14 results about "Network cost" patented technology

The invention discloses a long-distance port expansion device based on a multi-port PHY chip, and the device comprises a near-end device which is integrated with a multi-channel serial interface supporting a multi-port protocol; the remote equipment comprises at least one PHY (Physical Layer) chip, and the PHY chip is provided with an uplink multi-channel protocol interface supporting a multi-port protocol and is provided with a plurality of downlink network ports; and the multi-channel serial interface of the near-end equipment is connected with the uplink multi-channel protocol interface of the PHY chip through a long-distance transmission medium. According to the invention, the port access and data forwarding functions of a traditional switch (including a switch realized by a switch chip or a processor) are directly replaced by the far-end multi-port PHY, and the method is suitable for various network communication scenes sensitive to network cost, time delay and architecture complexity.

The application provides a kind of evaluation method and system of neural network cost model based on category guidance, it is related to data processing technical field, the feature of the tensor program to be evaluated is extracted from the perspective of syntax tree, and the tensor program feature is obtained;Tensor program features are processed by dimension reduction and clustering, to obtain the probability that the tensor program feature belongs to different categories;The feature of the tensor program to be evaluated is extracted from the perspective of scheduling primitive, to obtain intermediate features;Based on the probability that the tensor program feature belongs to different categories and the intermediate features, the performance score of the tensor program to be evaluated is obtained.From the perspective of syntax tree, extracting the features of the tensor program and extracting the features from the scheduling primitive can effectively utilize the complex relationship between subprograms, reduce the time of the AI compiler automatic tuning process, so that the neural network model can be deployed on the ground, and only needs less tuning time under the same tuning performance condition, improves the efficiency.

Embodiments of the present application provide a method of obtaining a distribution key and related devices for obtaining a distribution key. The method is applied to cloud management platforms. This method includes: receiving a request from a tenant, where the request is used to obtain a set of target distribution keys; obtaining a set of target tables and a set of candidate distribution keys based on the request and a set of historical query information; obtaining a set of first distribution keys from the set of candidate distribution keys based on a first optimization rule; and obtaining the set of target distribution keys from the set of first distribution keys based on a network cost of each couple of first distribution keys. The proposed technique provides a suitable distribution key for tenant, improves the efficiency of obtaining a distribution key, and improves the efficiency of query.

A computing system generates directives of a program. Beam nodes are selected one level at a time from multiple nodes in the tree structure. Each node represents a subset of operations in the program. A first number of the beam nodes are selected at a given level of the tree structure. The selection of the first number of the beam nodes uses a cost model that is based on a neural network. A second number of the beam nodes are selected using a random search. The ratio of the first number to the second number is determined based on a search completion percentage at the given level. A path is identified that passes through respective beam nodes at multiple levels of the tree structure. The path represents a schedule for executing the program on a target machine. Then the directives corresponding to the schedule are generated.

The invention discloses a main network construction cost rapid auxiliary review method and system, and the method comprises the steps: firstly obtaining construction cost data information and construction cost budget information of a main network construction cost, and recognizing each construction cost demand type and construction cost data distribution information based on the construction cost data information; then, based on the cost budget information, identifying a cost list, and based on the cost data distribution information and the cost list, identifying cost evaluation index values and cost evaluation reasons; then, based on the cost evaluation index value and the cost evaluation reason, identifying a cost evaluation result, and based on the cost evaluation result, generating main network auxiliary evaluation information of the main network cost; according to the method, the cost evaluation result of each cost demand type is comprehensively analyzed, workers are assisted to comprehensively analyze each cost demand type, and each cost demand type is comprehensively analyzed through the evaluation index, so that the timeliness, the accuracy and the comprehensiveness of main network cost evaluation analysis are improved, and the efficiency of main network cost evaluation analysis is improved. And meanwhile, the review efficiency is further improved.

The invention relates to the technical field of fifth-generation mobile communication core networks, in particular to a method and a device for realizing fixed wireless access security enhancement in a 5G network. The method is executed by a 5G core network, and comprises the following steps: in a PPPoE session discovery stage of accessing an FWA terminal to an L2 transmission network, acquiring terminal equipment security information, generating security enhancement information based on a pre-configured security policy, carrying the information through a Relay-Session-Id tag of a PPPoE protocol standard, and sending the information to a PPPoE server, thereby realizing dual authentication. The scheme adapts to IP type and Ethernet type PDU session scenes, does not need to additionally deploy hardware, is compatible with multiple types of terminals, improves the access security, reduces the network cost, and is suitable for multiple types of access scenes such as families, enterprises, remote areas and the like.

A method (300) for controlling an energy storage device or load comprises generating a hybrid tariff based on a weighted combination of a tariff and network cost. An energy usage prediction and, where renewable or other generation sources are available, an energy generation prediction are generated (302,304) for time periods for each site in a plurality of sites. The method further comprises generating (306), for the site, a plan to selectively store energy in an energy storage device at the site, discharge energy from the energy storage device, or control when a load at the given site consumes energy based at least in part on optimising the cost of energy consumed according to the hybrid tariff based on the energy usage and generation prediction.

A system and method (300) for controlling an energy storage device or load are provided. The method comprises generating a hybrid tariff based on a weighted combination of a tariff and network cost. An energy usage prediction and, where renewable or other generation sources are available, an energy generation prediction are generated (302, 304) for time periods for each site in a plurality of sites. The method further comprises generating (306), for the site, a plan to selectively store energy in an energy storage device at the site, discharge energy from the energy storage device, or control when a load at the given site consumes energy based at least in part on optimising the cost of energy consumed according to the hybrid tariff based on the energy usage and generation prediction. [Figure 3]

The present disclosure relates to a traffic control method, device, equipment and program product. The traffic control method applied to a client gateway module comprises: determining a target service in response to a data request sent by a client service module; determining a target time window corresponding to the target service; wherein the target time window is determined based on a target traffic model corresponding to the target service, and the target traffic model is used to balance network traffic; and sending the data request to the server gateway module within the target time window to request target data of the target service from a server service module corresponding to the server gateway module. In this way, the data requests of multiple clients can be more evenly dispersed, the network traffic can be better flattened, and traffic peaks and server peak capacity can be avoided, thereby reducing the network cost of data resource requests and the resource consumption of the server.

The invention relates to the field of network resource allocation, in particular to an FSDM network limited uplink and downlink port dynamic survival optical path configuration method and system, and the method comprises the steps: constructing an FSDM optical network employing a shared laser source and a local oscillator, building an analytical model, and predicting the network blocking performance under the condition of different numbers of uplink and downlink ports of optical cross connection nodes, determining a port threshold; and on the basis of a port threshold value, whether an idle uplink and downlink port exists in a source node and a destination node or not is firstly judged through a constructed adaptive routing algorithm, and then working and protection path search is started, so that FSDM optical network dynamic survival optical path configuration based on shared backup path protection is realized. According to the FSDM optical network protection strategy, the blank of the FSDM optical network protection strategy is filled, the analytical model can reduce redundant configuration and optimize the network cost, the adaptive routing algorithm can improve the spectrum utilization efficiency, and the medium Spa SCh granularity configuration is adopted, so that the FSDM network has high cost benefit.

The invention discloses a pipe network optimization method and system for a gas-steam combined cycle cogeneration unit, and relates to the field of gas-steam combined cycle cogeneration units. Aiming at the problem that the comprehensive cost of a unit and a steam pipe network is difficult to optimize in the traditional step-by-step design, the method comprises the following steps: constructing a plurality of steam pipe network schemes with different pipe section diameters and determining the total annual investment cost; determining unit steam supply parameters according to the pipe network inlet steam parameters; establishing a bottom-layer steam circulation thermal model, and determining unit heat consumption based on steam supply parameters; and calculating the annual comprehensive cost by combining the annual total investment cost and the unit annual operation income, and finally screening out the optimal steam pipe network scheme with the lowest annual comprehensive cost. The system correspondingly comprises a pipe network cost module, a steam supply parameter module, a heat consumption module and a pipe network optimization module. According to the invention, collaborative optimization of the steam pipe network and the unit is realized, the comprehensive cost is effectively reduced, and the system economy is improved.

The application provides a random access method, system and related device. The method comprises: receiving a random access request sent by a mobile terminal in a first cell; allocating a user identifier according to the random access request; and sending a first message containing the user identifier and a signaling request to a corresponding second cell, the first message being used to assist the second cell to determine the user identifier and to establish a signaling bearer with the mobile terminal; wherein the first cell is a cell processing data plane functions, a first base station is a base station where the first cell is located, the second cell is a cell processing signaling plane functions, and a second base station is a base station where the second cell is located. The application uses random access resources of the first cell to perform a random access process and to establish a signaling bearer between the second cell and the mobile terminal, so as to reduce network cost and energy consumption.

The invention discloses a multi-data center multi-task cooperative scheduling method with optimal comprehensive power consumption, which comprises the following steps of: 1) acquiring a calculation task, and determining the type of the calculation task; 2) constructing a computing power network cost evaluation model; and 3) solving the computing power network cost evaluation model to obtain a computing power distribution scheme of each computing task. According to the method, the advantages of the genetic algorithm and rolling time domain optimization are fused, the optimization decision is realized in a dynamically changing computing power network environment, and the constantly changing computing task requirements are met.

This invention discloses a bandwidth prediction and scheduling method and system for edge network cost optimization, belonging to the field of network resource scheduling technology. The method includes: collecting historical bandwidth demand data of task nodes in the edge network, performing adaptive anomaly repair and multi-granularity statistical feature extraction to construct a feature tensor; inputting the feature tensor into a bandwidth demand prediction model to output predicted bandwidth demands for multiple future steps; training the prediction model using a peak-valley asymmetric weighted loss function; constructing a marginal cost-sensitive online scheduling optimization model based on the predicted values, with the objective of minimizing the total transmission cost within the prediction time domain; and solving the scheduling optimization model using a greedy heuristic algorithm based on marginal cost increment ranking to output the optimal bandwidth allocation scheme that satisfies service quality constraints and capacity constraints. This invention can accurately predict and proactively schedule bandwidth before peak demand periods arrive, effectively reducing transmission costs in edge networks.