34 results about "Resource pricing" patented technology

This invention is a means both to allocate all types of resources for commercial, governmental, or non-profit organizations and to price such resources. A linear programming process makes fulfillment allocations used to produce product units. A Resource-conduit process governs the linear programming process, uses two-sided shadow prices, and makes aperture allocations to allow Potential-demand to become Realized-demand. A strict opportunity cost perspective is employed, and the cost of buyable resources is deemed to be the opportunity cost of tying up cash. Resource available quantities, product resource requirements, and Potential-demand as a statistical distribution are specified in a database. The invention reads the database, performs optimization, and then writes allocation directives to the database. Also determined and written to the database are resource marginal (incremental) values and product marginal costs. The database can be viewed and edited through the invention's Graphical User Interface. Monte Carlo simulation, along with generation of supply and demand schedules, is included to facilitate analysis, explore "what if," and interact with the user to develop product offering, product pricing, and resource allocation strategies and tactics.

This invention is a means both to allocate all types of resources for commercial, governmental, or non-profit organizations and to price such resources. A linear programming process makes fulfillment allocations used to produce product units. A Resource-conduit process governs the linear programming process, uses two-sided shadow prices, and makes aperture allocations to allow Potential-demand to become Realized-demand. A strict opportunity cost perspective is employed, and the cost of buyable resources is deemed to be the opportunity cost of tying up cash. Resource available quantities, product resource requirements, and Potential-demand as a statistical distribution are specified in a database. The invention reads the database, performs optimization, and then writes allocation directives to the database. Also determined and written to the database are resource marginal (incremental) values and product marginal costs. The database can be viewed and edited through the invention's Graphical User Interface. Monte Carlo simulation, along with generation of supply and demand schedules, is included to facilitate analysis, explore “what if,” and interact with the user to develop product offering, product pricing, and resource allocation strategies and tactics.

The embodiment of the invention provides a billing method, an analysis center and a billing center. The billing method includes the steps that the analysis center inquires the zone corresponding to each lessee and the usable area, corresponding to the lessee, in each zone according to the mark of each lessee, at least one usable area corresponding to each lessee is obtained, the project corresponding to each lessee is inquired according to the mark of the lessee, the resource information of resources used by each lessee are inquired under the usable areas corresponding to the lessee, and the use amounts of the resources are counted; finally, the resource use information of each lessee is obtained, a resource use statistic summary table is generated and sent to the billing center, and the billing center obtains the resource use information of each lessee according to the resource use statistic summary table, and determines the expenses of each lessee according to a resource price list and the resource use information of the lessee. The use of various cloud service resources can be billed in a mixed mode, and multiple cloud platforms in the multiple zones can be billed in a mixed mode.

The invention discloses a multi-dimensional resource pricing method in a mobile cloud computing environment based on a bilateral market. The method runs in the mobile cloud computing environment, the method involves two groups of participants in the mobile cloud computing environment, one group of participants are Cloudlets which have resources, and the other group of participants are VMs which request the resources. The VMs are regarded as a buyer in a bilateral market economic model, the Cloudlets are regarded as a seller, and the two sides complete allocation of the resources through a price interactive mechanism, unloading execution of an application request from the VMs to the Cloudlets is completed, and energy consumption of the mobile equipment is reduced. The price interactive mechanism in the method is based on a bilateral market game and is designed through combination of a punishment pricing mechanism and a balanced utility discount, the multi-dimensional resources of the application request of a mobile user can be reasonably distributed and dispatched on a plurality of Cloudlets, and therefore system benefits of a mobile cloud are maximized.

The invention discloses a resource charging method, a device and a platform. The resource charging method includes steps of acquiring time length and resource number of virtual machine resource used by a user every time in a charging cycle; when the charging cycle is finished, acquiring a charging bill according to the time length, resource number and the resource price of the virtual machine resource used by the user every time. From the technical scheme of the invention, it is obvious that the charging method, the device and the platform have accurately charged the resource use of the user,the waste of user's resource and money is avoided.

The invention discloses a charging method and device under a cloud computing operation system. The method comprises the following steps: acquiring duration for a user to use a virtual machine, service types and configuration parameters of the virtual machine when the virtual machine is closed, and determining a first charging bill according to a preset resource pricing standard for storing the configuration parameters of the virtual machine in a unit time in one-to-one correspondence with each service type; determining a charging impact factor of the user; determining a second charging bill of the user according to the determined charging impact factor of the user and the first charging bill. According to the technical scheme, the accuracy of a charging result and the system resource utilization rate are improved.

Embodiments of the invention provide a processing method and system for determining house resource price information. The method comprises the steps of obtaining similar house resources of a to-be-priced house resource, wherein the similar house resources include similar historical traded house resources; according to a trading price of a target similar historical traded house resource in the similar historical traded house resources, obtaining a pre-estimated trading price of the similar historical traded house resources; and based on a built trading cycle model, and according to an expectedtrading cycle and the pre-estimated trading price, obtaining a list price of the to-be-priced house resource, wherein an input parameter of the trading cycle model are a statistical parameter of the list price and the trading price, and an output parameter of the trading cycle model is the trading cycle. According to the processing method and system, the pre-estimated trading price is obtained according to the similar house resources, and the list price of the house resource is obtained by utilizing the trading cycle model in combination with the expected trading cycle, so that the accuracy and rationality of house resource pricing are improved.

The invention relates to an augmented Lagrangian-based resource consultation mechanism in MANETs (mobile ad hoc networks). The augmented Lagrangian-based resource consultation mechanism includes breaking down the ubiquitous service of a system optimization and balance framework, composed of multi-user and a network, into multiple atomic services; defining agents of various types, establishing and solving a resource pricing model; describing the information intersection in the resource market through the augmented Lagrangian-based resource consultation mechanism. By the use of the augmented Lagrangian-based resource consultation mechanism, user and network benefits can be comprehensively considered, and at the premise of the limited resource, maximum benefits of the whole network is achieved while the serve quality is ensured; multi-user benefits are balanced under the competitive environment, increasing of some user benefits never causes decreasing of other user benefits, with an iterative process, buyer bidding and seller offering are constantly adjusted, and the optimal resource allocation is achieved under the adjustment and control of the resource market.

The invention is applicable to the cloud computing technical field, and provides a resource pricing method based on Pareto optimization under the cloud environment. The method comprises the followingsteps: S1, based on user satisfaction degree and maximum utility of cloud service provider profit, establishing a Pareto optimization cloud service resource pricing model; S2, Pareto optimization is found based on hybrid search algorithm, that is, the best pricing of each cloud service resource is obtained. The invention proposes a resource pricing model based on Pareto optimality, and transformsthe price contradiction into a game between user satisfaction and cloud service provider profit, and finally realizes the balance between user satisfaction and cloud service provider profit, namely realizes Pareto optimality, and obtains the best pricing of each cloud service resource.

The invention discloses a method and apparatus for dynamically regulating pricing on a data inquiry operation. The method comprises: when detecting that distributed resource information of computing resources is changed, acquiring the distributed resource information of each type of computing resources in different time periods; acquiring fixed parameter information of each type of computing resources, wherein the fixed parameter information comprises total resource information of each type of computing resources in different time periods, lowest price information of each type of computing resources in different time periods and highest price information of each type of computing resources in different time periods; according to predetermined computing resource pricing regulating rules, the distributed resource information and the fixed parameter information, regulating pricing information of each type of computing resources in different time periods. Visibly, in the embodiment, the distribution condition of the computing resources is considered, and according to the distributed resource information of each type of resources in different time periods, pricing on the data inquiry operation is dynamically regulated, so that the data inquiry operation is more reasonably priced.

The invention relates to an operation management system and method based on cloud administrator resources. The operation management system is characterized by comprising a resource pricing module forincreasing various resources at any time and pricing; a process management module for customizing personalized application and approval process for different users and resources in the system; an order statistics module for counting various orders of the system; a consumption overview module for showing the consumption overview and details of each user, and supporting accurate queries according tousers; and a reporting module for customizing user consumption reports according to user needs.

The invention discloses a method and apparatus for dynamically regulating pricing on a data inquiry operation. The method comprises: when detecting that distributed resource information of computing resources is changed, acquiring the distributed resource information of each type of computing resources in different time periods; acquiring fixed parameter information of each type of computing resources, wherein the fixed parameter information comprises total resource information of each type of computing resources in different time periods, lowest price information of each type of computing resources in different time periods and highest price information of each type of computing resources in different time periods; according to predetermined computing resource pricing regulating rules, the distributed resource information and the fixed parameter information, regulating pricing information of each type of computing resources in different time periods. Visibly, in the embodiment, the distribution condition of the computing resources is considered, and according to the distributed resource information of each type of resources in different time periods, pricing on the data inquiry operation is dynamically regulated, so that the data inquiry operation is more reasonably priced.

The invention discloses an SDN resource pricing method based on multi-ownership combinatorial double auction. The method comprises the following steps that the parameters of various variables of service chains and resources of an SDN resource system are determined, and resource proxies decompose multi-ownership service chains transmitted by nodes into buying and selling type service chains; the nodes meeting market benefit maximization are solved, and the resource proxies arrange different types of nodes in corresponding sequence tables; an average pricing matrix of transaction is obtained through ordering; a transaction price matrix QUOTE<TT> under the SDN environment is calculated by using a K-pricing scheme; the transaction process is determined, and pricing of the resources is performed according to the relationship between supply and demand of the resources; and total cost and revenue in buying or selling the resources can be obtained. The method is more suitable for the SDN environment and can alleviate problems faced by the SDN resources by utilizing the multi-ownership of a combinatorial double auction model and an SDN resource transaction market.

The invention discloses an SDN resource pricing method based on resource load and user demands. The method specifically comprises the following steps: clustering and segmenting a user according to user demands and a user consumption model in an SDN resource transaction process so as to determine a user type; computing a probability parameter that a user cancels the reservation if the user adopts the planned consumption; computing a handling charge rate collected by a resource provider, establishing a price model and determining a reservation discount price of the planned transaction; computing the current resource load condition if the user adopts the spot consumption, computing the resource initial price by combining the user demands, and determining the final exact price through an auction model. By use of the SDN resource pricing method disclosed by the invention, the user is stimulated to reserve the resource in advance through the price, and a corresponding preferential price is provided for each user in combination with the credibility and the consumption habit, thereby effectively avoiding the problems of overcharge resource load and network congestion caused by a condition that the users propose the resource requests together; the reasonable allocation of the resource is realized, and the normal operation of each meta-service or meta-business can be guaranteed all the time.

A method for cloud disaster recovery data backup based on a game theory relates to the technical field of data backup disaster recovery, and solves the problems in an existing data backup method that the resource cost is high, the storage cost is high, and influences of behaviors of source end cloud suppliers on a target end cloud supplier are neglected. The method for optimal data backup in a cloud disaster recovery environment based on the game theory provided by the invention is characterized in that interaction between the source end cloud supplier and the target end cloud supplier is simulated into a storage resource pricing model; and storage resource leading courses among backup nodes of the target end cloud supplier are modeled into a gaming course which pursues maximum benefits. The invention also provides a method for quantitative computation of optimal solutions of a storage resource quantity and a storage resource price, so that benefits of both gaming parties, namely the source end cloud supplier and the target end cloud supplier can be maximized simultaneously.

The invention discloses a virtual resource sharing distribution method based on a pricing mechanism under a satellite network and application, and belongs to the field of satellite network resources.The method comprises the following steps: S1, defining a quotation model for a user request; S2, defining a pricing mechanism according to the quotation model; S3, dividing the total quotation of theuser request for the required resources into two parts of basic price and marginal cost, and obtaining the total quotation through a quotation model; S4, introducing a resource distribution model, pricing various resources according to a pricing mechanism, and calculating respective dominant shares by all user requests according to the requirements of the resources; and S5, obtaining a revenue function requested by the user and an objective function of the resource allocation model according to a pricing mechanism, and constraining the objective function. According to the resource allocation method and device, it is guaranteed that the resource price occupied by each user to be the maximum is the lowest, so that it is guaranteed that the cost of each user is the lowest and the resources are fully utilized under the condition that the resource requirements are met, and the resource utilization rate and the resource allocation fairness are improved.

The invention discloses a statistical analysis method used for cloud computing resource pricing. The method comprises the following steps: 1, a resource example of a new cloud service provider is given, and a cloud computing example of the existing market is collected; 2, the probability distribution of all existing examples in different price ranges is subjected to statistics; 3, data of the existing examples and a new example are subjected to standard processing, the existing example and the new example are classified, the existing example which is in the same category with the new example are selected as similar examples of the new example; 4, initial market shares of the similar examples are obtained, a user transition probability matrix is built, and short-term market shares and finial market shares of the similar examples are calculated by adopting a Markov chain method; 5, the price, the probability distribution and the market shares of the similar examples are subjected to statistics, and the price of the new example is calculated.

The invention discloses a house resource pricing method and system. The method comprises the steps of extracting first to-be-priced shell resource information data and second to-be-priced shell resource information data from a first database, searching a market shell resource price in a second database, and estimating an estimated to-be-priced shell resource price corresponding to the first to-be-priced shell resource information data through the market shell resource price; processing the first to-be-priced shell resource information data and the second to-be-priced shell resource informationdata to obtain first data and second data; substituting the first data and the estimated to-be-priced house resource price into a to-be-trained model, and training the to-be-trained model to obtain afirst pricing model; and substituting the second data into the first pricing model to calculate the price of the to-be-priced house resource. According to the invention, the to-be-priced shell resource price corresponding to the to-be-priced shell resource information can be calculated by substituting the processed to-be-priced shell resource information data into the first pricing model, and pricing and machine learning are combined to realize a non-artificial pricing system.

The embodiment of the invention provides a billing method, an analysis center and a billing center. The billing method includes the steps that the analysis center inquires the zone corresponding to each lessee and the usable area, corresponding to the lessee, in each zone according to the mark of each lessee, at least one usable area corresponding to each lessee is obtained, the project corresponding to each lessee is inquired according to the mark of the lessee, the resource information of resources used by each lessee are inquired under the usable areas corresponding to the lessee, and the use amounts of the resources are counted; finally, the resource use information of each lessee is obtained, a resource use statistic summary table is generated and sent to the billing center, and the billing center obtains the resource use information of each lessee according to the resource use statistic summary table, and determines the expenses of each lessee according to a resource price list and the resource use information of the lessee. The use of various cloud service resources can be billed in a mixed mode, and multiple cloud platforms in the multiple zones can be billed in a mixed mode.

The invention discloses a demand side resource pricing method and system based on shared random optimization. The method comprises the following steps: firstly, calculating the microgrid operation cost under the condition of having or not having demand response for each scene in N randomly generated scenes; calculating the income of the microgrid operator according to the microgrid operation costunder the demand response and the demand-free response, sorting the income under the N scenes from large to small, and selecting the income without money loss for ensuring that the island microgrid operator does not lack money; and determining a demand side response price according to the money-loss-free income. A microgrid operator responds to resource pricing for a demand side. According to theinvention, the pricing of the demand-side resources is carried out by referring to the improvement condition of the power grid operation benefit after the demand-side response is introduced without considering a utility function or a comfort function, thereby guaranteeing the stable operation of the microgrid, attracting the user to participate in the demand-side response at a higher price, and enabling the pricing to be more reasonable.

The present invention discloses a media asset resource pricing method and system. The method comprises the steps of: performing classification of media asset resources according to access sources of the media asset resources in a server, performing packing processing of the media asset resources belonging to the same class to obtain a plurality of media asset resource packs, and finally, performing pricing of the media asset resources included in the media asset resource packs. Therefore, the purpose of pricing of all the media asset resources in the server is achieved, and a basis is providedfor popularization and application of all the media asset resources in server by managers of the media asset resources. Besides, the types of the media asset resources in the server are expanded, thepricing method of the media asset resources is stilled employed to perform pricing of the expanded media asset resources, and the applicability is high.

The invention discloses a statistical analysis method for cloud computing resource pricing, comprising the following steps: step 1, given a resource instance of a new cloud service provider, and collecting cloud computing instances in the current market; step 2, counting The probability distribution of all current instances in different price ranges; step 3, standardize the data of current instances and new instances, and classify the current instances and new instances, and select the current instance in the same category as the new instance as the new instance Similar instances; step 4, obtain the initial market share of similar instances, and establish a user transition probability matrix, and use the Markov chain method to calculate the short-term market share and final market share of similar instances; step 5, calculate the price and probability of similar instances Distribution and market share, calculate the price of new instances.

The invention discloses an end-to-end network resource allocation method based on Bayesian learning, and belongs to the technical field of calculation, reckoning or counting. According to the method, a solution based on a game framework is adopted, a network resource pricing strategy reflecting service provider demand information is provided, and more reasonable network resource pricing and distribution are realized through analysis of network resource states and service provider behaviors. The method comprises the following steps: firstly, establishing game models of a plurality of service providers and operators, and selecting a unit network slice price of a first stage by the operators according to limited demand information; and updating the demand information in the second stage to determine the price. A simulation result shows the existence of a Nash equilibrium point of the system model, and a response type network resource slice allocation scheme is provided, so that resource shortage and network congestion caused when a service provider intensively requests resources are avoided, and reasonable allocation of network resources is realized.

The invention relates to a resource pricing processing method, device and system, computer equipment and a storage medium, and the method comprises the steps: calling first configuration item information from a configuration platform, and determining a service resource of resource pricing according to the first configuration item information; acquiring a first resource quota of the service resources, and performing resource pricing on the service resources according to the first resource quota; when the service resources are deducted, acquiring a second resource quota of the service resources, adjusting the resource pricing of the service resources according to the second resource quota being smaller than the first resource quota; and acquiring pricing information of resource pricing of the service resources, resource quota use information of the service resources after resource pricing adjustment and resource deduction information of the service resources, and carrying out resource analysis on the service resources. According to the method, the full-link service process of the service resources can be monitored.

The invention discloses a distributed cloud and fog network resource pricing strategy for a mobile block chain system, so as to efficiently utilize computing resources and communication resources in a cloud and fog network. The computing power demand of an edge computing user in a block chain system and computing resource allocation in a cloud and fog network are modeled as a master-slave game model, an FAP sets the price of computing resources according to the maximum income, and the edge computing user decides to rent the computing resources of a fog node or a cloud computing center according to the price of the computing resources provided by the fog node FAP. The game between the user and the FAP is calculated through the edge to maximize the common revenue. According to the invention, a cloud and fog fusion network is considered to participate in and support a block chain system, so that the application scene of a block chain network technology is effectively expanded.

The invention discloses a green energy harvesting technology for distributed wireless backhaul links. Each node on the wireless backhaul link is functioned by a green energy node. The disclosed technology is implemented through a renewable energy distribution method based on a master-slave game, which enables stable networking of the entire distributed green wireless link. The algorithm contains the following steps: the first step, the energy supplier on the backhaul link sets the appropriate energy price; the second step, the operator sets the subscription volume and service fee according to the energy price; the third step, the energy supplier of each node Form an alliance among them and repeat steps one and two to achieve a stable alliance structure. Compared with the existing technology, the resource pricing technology designed by the present invention can enable wireless backhaul link operators and multiple distributed green energy supply nodes to work collaboratively and stably, so that all parties can obtain reasonable benefits, thereby constructing an efficient , Stable green wireless backhaul link system.

The invention discloses a resource processing method and device, and a value conversion method and device. The resource processing method comprises the following steps of receiving a resource processing instruction; responding to the resource processing instruction and acquiring a first resource value and a first conversion coefficient; according to the ratio of the first resource value and the first conversion coefficient, acquiring a second conversion coefficient; according to the ratio of the first resource value and the second conversion coefficient, acquiring a second resource value. Thevalue conversion method comprises the following steps of receiving a value conversion instruction; responding to the value conversion instruction and acquiring a total resource value and the resourcepricing value of a platform in the previous day; and according to the ratio of the total resource value and the resource pricing of the platform in the previous day, acquiring the current integral pricing value of a commodity. In the method of the invention, the second resource value and the first resource value can be maintained to be consistent, simultaneously, the current integral pricing valueof hte commodity is acquired, resource processing and value conversion efficiency is increased, and simultaneously, the value of the commodity is accurately embodied.