23 results about "Effective capacity" patented technology

The present application relates to a wireless communication system. Provided are a service signal sending method and a related device. The sending method comprises: an access network device acquiring an effective-capacity requirement corresponding to a user equipment, wherein an effective capacity is used for indicating a data transmission rate of a channel that meets data transmission requirements corresponding to a service, and the data transmission requirements comprise signal delay requirements; on the basis of the effective-capacity requirement, the access network device determining precoding corresponding to a downlink channel, wherein the precoding is used for adjusting the channel capacity of the downlink channel, such that the channel capacity of the downlink channel meets the effective-capacity requirement; and the access network device preprocessing, on the basis of the precoding, a service signal corresponding to the service, and sending the preprocessed service signal to the user equipment by means of the downlink channel. In the embodiments of the present application, the access network device can ensure that the channel capacity corresponding to each user equipment can meet the requirements for real-time performance and integrity of service data of the user equipment. In this way, the total effective capacity of a whole system can be improved while ensuring the total throughput of the system.

The invention discloses a capacity market clearing and pricing method and device and a medium, which are applied to an electric power system, and the method comprises the steps: obtaining the new energy real-time data of a new energy station in the electric power system, inputting the new energy real-time data into a capacity contribution evaluation network model, and obtaining an equivalent reliable capacity; calculating a traditional unit capacity, an energy storage capacity and a demand side response capacity respectively; and respectively inputting the equivalent reliable capacity, the traditional unit capacity, the energy storage capacity and the demand side response capacity into a clearing model to obtain a bid-winning subject and a clearing price of the corresponding capacity. According to the method, the effective capacity of various resources can be accurately quantified, and a price signal capable of truly reflecting the capacity scarcity degree of the system is formed on the basis, so that the optimal power supply structure investment is effectively guided, and long-term reliable operation of the high-proportion new energy power system is guaranteed.

The present application relates to power system power source planning method technical field, especially a kind of multi-region power system power source planning method considering capacity sharing, including the construction load growth driven time sequence uncertainty probability model;Establish the effective capacity refined evaluation model under the random failure of multi-source unit;System capacity distribution analytical transformation based on semi-invariant and series expansion.The present application breaks the limitation of traditional single region independent planning by establishing the capacity sharing mechanism between receiving end and sending end regional power grid.Can dynamically adjust inter-regional power resource allocation according to the degree of capacity scarcity, significantly reduce cost under the premise of guaranteeing reliability.

The invention discloses a storage pool creation method and device, equipment, a medium and a product, which are applied to the technical field of storage, and comprise the following steps: obtaining the number of fault domain units and the number of copies; when the number of the fault domain units is greater than the number of the copies, judging whether each fault domain unit meets a first preset capacity balance condition or not based on the minimum effective capacity and the expected effective capacity corresponding to each fault domain unit; if the first preset capacity balance condition is not met, grouping recursive calculation is carried out on each fault domain unit to obtain a target effective capacity, and whether a second preset capacity balance condition is met is judged based on the target effective capacity and the expected effective capacity; and under the condition that a second preset capacity balance condition is not met, creating a main pool based on the target effective capacity and creating an auxiliary pool based on the residual capacity. Therefore, the utilization rate of storage resources can be improved.

The application discloses a large language model key value management system and method based on a memory pool, and belongs to the technical field of computers.The system comprises: a first layer storage module, which is GPU memory and stores key value cache data of an inference request being processed; a second layer storage module, which comprises local main memories of various computing nodes and stores key value cache data generated after inference of each computing node is completed in the form of prefix data blocks; and a third layer storage module, which is a memory pool and is used for storing prefix data blocks repeatedly accessed by a large number of different requests; and a three-layer storage scheduling module, which is used for transmitting the prefix data blocks of the second layer storage module to the third layer storage module for exclusive storage according to an access frequency, and bidirectionally expelling and writing back when the capacity of the local main memories of the computing nodes and the third layer storage module reaches an upper limit.The application can eliminate a network bottleneck, reduce inference delay, improve effective capacity of storage space, and improve a cache hit rate.

The application discloses an optimization method for improving the effective capacity of a management system database, which adopts double judgment logic of communication characteristic data and service characteristic data to simultaneously provide communication state judgment and service state judgment, and instantly eliminates communication faults and service data that do not meet the requirements, so as to greatly reduce invalid data stored from a source system to the management system, thereby achieving the purposes of prolonging the available time of the same storage hardware or reducing the storage hardware storage under the same expected time limit, reducing the hardware cost on one hand and reducing the power consumption cost on the other hand, and improving the effective capacity of the management system database.

This application provides a capacity testing system, method, integrated charge / discharge machine, dielectric, program product, and terminal. The capacity testing in this application is performed synchronously with the charge / discharge process, eliminating the need for separate testing. Furthermore, it employs an embedded modular design, enabling online capacity testing without external equipment. The capacity testing method uses the traditional two-point method capacity calculation result as the initial capacity observation value, and then dynamically corrects the initial capacity observation value through aging state transition and stress mapping, resulting in significantly higher capacity testing accuracy than the traditional two-point method. The capacity testing system of this application is applicable to different cell types, overall pack designs, and thermal management strategies. This application obtains highly accurate battery effective capacity and estimated state of equilibrium (SOH), which can be used for subsequent battery operating status assessment, life analysis, and user display. It can also provide a basis for equipment operation strategy optimization or maintenance decisions, and is continuously iterated and updated during subsequent operation.

The application discloses a kind of power supply full life cycle flat equalization capacity cost calculation method, system, equipment and medium, it is related to power system analysis and planning technical field, including obtaining the multiple cost parameters of each year of target power supply in entire life cycle, and according to the operation state data of target power supply in life cycle, calculate capacity reliability representation parameter, each year multiple cost parameters are uniformly converted to reference time point using the preset time value discount factor, and summation is carried out, obtain the present value of total cost in full life cycle, based on the present value of total cost in full life cycle and cumulative effective capacity, the amortization cost of unit effective capacity in life cycle is calculated, i.e.flat equalization capacity cost.The application is quantified to power supply full life cycle flat equalization capacity cost by combining capital recovery, dynamic environmental cost, capacity reliability reduction and comprehensive operating cost, provides fair evaluation basis for the capacity value of power supply of different technical route.

The application relates to the technical field of wireless communication, and particularly discloses a GFDM effective capacity optimization method and system for a jungle channel, the method comprising the following steps: obtaining a raw binary data stream at a transmitting end, pre-processing and demodulating a signal received at a receiving end to obtain a demodulated binary data stream, and calculating a bit error rate based on the raw binary data stream and the demodulated binary data stream; calculating effective capacity based on the bit error rate, taking the effective capacity as a utility function, and step-by-step optimizing GFDM waveform design parameters by applying a particle swarm algorithm, wherein the GFDM waveform design parameters comprise a roll-off coefficient and a subcarrier number; and the method can optimize the GFDM effective capacity under the jungle channel, and obtain the best effective capacity and corresponding subcarrier number and pulse shaping filter coefficient.

The application discloses a storage pool creation method and device, equipment, medium and product, applied to the storage technical field, including: obtaining the number of fault domain units and the number of copies; when the number of fault domain units is greater than the number of copies, whether each fault domain unit meets the first preset capacity balance condition is judged based on the minimum effective capacity corresponding to each fault domain unit and the expected effective capacity; if the first preset capacity balance condition is not met, the target effective capacity is obtained by grouping and recursively calculating each fault domain unit, and whether the second preset capacity balance condition is met is judged based on the target effective capacity and the expected effective capacity; in the case of not meeting the second preset capacity balance condition, the main pool is created based on the target effective capacity, and the auxiliary pool is created based on the remaining capacity. In this way, the utilization rate of storage resources can be improved.

The embodiment discloses a micro-service capacity expansion method and device, electronic equipment, a storage medium and a computer program product, and the micro-service capacity expansion method comprises the steps: judging whether an application layer of a micro-service architecture meets a first capacity expansion condition or not, and judging whether a persistence layer of the micro-service architecture meets a second capacity expansion condition or not; the application layer comprises micro-services; the persistence layer is used for storing data used during operation of each micro-service; when the application layer meets a first capacity expansion condition, carrying out capacity expansion on the application layer; and when the persistence layer meets a second capacity expansion condition, carrying out capacity expansion on the persistence layer. Through the micro-service capacity expansion method provided by the embodiment of the invention, the hierarchy needing capacity expansion in the micro-service architecture can be accurately obtained, effective capacity expansion of the micro-service architecture can be realized, and the overall operation capability of the micro-service architecture is improved.

The invention discloses an effective energy efficiency optimization method for an MU-MIMO-NOMA system, and the method comprises the steps: dividing users into a plurality of clusters according to the difference of the service time delay service quality requirements of all users of a multi-user MIMO system; performing block diagonalization precoding on different clustered transmission signals to eliminate inter-cluster interference; carrying out power domain power distribution in each cluster by adopting a non-orthogonal multiple access technology to obtain distribution power; calculating the user transmission rate based on the distribution power, and obtaining the effective capacity and the effective energy efficiency of the system; constructing an optimization problem with effective energy efficiency maximization as a target, wherein the optimization problem takes system transmitting power and NOMA power distribution factors as optimization variables; and solving the optimization problem by using an improved EAO algorithm to obtain optimal system transmitting power and NOMA power distribution factors, thereby realizing effective energy efficiency optimization.

A number of available units that represent a set of erase blocks of a storage device that can be programmed in modes having differing effective capacities are provided by a storage device controller through an interface. Requests to form unit sets including one or more of the available units and configured to be programmed in one or more modes are received, resulting virtually addressable capacity corresponding to effective capacity for the unit sets when programmed in the one or more modes. Data into one or more erase blocks of the one or more of the available units of the unit sets using the one or more modes.

The invention relates to the field of AP management, in particular to a self-adaptive AP capacity planning management method and device, equipment and a medium. Respectively calculating an aggregation bandwidth demand of each terminal type according to the number and the concurrency rate of each terminal type in the target wireless network scene and the bandwidth demand of a single terminal; calculating the effective capacity of the single AP for each terminal type according to the theoretical support capacity of the single AP for different terminals and the physical layer transmission efficiency; obtaining the total number of first APs needing to be deployed in the daytime according to the aggregation bandwidth requirement of each terminal type and the effective capacity of the single AP for each terminal type; obtaining the total number of second APs needing to be deployed at night according to the online rate of each terminal type at night and the number of each terminal type; and according to the total number of the first APs, the total number of the second APs and the plane position coordinates of all the APs in the target wireless network scene, determining the APs needing to be closed at night. And the overall utilization rate of network resources is improved.

The invention discloses a two-dimensional code generation method and device and a two-dimensional code recognition method and device based on capacity expansion, and the method comprises the steps: obtaining target content which comprises text information, a URL link and structured information; partitioning the target content to obtain a plurality of content sub-blocks, and encoding each content sub-block to obtain an encoding value of each content sub-block; a symbol identifier corresponding to each content sub-block is determined according to the coded value of each content sub-block, and the symbol identifiers are different in shape and / or color; and generating a target two-dimensional code based on the symbol identifier corresponding to each content sub-block and a preset error correction code. The method aims at solving the technical problems that the effective capacity of a two-dimensional code is low, and a large amount of information and data cannot be stored.

The embodiment of the present application relates to the application field of storage devices, and discloses a data write protection method and a storage device, the method comprising the following steps: when the storage device is in a write state, obtaining the compression ratio and the residual effective capacity of each valid super block of the storage device; calculating a first approximate compression ratio according to the compression ratio of each valid super block; and determining the write protection strategy of the storage device according to the comparison result of the first approximate compression ratio and a preset compression ratio, and the comparison result of the residual effective capacity and a capacity threshold. The write protection strategy of the storage device is determined according to the comparison result of the first approximate compression ratio and the preset compression ratio, and the comparison result of the residual effective capacity and the capacity threshold, so that the problem that the storage device is down due to the continuous data writing of the host can be solved, and the stability of the storage device is improved.

The invention provides an OSD adding method and device, electronic equipment and a storage medium, relates to the technical field of data storage, and can be applied to various scenes such as cloud technology, intelligent traffic and auxiliary driving. The method comprises: receiving an adding request; in response to the addition request, determining a reference OSD of the target OSD based on the type of the target OSD, and determining an effective capacity of the reference OSD based on a maximum capacity of the reference OSD or an expected capacity of the reference OSD; and determining a weight of the target OSD based on the effective capacity of the reference OSD, and adding the target OSD to the distributed storage system based on the weight of the target OSD. In the embodiment, the weight of the target OSD is determined by referring to the effective capacity of the OSD, so that the stability of the distributed storage system can be ensured, and the maintenance difficulty of the distributed storage system can be reduced.

The invention provides an end-to-end service level adaptive cloud data center resource collaborative optimization method. The method is characterized by comprising the following steps of: predicting a workload based on historical task data; under the constraint of global SLA violation budget, dynamic violation budget allocation and resource quota calculation are carried out on each application type based on dynamic planning; calculating the effective capacity of the virtual machine based on a historical utilization rate and a security margin factor, and supplying a security excess allocation virtual machine; a virtual machine-to-physical machine placement step based on an anti-affinity principle; and a double-layer load balancing task scheduling step based on deep reinforcement learning. According to the method, workload prediction, SLA violation budget allocation, resource supply and placement and online task scheduling are unified in one framework, and the problem of global sub-optimization caused by isolated optimization of a resource configuration layer and a scheduling layer is avoided.

The invention provides an instruction compression method and device, a processor core and computer equipment, and relates to the technical field of data compression. The instruction compression method comprises the steps of obtaining a plurality of micro-operations corresponding to at least one instruction in a current period; according to the execution unit type corresponding to each of the plurality of microoperations and a plurality of preset compression types, determining a plurality of compression modes for the plurality of microoperations; according to the compression lengths of the various compression modes, selecting a target compression mode from the various compression modes; and compressing the plurality of microoperations into the reordering buffer area by adopting a target compression mode. According to the method, multiple compression modes with the high coverage rate are determined based on execution unit types corresponding to the microoperations and multiple preset compression types, then an optimal target compression mode is determined from the multiple compression modes based on the compression length, and the multiple microoperations are compressed into a reordering buffer area in the target compression mode. In this way, more microoperations can be accommodated for the same reordering buffer area resources, the effective capacity of the reordering buffer area is improved, and then the renaming speed is increased.

This application provides a packet discarding method and a communication device relating to the field of communications. The method includes the steps of: a second communication device transmitting first instruction information to a first communication device, wherein the first instruction information indicates adjusting the duration of a discard timer corresponding to first data at the PDCP layer to a second duration, and the first data being a first data packet or a first data packet set of target importance; and the first communication device adjusting the duration of the discard timer from a first duration to a second duration based on the first instruction information. According to the method, the first communication device can quickly and flexibly adjust the duration of the discard timer for first data to adapt to different communications environments, increase the effective capacity of the system, and improve the user experience. For example, in scenarios where network congestion occurs, the duration of the discard timer for less important data can be shortened. In this way, less important data can be preferentially discarded, and it can be ensured that more important data can be transmitted normally.

The invention relates to the technical field of wireless communication, and particularly discloses a jungle channel-oriented GFDM effective capacity optimization method and system, and the method comprises the steps: obtaining an original binary data stream of a transmitting end, carrying out the preprocessing and demodulation of a signal received by a receiving end, obtaining a demodulated binary data stream, and carrying out the demodulation of the demodulated binary data stream. Calculating an error rate based on the original binary data stream and the demodulated binary data stream; the effective capacity is calculated based on the bit error rate, the effective capacity serves as a utility function, GFDM waveform design parameters are optimized step by step by applying a particle swarm algorithm, and the GFDM waveform design parameters comprise a roll-off coefficient and the number of subcarriers; the optimization of the GFDM effective capacity under the jungle channel can be realized, and the optimal effective capacity and the corresponding subcarrier number and pulse shaping filter coefficient can be obtained.

The application discloses a data transmission optimization method and device of a communication system, a terminal and a medium, and comprises the following steps: modeling an IRS-aided channel according to a cascade channel model; obtaining the AoI violation probability of each device according to the definition of AoI; constructing an effective capacity maximization problem of information timeliness guarantee; converting a long-term random optimization problem into a per-slot deterministic optimization problem according to a Lyapunov optimization algorithm; converting the original effective capacity optimization problem into a Markov decision process; and jointly optimizing the phase shift of the IRS and the transmission power of the device according to an SAC algorithm to obtain an optimized data transmission strategy. The application solves the effective capacity maximization problem of information timeliness guarantee in an IRS-aided NOMA communication system with imperfect CSI.

The invention discloses a new energy credible capacity determination method based on source storage collaboration and a Newton iteration algorithm under the condition of considering energy storage collaboration, and the method comprises the steps: determining a plurality of parameters used for representing the power generation characteristics of new energy, building a Copula model considering the joint distribution based on the historical data sample edge distribution of the parameters, and determining the credible capacity of the new energy based on the Copula model. Generating a new energy output scene; for an initial system which is not added to the new energy unit to be evaluated in each scene, evaluating the influence of the scene on the system reliability by combining a Monte Carlo simulation method, and determining the load loss probability of the initial system; and adding a new energy unit to be evaluated into the initial system, calculating the load loss probability of the new system by using a Monte Carlo sampling method, and solving the operation credible capacity of the new energy unit to be evaluated by using an effective capacity quantification algorithm based on Newton iteration. The method can reliably reflect technical contributions of various resources to capacity support, meanwhile, it is guaranteed that the calculation process is simple and transparent, and good balance is achieved between evaluation precision and practical application.