2217 results about "Resource distribution" patented technology

Apparatus and methods implement aggregation frames and allocation frames. The aggregation frames include a plurality of MSDUs or fragments thereof aggregated or otherwise combined together. An aggregation frame makes more efficient use of the wireless communication resources. The allocation frame defines a plurality of time intervals. The allocation frame specifies a pair of stations that are permitted to communicate with each other during each time interval as well as the antenna configuration to be used for the communication. This permits stations to know ahead of time when they are to communicate, with which other stations and the antenna configuration that should be used. A buffered traffic field can also be added to the frames to specify how much data remains to be transmitted following the current frame. This enables network traffic to be scheduled more effectively.

A system for managing allocation of resources based on service level agreements between application owners and cloud operators. Under some service level agreements, the cloud operator may have responsibility for managing allocation of resources to the software application and may manage the allocation such that the software application executes within an agreed performance level. Operating a cloud computing platform according to such a service level agreement may alleviate for the application owners the complexities of managing allocation of resources and may provide greater flexibility to cloud operators in managing their cloud computing platforms.

A method and system (102) provide adaptive modulation / coding with distribution of excess resources based on one or more system criteria. The system (102) may be any system with more than one modulation rate or more than one coding rate and may be a wireless communication system using CDMA, TDMA, OFDM or any other signal formats. Generally, the method determines excess resources of the system based on desired characteristics of links supported by the system. The excess resources may be any number of system resources, such as transmit power. These excess resources are then distributed to the links based on various system criteria, such as to increase system coverage, to increase system capacity, to modify a data rate profile of the system or to reduce interference in the system. Methods for providing such distribution of the excess resources are also provided for equal data rate systems.

The present invention relates to a system and methodology facilitating flexible resource distribution in an industrial control environment. A query component is provided to determine one or more system resources from a networked industrial controller system, wherein the resources can include listings of applications, configurations, variable settings, and performance capabilities associated with a controller. Upon receiving available resource listings from various control devices, a distribution component can update the devices based in part on the resource listings and according to various criteria. A configuration component can be utilized in the controller system to provide network updates of controller parameters and to facilitate automated protocol selections when interacting with out-of-network devices. An analysis component can interact with the query, distribution, and configuration components to support higher-level decision-making in the resource distribution and allocation process.

The invention discloses a controller for determining a network state based on an SDN (Software Defined Networking) and a determination method thereof. The controller comprises a state updating module, a calculation module, an execution module, a flow management module and an evaluation module, wherein the state updating module is used for updating through a state and a path calculated by the calculation module; the calculation module is used for calculating a current network resource state N; the execution module is used for setting rules according to the path calculated by the calculation module and writing the path into a flow meter; the flow management module is used for carrying out congestion avoidance, flow supervision and shaping; and the evaluation module is used for carrying out synthetic judgment according to the current network resource state N calculated by the calculation module and QoS (Quality of Service) requirements of an application when receiving the application transmitted by a switch. According to the controller, the network state can be accurately controlled, a forwarding plane is precisely controlled, a 'Q+X' resource distribution mode is proposed, and the network resource is scheduled, so that the flexibility, the high efficiency, the intelligence and the optimization of a network can be realized.

A wireless communication system can implement beamforming across multiple omni-directional antennas to create beams at different spatial directions. The communication system can arrange the beams in sets, with each set arranged to provide substantially complete coverage over a predetermined coverage area. The communication system can arrange the multiple SDMA beam sets to support substantially complementary coverage areas, such that a main beam from a first set provides coverage to a weak coverage area of the second beam set. The wireless communication system assigns or otherwise allocates substantially orthogonal resources to each of the beam sets. The wireless communication system allocates resources to a communication link using a combination of beam sets and substantially orthogonal resources in order to provide improved coverage without a corresponding increase in interference.

A system for managing allocation of resources based on service level agreements between application owners and cloud operators. Under some service level agreements, the cloud operator may have responsibility for managing allocation of resources to the software application and may manage the allocation such that the software application executes within an agreed performance level. Operating a cloud computing platform according to such a service level agreement may alleviate for the application owners the complexities of managing allocation of resources and may provide greater flexibility to cloud operators in managing their cloud computing platforms.

The present invention leverages analysis methods, such as expected value of information techniques, rate-based techniques, and random selection technique, to provide a fusion of low-level streams of input data (e.g., raw data) from multiple sources to facilitate in inferring human-centric notions of context while reducing computational resource burdens. In one instance of the present invention, the method utilizes real-time computations of expected value of information in a greedy, one-step look ahead approach to compute a next best set of observations to make at each step, producing “EVI based-perception.” By utilizing dynamically determined input data, the present invention provides utility-directed information gathering to enable a significant reduction in system resources. Thus, of the possible input combinations, the EVI-based system can automatically determine which sources are required for real-time computation relating to a particular context.

Embodiments of the invention provide distribution method for user equipment coverage enhancement resource, a base station and user equipment. The method comprises that the base station detects whether communication requirements of user equipment (UE) corresponding to first coverage enhancement level exists or not; and the base station adjusts the coverage enhancement resource distributing for the first coverage enhancement level according to detection results. According to the method provided by the embodiments, the base station can adjusts coverage enhancement resource distribution timely and flexibly according to the coverage enhancement requirements of UE corresponding to the first coverage enhancement level, thereby reducing wastes of the coverage enhancement resource.

A resource download process is provided which includes accepting and / or determining evidence about user based factors, accepting and / or determining resource based factors, and maximizing the expectcd value of downloading resources. A resource distribution process is provided which includes accepting and / or determining user based factors, accepting and / or determining resource based factors, accepting and / or determining intermediate storage facility based factors, and minimizing the total expected latencies between requesting and receiving resources. A process for distributing resources is provided which includes determining a change in value and a change in cost of storing resources on a first storage facility versus storing resources on a second storage facility, determining a value density based on the change in value and the change in cost, and maximizing a total value density given a total size of resources being less than the finite available capacity of the first storage facility.

Resources to a device are granted access to an application based on privileges associated with the application. A permission list may be created by a server. The permission list may be created using information from authorities, entities, or parties and information about the device resources. The permission list indicates what device resources the application may access. During application execution when the application requests a resource, a control program executing on the device may be used to check the permission list associated with the application to determine if the application may access the resource. The control program can then grant or deny access based on the privileges defined in the permission list. Digital signatures may be used to detect modifications to the application and / or permission list. In addition, multiple permission lists may be associated with the same application.

The invention relates to the dynamic resource scheduling technique in the cloud computing field, and provides a cloud computing dynamic resource scheduling method based on the feedback and a prediction mechanism. The method aims to overcome the defects of the cloud computing resource distribution and scheduling technique in the prior art, and can achieve balance use of various computer resources in a cloud computing environment, obtain satisfactory load balance under small pay expenses and improve comprehensive efficiency of system scheduling. According to the scheme, various performance indexes of virtual machines are monitored in real time in operation processes of the virtual machines, operation circumstances of all the current virtual machines within a next short period of time are predicted according to the monitored various current performance indexes of the virtual machines and a virtual machine state prediction model based on state feedback when a task request comes, and the most adaptive virtual machine is selected by combining a prediction result and a required task type and the required task is distributed. In addition, the invention further discloses a corresponding cloud computing dynamic resource scheduling system applicable to dynamic resource scheduling.

A resource distribution method capable of lending surplus resources among a plurality of services and reducing the maintenance cost of the surplus resources is provided. Computer resources in the standby system have a dead standby state in which at least an application is not installed. A plurality of services or a plurality of users share the computer resources in the standby system. As a result, improvement of the utilization factor of idle computer resources and server integration are implemented, and the cost required to maintain the computer resources is reduced. Furthermore, load prediction is conducted as regards individual services by using past operation history. Idle computer resources secured from services having surplus and maintained are thrown in according to a result of the prediction.

The present invention relates to a system and methodology facilitating flexible resource distribution in an industrial control environment. A query component is provided to determine one or more system resources from a networked industrial controller system, wherein the resources can include listings of applications, configurations, variable settings, and performance capabilities associated with a controller. Upon receiving available resource listings from various control devices, a distribution component can update the devices based in part on the resource listings and according to various criteria. A configuration component can be utilized in the controller system to provide network updates of controller parameters and to facilitate automated protocol selections when interacting with out-of-network devices. An analysis component can interact with the query, distribution, and configuration components to support higher-level decision-making in the resource distribution and allocation process.

The invention relates to a multi-agent reinforcement learning scheduling method, a multi-agent reinforcement learning scheduling system and electronic equipment. The method comprises the following steps: step a, collecting server parameters of a network data center and virtual machine load information running on each server; b, establishing a virtual simulation environment by using the parametersof the server and the load information of the virtual machine, and establishing a deep reinforcement learning model of multiple agents; c, performing offline training and learning by utilizing the deep reinforcement learning model of the multiple agents and a simulation environment, and training an agent model for each server; and d, deploying the agent model to a real service node, and schedulingaccording to the load condition of each service node. The service running on the server is virtualized through the virtualization technology, load balancing is carried out in a virtual machine scheduling mode, resource distribution is more macroscopic, and a strategy that multiple agents generate cooperation in a complex dynamic environment can be achieved.

A reference signal of a user equipment to which a resource (LB#1) is allocated for a L1 / L2 control signal, is allocated a resource (SB#1) that is closer on the time axis to the resource (LB#1), which the L1 / L2 control signal is allocated, within the same frequency band as the L1 / L2 control signal. A reference signal for CQI estimation, independent of a data signal and a L1 / L2 control signal, is allocated a resource with which at least one of a reference signal for demodulation of a data signal and a reference signal for demodulation of a L1 / L2 control signal is not transmitted at the same timing within the transmission band. The types of bandwidths of the reference signals multiplexed in a same short block within a same band are reduced, whereby restrictions as to the number of reference signal sequences that can be secured are diminished.

The invention discloses a Device to Device (D2D) resource distribution method of an Internet of Vehicles terminal and a related device which are used to achieve D2D resource distribution of a terminal in an Internet of Vehicles system and improve use efficiency of a wireless resource, resource distribution efficiency and resource updating efficiency. The method comprises the following steps: a D2D resource control entity receives a first signal sent by a terminal through a base station, wherein the first signal at least carries position information of the terminal; and, according to the position information of the terminal and locally saved D2D resource occupied information, the D2D resource control entity allocates an idle D2D resource for the terminal and sends indication information of the allocated D2D resource to the terminal through the base station, wherein the D2D resource occupied information comprises the position information of the terminal of the allocated D2D resource and occupied D2D resource information thereof.

The invention discloses a distribution method for frequency source of wireless system which includes: every section reports the information that indicates the load state or the needed frequency source periodically; it decides the needed frequency source according to the reported information from sections, and judges the needed frequency source is bigger than the fixed frequency source which belongs to the section, if yes, the spare frequency source of adjacent sections is distributed for the section. The invention also provides the corresponding frequency source distribution device and wireless communication system. The invention can adjust the main frequency source that occupied by the boundary users according to the different load requirement of sections, it can avoid the disturbance between the section and improve the throughput of section boundary.

The invention discloses a cloud computing resource scheduling method based on scheduling object space. According to the method, the concept of scheduling object space is introduced for setting a flexible standard framework, so that a user can explain the requirement on service resource scheduling, namely the user can select required scheduling attribute for optimization, wherein a multi object resource distribution scheduling mechanism can make adaptive resource scheduling decision under the driving of the expandable user scheduling object space. The method can dynamically deploy cloud computing resource according to the requirement of the user on resource scheduling, and realizes the adaptive optimal distribution of the cloud computing resource driven by the user requirement. Moreover, the scheduling strategy can avoid over turning-on of a cloud computing server as much as possible, thereby improving the utility ratio of resources and reducing the cost of a cloud service provider.

The present invention provides a method and device for avoiding D2D (Device-to-Device) communication interference, relates to the technical field of wireless communication, and solves the problem of interference on cellular transmission by D2D transmission. The method includes: obtaining, by user equipment, a D2D resource distribution approach and / or D2D power control information; and using, by the user equipment, the D2D resource distribution approach and / or D2D power control information for D2D transmission. The technical solution provided by the present invention is adapted to the network of the D2D technology, and achieves successful D2D transmission and uplink cellular transmission.

The embodiment of the invention discloses a method, equipment and a system for sharing a frequency spectrum resource, which relate to the field of wireless communication and are used for realizing the sharing of a dynamic frequency spectrum resource among different mobile honeycomb networks on the basis of ensuring the network coverage and the service continuity. The method comprises the following steps: dividing the frequency spectrum resource into a basic frequency band and a dynamic frequency band, wherein the basic frequency band is used for ensuring the network coverage and the service continuity of at least two networks of the sharing frequency spectrum resource; fixedly distributing the basic frequency band in the frequency spectrum resource to at least two networks in a static mode, and distributing the dynamic frequency band in the frequency spectrum resource to at least two networks in a dynamic mode; and transmitting the frequency spectrum resource distribution information of the basic frequency band and the frequency spectrum resource distribution information of the dynamic frequency band to a base station so as to be used for the frequency spectrum resource allocation of the base station. The invention is suitable for mobile honeycomb networks, such as GSM, UMTS, LTE, CDMA2000, WiMAX and the like.

The invention provides an ant colony optimization computing resource distribution method based on a cloud computing environment. The computing resource distribution method is based on ant colony optimization and characteristics of the cloud computing environment. The cloud computing resource distribution method comprises the steps of predicting computing quality of potential available nodes, analyzing influence of factors such as network bandwidth occupation, quality of a track, responding time, task cost and reliability on resource distribution according to characteristics of a cloud computing service mode, and then obtaining a set of optimized computing resources by means of the ant colony algorithm. According to the algorithm, shorter responding time and better running quality can be acquired compared with other distribution algorithms which aim at the network on the premise that cloud computing environment requirements are met, and therefore the ant colony optimization computing resource distribution method based on the cloud computing environment is more suitable for the cloud environment.

A system and method for input thresholding packets in a network switch. A network switch may include multiple input ports, multiple output ports, and a shared random access memory coupled to the input ports and output ports by data transport logic. Packets entering the network switch may be assigned to one of a plurality of threshold groups and to one of a plurality of flows within the threshold group. In one embodiment, each threshold group may be divided into a plurality of levels of operation. As resources are allocated or freed by the threshold group, the threshold group may dynamically move up or down in the levels of operation. Within each level, one or more different values may be used as level boundaries and resource limits for flows within the threshold group. In one embodiment, programmable registers may be used to store these values.

The invention provides a resource distribution method and system. The method comprises the steps that the initial weight coefficients of attribute data of M queued tasks are generated according to resource deployment data at the starting moment of each resource distribution period; the M tasks are clustered according to the attribute data, and the M tasks are divided into a plurality of sets; initial weight coefficient vectors formed by the initial weight coefficients of the attribute data of each set are respectively adjusted through the entropy evaluation method, and the weight coefficient vector of each set is obtained; the priority scores of the tasks are respectively calculated according to the weight coefficient vectors of the sets which the tasks belong to and the attribute data of the tasks, and resource distribution is carried out on the tasks according to the priority scores from large to small. The resource utilization rate can be improved.

Disclosed is a method and apparatus for providing range based queries over distributed network nodes. Each of a plurality of distributed network nodes stores at least a portion of a logical index tree. The nodes of the logical index tree are mapped to the network nodes based on a hash function. Load balancing is addressed by replicating the logical index tree nodes in the distributed physical nodes in the network. In one embodiment the logical index tree comprises a plurality of logical nodes for indexing available resources in a grid computing system. The distributed network nodes are broker nodes for assigning grid computing resources to requesting users. Each of the distributed broker nodes stores at least a portion of the logical index tree.

An embodiment of the invention discloses an upward resource scheduling method of a TDD system, a system and a device, realizing dynamic scheduling on the upward resource on the basis of ensuring optimal transmission performance. The upward resource scheduling method comprises: a base station distributes upward resources for transmitting upward data on the user equipment, and transmits upward resource distribution information including upward sub-frame indexes in the sending time span corresponding to the upward sub-frame occupied by the upward resource, the sending time span corresponding to the upward sub-frame is arranged in advanced; the user equipment receives the distribution information, determines the upward sub-frame according to the upward sub-frame indexes and the upward sub-frame scheduling strategy, and transmits the upward data on the upward resource indicated by the distribution information in the upward sub-frame. An upward resource scheduling system comprises: user equipment and a base station. The embodiment of the invention also discloses a base station and user equipment.

The present invention discloses a group system comprising a load balanced server and at least two sub nodes, wherein the at least two sub nodes are used for respectively collecting respective various source information, and sending the source information to the load balanced server; the load balanced server is used for receiving tusk requirements and the various source information; sub nodes for processing the tusk requirements are ensured according to load balanced tactics and the various source information; and the tusk requirements are sent to the ensured sub nodes. Correspondingly, the present invention also discloses a method for realizing load balance and the load balanced server. The sub nodes for processing the tusk requirements are ensured according to the load balanced tactics and the various source information respectively sent by the at least two sub nodes in the group system, the most reasonable source distribution is realized in the group system, and flexible configuration can be realized according needs to enable the processing efficiency of the group system to improve mostly.

A system and method for automatically allocating resources is provided. The system includes one or more components for automatically allocating one or more resources, based at least in part on data associated with the one or more resources, the data including at least one of, type data, instance data, characteristic data, and dynamically modifiable metadata. An alternative aspect of the system provides one or more components for automatically allocating one or more resources distributed on a plurality of resource allocation servers. The one or more components for automatically allocating the one or more resources can improve utilization of the capacity of the one or more resources. In an alternative embodiment the system includes an Application Programming Interface (API) operable to configure and / or control the one or more components for automatically allocating one or more resources.

The invention discloses a signal path measurement resources distribution method of a wireless broadband access. The method comprises that a terminal receives a signal path measurement request transmitted by a base station, the signal path measurement request comprises a signal path to be measured and the measuring time, and the terminal conducts the measurement to the signal path to be measured in the measuring time. The invention also discloses a signal path measurement resources distribution system, a base station and a terminal of a wireless broadband access system. By using the method of the invention, the terminal can obtain accessible measurement resources without affecting the normal service communication between the terminal and the service base station.