data voltage and an aggregate differential DFE correction signal, and generating a data decision by driving the differential output of the multi-input summation latch into one of two possible output states according to a summation of the differential data voltage signal and the aggregate differential DFE correction signal and subsequently holding the data decision by holding the differential output of the multi-input summation latch in a latched state for a duration determined by the sampling clock.

A Session Admission Control (SAC) for negotiating admission control in a multi-services communications network including multicast services is described. The module distributes the admission process between a centralized decision function (SAC-PDP) and a distributed decision function (SAC-M) in a fashion that solves admission control scaling problems. The mechanism for interaction between the SAC-PDP and SAC-M is defined. Mechanisms are defined for the SAC-PDP to discover or learn the network capacity against which the admission control decisions will be made. Systems are also described for incorporating SAC-M in multicast replication points in the network, allowing multicast replication points to participate in the admission control process.

The invention discloses a distributed decision making supporting massive high-concurrency access I / O server load balancing system, and is used for solving the problems of high performance computers, for example, the high performance computer is lack of file strips with high data concurrency access file level, an allocation method which is used for the strip-oriented files and can fully consider dynamic file access features, and a load balancing which supports the distributed decision making. The system disclosed by the invention provides a novel dynamic load balancing support which has high expandability and fully considers network delay and migration cost. Modularly, the system mainly comprises file level strips oriented to high-concurrency access request, file allocation capable of minimizing IO access conflict and the load balancing based on distributed decision making. The system can meet the application needs of the load balancing system of the high performance computers with massive high concurrency and distributed decision making. Thus, the system has the characteristics of being wide in application foreground and capable of generating remarkable economic benefit, and the like.

A method, apparatus and computer product that enables a processor associated with a node in a computer system having various nodes, the nodes having sensors which provide data, and the nodes being connected by a communications facility acquiring local data from the sensor and remote data from other nodes via the data transfer facility. The nodes process data from a local sensor at the node and from remote sensors at other nodes; and analyze the local data, data from other nodes and local decisions made at and received from other nodes to make a local decision for action at the node. A local decision made at a node is in turn communicated to other nodes.

A method supports a decision-making process in a time critical scenario managed by a distributed workflow consisting of a plurality of distributed nodes. The method includes assessing a given situation with available information to establish confidence percentages for possible decisions associated with the given situation and the distributed workflow. A distributed workflow architecture is provided that allows the distributed workflow to use the confidence percentages to enable a decision maker to get knowledge of a best possible course of action when executing the distributed workflow. Fuzzy logic is used to compute and maintain the confidence percentages for the possible decisions based on the available information. Furthermore, an appropriate workflow management system is proposed.

The invention discloses an automatic answering system which can provide answers for community customers on line in real time, reduce distribution processing pressure during an answering process and improve answering efficiency. Moreover, the system provided by the invention can continuously update and adjust knowledge databases and key words according to questions put forth by users and feedback information, thus improving the accuracy of answering and the satisfaction of the customers. Distributed decision of answering questions is realized by a communication conversion and pressure balancing module, a distributed decision module and a guide module; classification of knowledge points, extraction of key words and searching and matching for answering questions are realized by a searching and matching module of answering results; recording of knowledge data, user operation and feedback is carried out by a knowledge database module; updating and adjusting of knowledge point data are carried out respectively from the aspects of manual management and automatic learning by a learning analyzing module and a management and data maintenance module.

A computerized decision tree training system may include a distributed control processing unit configured to receive input of training data for training a decision tree. The system may further include a plurality of data batch processing units, each data batch processing unit being configured to evaluate each of a plurality of split functions of a decision tree for respective data batch of the training data, to thereby compute a partial histogram for each split function, for each datum in the data batch. The system may further include a plurality of node batch processing units configured to aggregate the associated partial histograms for each split function to form an aggregated histogram for each split function for each of a subset of frontier tree nodes and to determine a selected split function for each frontier tree node by computing the split function that produces highest information gain for the frontier tree node.

The invention discloses a cloud service robot based on a distributed decision-making algorithm, and relates to the technical field of robots. The robot comprises a robot body, and the robot body is connected with an Android man-machine interaction terminal through a WebService interface. The Android man-machine interaction terminal comprises a voice interaction module, a touch control interaction module, a safety management module, a robot teaching demonstration box module, a robot task level planning module, an environment information management module, a global video monitoring module, and a 3D virtual visualization platform. The voice interaction module is connected with a voice cloud, and the safety management module is connected with the 3D virtual visualization platform. The robot teaching demonstration box module, the robot task level planning module, the environment information management module and the global video monitoring module are respectively connected with the WebService interface. Through the cloud processing and analysis, the robot executes the specific operations, and perfectly plays roles in early education for children, the accompanying with the elders and a household health manager.

A decision support tool which takes a high-level view of supply and demand in the realm of labor resources and produces globally-optimal recommendations for assignment of practitioners to open seats. These assignments preferably optimize a utility function composed of different business metrics and can be customizable for different organizations and priorities.

The invention relates to a distributed access control method based on a block chain, and belongs to the field of information security. The method comprises the following steps: designing a distributed access authorization process: designing the distributed access authorization process according to the functions of each component in a distributed access control model B-ABAC based on a block chain; meanwhile, in the authorization process, recording generated authorization access records on the block chain; S2, designing an attribute and strategy intelligent contract: separating functions of attribute authority and strategy authority, and dispersing the functions into an intelligent contract and a block chain account book in the B-ABAC model; and S3, designing consensus algorithm: using the distributed decision network to replace original decision points, and designing and using the improved consensus algorithm to carry out consensus maintenance on the distributed decision network. In an untrusted environment, fine-grained and dynamic access authorization can be provided, meanwhile, the security and auditability of an access model are improved, and human intervention in the authorization process is reduced.

The invention discloses an intelligent traffic control system and method of a wireless sensing and driving a network. The system comprises a central control center, M zone gateway devices and N sensing-driving knots which form L clusters with L cluster heads, and each cluster comprises one cluster head and at least one sensing-driving knot. A multi-level structure is formed from the central control center, M zone gateway devices to N sensing-driving knots. For the system of the invention, each sensing-driving knot can senses the traffic state in time and exchanges information with other knots through a wireless communication way provided with self-error replying capability. The intelligent traffic control system adopts a distributed decision calculating frame to automatically regulate the control plans of each communication crossing according to the actual traffic state so as to realize an effective control to traffic.

The invention discloses a distributed energy cloud networking intelligent control method and a distributed energy cloud networking intelligent control system. The distributed energy cloud networking intelligent control method comprises the steps of: acquiring an optimal electric price curve, dividing time periods, allocating optimal allocation output or optimal allocation load to energy subnet at different time periods, controlling power generation equipment to generate power according to the maximum output for each energy subnet, and charging charging equipment when the charging equipment plugs into a charging pile; and controlling energy storage equipment to adjust actual output and actual load of the energy subnets. The distributed energy cloud networking intelligent control system comprises a central scheduling decision-making unit, an energy cloud networking allocation unit and a distributed decision-making execution unit. The distributed energy cloud networking intelligent control method and the distributed energy cloud networking intelligent control system achieve the effects of reducing excess load and output surplus by taking the energy subnets as a unit based on controlling the controllable loads such as the energy storage equipment in the energy subnets and the charging pile, achieve the purposes of power grid load balancing, peak shaving and load shifting, can prevent charging of various kinds of large-scale charging equipment from affecting peak of the power grid, achieving efficient / optimized configuration of energy resources, and enhance social and economic benefits.

Pre-charging two or more sets of nodes to set a differential output of a multi-input summation latch connected to the two or more sets of nodes in a pre-charged state, the two or more sets of nodes comprising a set of data signal nodes and a set of DFE correction nodes, in response to a sampling clock, generating a differential data voltage and an aggregate differential DFE correction signal, and generating a data decision by driving the differential output of the multi-input summation latch into one of two possible output states according to a summation of the differential data voltage signal and the aggregate differential DFE correction signal and subsequently holding the data decision by holding the differential output of the multi-input summation latch in a latched state for a duration determined by the sampling clock.

An embodiment of the invention provides a technique that extends relevance-based computation to include computation based on information accessed from or exchanged with other agents. Mechanisms are provided by which an agent accesses or exchanges information between or among other agents and may include one or more of: central bulletin board, broadcast, direct request—pull, direct request—push, and server-routed. Architectural models of distributed decision making to facilitate a distributed and policy-based management of IT infrastructure are provided.

The invention discloses a group self-organization cooperative control method of an underground mining hydraulic support system. According to the characteristic of multiple constraints and a cooperative support effect, performed on surrounding rocks, of underground mining support devices, influences, on sedimentation and collapsing of the surrounding rocks, of organization, group stability and group propulsion cooperativity of the support system are considered, local information interaction between support individuals as well as between supports and the surrounding rocks and an independent decision-making distributed control strategy are adopted for eliminating a main control mechanism of an existing support group, and a cooperative operation system of independent control and distributed decision making performed on the individuals in the group is established; a mixed control method of social potential fields and behaviors is adopted for establishing a control function, and self-adapting supporting of the surrounding rocks and self-organization queuing and cooperative propulsion of the large-scale support group are achieved. The problems that due to a centralized control method, the information interaction between the individuals is lack, the multi-dimensional dispersed group behaviors can not be converged into an overall object are solved, and the method is adapted to underground mining conditions and an underground mining technology more flexibly, and effectively meets automatic and unmanned mining requirements.

The invention discloses a Supply-Hub-based supplier management inventory operation method. According to the method, one three-level supply chain including two suppliers, a Supply-hub centralized distribution center and a single manufacturer is used as a research object, a centralized and distributed decision game thought is respectively applied to establish a model to solve an optimal pricing strategy, the service level is used as a variable to be considered into a target function, and the influence of the service level on a decision result is analyzed. A supplier management inventory mode isa VMI mode; the Supply-Hub is a centralized distribution center and belongs to fourth-party logistics and helps to coordinate the whole supply chain, and suppliers can directly deliver inventory management rights to a centralized distributor (hub operator); particularly, under the condition of uncertain supply or demand, Hub coordination is achieved, by means of leading-edge technologies such as abig data sharing platform, the demand of a manufacturer is monitored and predicted in real time, JIT real-time distribution of parts is achieved, and meanwhile the inventory cost is reduced.

The invention belongs to the field of data safety and particularly relates to a self-adaptive distributed intelligent decision making method. Possible abnormalities are detected through exploiting aiming at real-time monitoring logs and operation request logs, advantages of a neutral network in mode recognition and knowledge based reasoning theories are combined, a self-adaptive mechanism is introduced on the basis of integrating of multiple adjacent node data to realize intrusion detection in a distributed manner, and a decision making process is arranged in distributed nodes instead of a central control board, so that network transmission is reduced, and distributed decision making speed is increased. By integrating of information feedback of adjacent nodes, self-adaptive regulation is performed without dependency on global information, and accordingly data transmission is reduced, and intrusion data difficult for a single node to detect can be detected out effectively.

The invention relates to the technical field of control of air traffic management areas, and discloses an FAB flow management method based on a distributed decision model. The method comprises the steps of: A, planning to construct a model: (1), defining interference or conflict between any two flight trajectories as flight interaction; and (2), establishing a distributed decision model, wherein on the basis of a meta-heuristic method, the distributed decision model separates a set of given interactive aircraft trajectories by adopting mixed algorithm that simulated annealing and local climbing search are combined; a distributed decision used for solving flight interaction derives from an innovative data structure, called as an FAB-flight interaction matrix; and it captures flight interaction information between and inside FABs. The FAB flow management method based on the distributed decision model can solve the problem that a negative effect can be caused on the air traffic security due to the facts that the current management tool is too single, an airline company and an air traffic management unit are lack of coordination and the environment in air field is worse and worse.

The invention discloses an automatic driving multi-vehicle intelligent cooperation regional traffic guidance method, which is applied to the field of intelligent Internet of Vehicles, and aims at the problems that a traditional path planning algorithm is short in sight and ignores communication resource constraints. The invention provides a multiple-inteligent-agent depth deterministic strategy gradient model with a self-evolution function, and the model can carry out centralized training and distributed execution on road network data, that is, each automatic driving vehicle can have different reward structures and make decisions according to local information of the automatic driving vehicle. Strategy congestion caused by strategy conflicts is avoided to a certain extent; and an area server establishes digital twinning for vehicles in the area to perform road condition deduction, and generates periodic feedback for the vehicles. According to the invention, through a digital twin iteration vehicle strategy, future traffic conditions under the action of multiple vehicles are accurately speculated and are fed back as input to the vehicles for distributed decision making. On the premise of considering personal travel safety and time constraint, the multi-vehicle travel efficiency in the system is remarkably improved.

The present invention describes a new distributed decision making scheme for adaptive signal detection. The innovation describes an adaptive system and method for allocating signal detection resources that are used to find out the status of channel use (occupied / unoccupied). The system includes selection of suitable spectrum sensing methods and decision combining techniques as well as the associated parameters to meet the requirements set for the system in the specific operational environment. The result is that the system has good performance, simple implementation and is applicable to versatile time-variant situations.