CN107256460B - Resource allocation method and device based on real estate - Google Patents
Resource allocation method and device based on real estate Download PDFInfo
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- CN107256460B CN107256460B CN201710433140.1A CN201710433140A CN107256460B CN 107256460 B CN107256460 B CN 107256460B CN 201710433140 A CN201710433140 A CN 201710433140A CN 107256460 B CN107256460 B CN 107256460B
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Abstract
The invention provides a resource allocation method and a device based on real estate, wherein the method comprises the following steps: acquiring characteristic information of real estate and characteristic information of a network server; associating the characteristic information of the real estate with the characteristic information of the network server to obtain associated information; and configuring network virtual resources and social entity resources according to the associated information. The real estate-based resource allocation method and device provided by the invention improve the resource allocation efficiency and are beneficial to the good use of network virtual resources and social entity resources.
Description
Technical Field
The present invention relates to network information technologies, and in particular, to a resource allocation method and device based on real estate.
Background
With the rich development of internet content, the application of information service-oriented network services is more and more diversified, and various applications such as electronic commerce, intelligent transportation, logistics distribution, military and national defense, public security and fire protection, environmental engineering, field data acquisition and the like play an important role in the digital life of people in the future. Meanwhile, with the development of land area, airspace and house and land industries in China and even all over the world, the uniqueness of real estate addresses is revealed gradually, and the attribution of real estate property rights is determined gradually, namely the real estate has uniqueness and certainty.
In the prior art, network services oriented to information services are executed by servers distributed all over the world, but network resources are dispersed and have poor interoperability, so that the network information resource configuration efficiency is low, and the network virtual resources and social entity resources are not favorably used.
Disclosure of Invention
The invention provides a resource allocation method and device based on real estate, which improve the efficiency of resource allocation and enhance the safety and the efficiency of social entities of network content services.
The invention provides a resource allocation method based on real estate, which comprises the following steps:
acquiring characteristic information of real estate and characteristic information of a network server;
associating the characteristic information of the real estate with the characteristic information of the network server to obtain associated information;
and configuring network virtual resources and social entity resources according to the associated information.
In an embodiment of the present invention, the configuring, according to the association information, network virtual resources and social entity resources includes:
naming the association information to enable the association between the servers and the association between the server contents to jointly form a resource dynamic topological graph of the named data network, wherein the resource dynamic topological graph reflects the network virtual resources and the social entity resources on the association between the characteristic information of the real estate and the real estate.
In an embodiment of the present invention, after naming the association information, so that the association between the servers and the association between the server contents together form a dynamic topology diagram of resources of the named data network, the method further includes:
predicting dynamic changes of the network virtual resources and the social entity resources through a neural network.
In an embodiment of the present invention, after naming the association information, so that the association between the servers and the association between the server contents together form a dynamic topology diagram of resources of the named data network, the method further includes:
and establishing a network closed loop cycle development model according to the social entity resources, the network server, the content of the network virtual resources and the user group of the network server resources.
In an embodiment of the present invention, after the establishing a network closed loop cycle development model according to the social entity resource, the network server, the content of the network virtual resource, and the user group of the network server resource, the method further includes:
configuring the network virtual resources and the social entity resources according to the network closed loop cycle development model;
and according to the network closed loop cycle development relationship and the resource scheduling direction, performing information transmission and resource scheduling by adopting an optimal control strategy, and constructing a fast and high-speed green channel for network routing transmission.
In an embodiment of the present invention, the acquiring the characteristic information of the real estate and the characteristic information of the network server includes:
analyzing characteristics of the real estate, such as address, property right, distribution, structure, density, purpose, age, category and the like to obtain characteristic information of the real estate;
and planning the resources of the network server according to the relation among the user, the resources and the service application to obtain the characteristic information of the network server.
In an embodiment of the present invention, the associating the characteristic information of the real estate with the characteristic information of the network server to obtain associated information includes:
and mapping and matching the address and the property right of the real estate with the network server to obtain the associated information.
The invention provides a resource allocation device based on real estate, comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring the characteristic information of the real estate and the characteristic information of the network server;
the association module is used for associating the characteristic information of the real estate with the characteristic information of the network server to obtain association information;
and the configuration module is used for configuring network virtual resources and social entity resources according to the associated information.
In an embodiment of the present invention, the configuration module is specifically configured to,
naming the association information to enable the association between the servers and the association between the server contents to jointly form a resource dynamic topological graph of a named data network, wherein the resource dynamic topological graph reflects the network virtual resources and the social entity resources on the association between the characteristic information of the real estate and the real estate;
predicting dynamic changes of the network virtual resources and the social entity resources through a neural network;
establishing a network closed loop cycle development model according to the social entity resources, the network server, the content of the network virtual resources and the user group of the network server resources;
configuring the network virtual resources and the social entity resources according to the network closed loop cycle development model;
and according to the network closed loop cycle development relationship, the resource scheduling direction and the like, performing information transmission and resource scheduling by adopting an optimal control strategy, and constructing a fast and high-speed green channel for network routing transmission.
In an embodiment of the present invention, the obtaining module is specifically configured to,
analyzing characteristics of the real estate, such as address, property right, distribution, structure, density, purpose, age, category and the like to obtain characteristic information of the real estate;
planning the resources of the network server according to the relation among the users, the resources and the service application to obtain the characteristic information of the network server;
the association module is specifically configured to map and match addresses and property rights of the real estate and the network server with each other to obtain the association information.
The invention provides a resource allocation method and a device based on real estate, wherein the method comprises the following steps: acquiring characteristic information of real estate and characteristic information of a network server; associating the characteristic information of the real estate with the characteristic information of the network server to obtain associated information; and configuring network virtual resources and social entity resources according to the associated information. The real estate-based resource allocation method and device provided by the invention improve the efficiency of network information resource allocation and are beneficial to good use of network virtual resources and social entity resources.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flowchart illustrating a first embodiment of a real estate-based resource allocation method of the present invention;
FIG. 2 is a flowchart illustrating a second embodiment of a real estate-based resource allocation method of the present invention;
FIG. 3 is a diagram illustrating a model for associating virtual resources with physical resources according to the present invention;
FIG. 4 is a schematic diagram of a neural network system of a virtual resource and physical resource association model according to the present invention;
FIG. 5 is a schematic diagram of a closed loop cycle development relationship between virtual resources and physical resources according to the present invention;
FIG. 6 is a schematic structural diagram of a first embodiment of a real estate-based resource allocation apparatus according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
Fig. 1 is a flowchart illustrating a first embodiment of a real estate-based resource allocation method according to the present invention. As shown in fig. 1, the resource allocation method based on real estate in this embodiment includes the following steps:
s101: and acquiring the characteristic information of the real estate and the characteristic information of the network server.
Specifically, in order to reasonably plan the network information resources, the network virtual resources and the social entity resources are analyzed and configured in a real estate-based manner, in S101, feature information of the real estate and feature information of the network server are first obtained. The characteristic information of the real estate includes, for example: address, property, distribution, structure, density, purpose, age, and category of real property, etc. The characteristic information of the web server includes, for example: type, content, number, density, number, scale, etc. of web servers.
Therefore, S101 includes: analyzing the characteristics of the real estate, such as address, property right, distribution, structure, density, purpose, age, category and the like to obtain characteristic information of the real estate; and planning the resources of the network server according to the relation among the user, the resources and the service application to obtain the characteristic information of the network server. The characteristic information of the network server refers to the characteristic information of all resources passing through the network server, and the resources passing through the network server comprise network virtual resources and social entity resources.
In particular, the characteristic information of real estate can be described by a value description function V of real estateEstate＝VE(x1,x2,x3,x4,x5,x6,x7) In which VEstate，VE()，x1，x2，x3，x4，x5，x6，x7The value of real estate, the value function of real estate, real estate parameters that affect the value of real estate, respectively: address, distribution, structure, density, purpose, age, category of real estate. For example: one possible implementation of the value function of real estate is VEstate＝x1+x2+x3+x4+x5+x6+x7Which isThe address is numbered by the area and the street of the real estate located in the city, the distribution refers to the position information from the city center or the functional area, the structure refers to the division of the real estate structure by different structures, the density refers to the real estate density at the periphery of the real estate, the purpose is to distinguish the real estate by different numbers, the generation time of the real estate from the generation to the present or the generation or construction time of the real estate can be the generation time of the real estate, the category refers to public business, and the like. All of the above features can be represented in numerical form and added to yield the value of real estate. Optionally, each term may also be multiplied by a different weight in the real estate value function formula, thereby heavily measuring the value of the real estate.
The characteristic information of the network server can be reflected by a value description function of the information resource, a value description function of the virtual resource and a value description function of the entity resource, wherein the value description function of the information resource, the value description function of the virtual resource and the value description function of the entity resource can be used for quantifying the network information resource and the social entity resource. The value description function of the information resource reasonably and properly plans complicated network resources by analyzing the relationship between the network users and the information resources, the relationship between the business application and the information resources, the relationship between the entity resources and the information resources and the relationship between the real estate and the information resources, and finally the characteristic information of the network information resources is described by the value description function V of the information resourcesInformationResources＝VIR(VEstate,VEntityResources,VOtherInformationResources,u1,u2,u3) In which VInformationResources，VIR()，VEntityResources，VOtherInformationResources，u1，u2，u3Respectively representing the value of the information resource, a value function of the information resource, the value of the entity resource, the values of other information resources and parameters influencing the value of the information resource: user, business application and supporting network facility values. For example: one possible implementation of the value description function of the information resource is as follows: vInformationResources＝VEstate+VEntityResources+VOtherInformationResources+u1+u2+u3. All the above characteristics can be represented in a digital form, and the values are added to obtain a value description of the information resource. Optionally, each term in the formula can be multiplied by different weights, so that the value of the information resource is heavily measured. The value description function of the virtual resource is VVirtualResources＝VVR(VInformationResources,u3) Wherein V isVirtualResources，VVR() Representing the value of the virtual resource and the cost function of the virtual resource, respectively. VEntityResources＝VER(VEstate,VInformationResources,VOtherInformationResources,VOtherEntityResources,m1,m2,m3) Describing a function for the value of the entity resource, wherein VER()，VOtherEntityResources，m1，m2，m3Respectively representing the value function of the entity resource, the values of other entity resources and parameters influencing the value of the entity resource. Wherein the parameters affecting the value of the entity resource include: user, service application and entity resource supporting facility values. For example: one possible implementation of the value description function of the virtual resource is as follows: vVirtualResources＝VInformationResources+u3All features in the formula are represented in numerical form. One possible implementation of the value description function of the entity resource is as follows: vEntityResources＝VEstate+VInformationResources+VOtherInformationResources+VOtherEntityResources+m1+m2+m3. All the above features can be represented in a digital form, and the value descriptions of the virtual resources and the physical resources can be obtained after the features are added. Optionally, each term in the formula may be multiplied by a different weight, so as to measure the value of the virtual resource and the entity resource with emphasis.
S102: and associating the characteristic information of the real estate with the characteristic information of the network server to obtain associated information.
Specifically, associating the characteristic information of the real estate with the characteristic information of the network server includes: and mapping and matching the address and the property right of the real estate and the network server to obtain the associated information.
Mapping and matching the addresses and property rights of the network server and the real estate to obtain the associated information, wherein the associated information can be a value relation function V of the value of the constructed internet network server information resources and the real estateInformationResources＝fIE(VEstate) Thus obtaining the product. Wherein f isIE() A value-relation function representing the value of the information resource and the real estate. The value-relation function of the information resource and the real estate may be represented in a digital weighting form, for example, the use in the forms of a mall, a museum, and the like included in the real estate is marked with different numbers, and the value of the real estate is evaluated through the different numbers, so that the value-relation function of the information resource and the real estate is obtained in the digital weighting form.
S103: and configuring network virtual resources and social entity resources according to the associated information.
Specifically, the network server resource is configured according to the association information obtained in S102. Wherein the configuring may include: the method comprises the steps of dynamic topological graph of network information resources, dynamic change of virtual resources and entity resources is predicted, a network information resource closed-loop development model is established according to the entity resources, servers, contents and user groups, and the network virtual resources and social entity resources are configured according to the closed-loop development model. Herein, a virtual resource refers to a network virtual resource, and an entity resource refers to a social entity resource.
Because each node of the internet exists in a certain real estate at every moment, the address of the internet server and the address and property right of the real estate can be mapped and matched with each other, the mapping and matching relation brings convenience to management of internet information resources and governance of internet content, actual activities of a server user group and users engaged in through the internet can be further determined, and safety and efficiency of a network content service social entity are guaranteed. The virtual resources in the invention mainly refer to network resources, including network information resources and related supporting network facilities such as: a server, etc. The entity resource in the invention mainly refers to the off-line entity economic resource. The Internet server also comprises an Internet server such as a PC terminal, a smart phone terminal, a tablet and other very small equipment which can have the function of the server.
According to the resource allocation method based on the real estate, the network information resources based on the real estate, the social entity resources based on the real estate and the association of the social entity resources are used, the efficiency of network information resource allocation is improved, the method is an exploration research on content internet, convenience is brought to management of internet server resources and treatment of internet server contents, and the safety and the efficiency of the social entity of the network content service are guaranteed. Meanwhile, each server node of the current internet is always located at a real estate, so that the address of the internet server and the address and property right of the real estate can be mapped and matched with each other, the mapping and matching relation brings convenience for management of internet information resources and treatment of internet content, actual activities of a server user group and users engaged in through the internet can be further determined, and safety and efficiency of a network content service social entity are guaranteed.
Fig. 2 is a flowchart illustrating a second embodiment of a real estate-based resource allocation method according to the present invention. As shown in fig. 2, this embodiment further includes, on the basis of the method shown in fig. 1:
s201: and naming the association information to enable the association between the servers and the association between the server contents to jointly form a resource dynamic topological graph of the named data network, wherein the resource dynamic topological graph reflects the network virtual resources and the social entity resources on the association between the characteristic information of the real estate and the real estate.
Specifically, the mapping and matching relationship between the internet server and the real estate is named effectively, and the association between the servers and the association between the server contents form a resource dynamic topological graph of the named data network together, which can be reflected on the association between the real estate. The effective naming can adopt a safe coding mode to carry out network coding, and the associated information of the real estate refers to the whole obtained by combining a plurality of real estate.
Establishing a value relation function V of the correlation between the internet servers and the information resources of the internet serversInformationResources＝fIS(fs1(s1,r1),fs2(s2,r2),...,fsi(si,ri),...,fsn(sn,rn) 1,2,., n, wherein fIS()，fsi()，si，riThe information resource management method comprises a value relation function representing association between the information resource and the server, a value influence function of the ith association server, a value parameter of the ith association server and a routing parameter of the ith association server. One possible implementation of the correlation between internet servers and the value relationship function of the internet server information resources is as follows: vInformationResources＝fs1(s1,r1)+fs2(s2,r2)+...+fsi(si,ri)+...+fsn(sn,rn) 1, 2.., n. All the characteristics can be represented in a digital form, and the characteristics are added to obtain the description of the value relationship between the correlation between the internet servers and the information resources of the internet servers. Optionally, each item in the formula may be multiplied by a different weight, so as to heavily measure the relationship between the association between the internet servers and the value of the information resources of the internet servers. Constructing a value relation function V of real estate and associations between real estate mapped by association matching between serversEstate＝fEE(fE1(VE1,y1),fE2(VE2,y2),...,fEi(VEi,yi),...,fEn(VEn,yn) 1,2,., n, wherein fEE()，fEi()，VEi，yiA value relation function representing the association between real estate and the server's association matching mapping, the price of the ith associated real estate, respectivelyA value influence function, an ith real estate-associated value parameter, and an ith real estate-associated location traffic parameter. One possible implementation of the above cost relationship function is: vEstate＝fE1(VE1,y1)+fE2(VE2,y2)+...+fEi(VEi,yi)+...+fEn(VEn,yn) N, all the above features can be represented in a numerical form, and the sum is carried out to obtain a description of the value relation between the association between the real estate and the real estate of the association matching mapping between the servers. Optionally, each term in the formula may be multiplied by a different weight, so as to measure the value relationship between the real estate and the association between the servers, which is associated with the mapping, with emphasis on the value relationship between the real estate.
FIG. 3 is a diagram illustrating a model for associating virtual resources with physical resources according to the present invention. As shown in fig. 3, there is a virtual resource and an entity resource associated with the entity resource e 11. Among the virtual resources are information resource at server s11, information resource at server s12, information resource at server s13, information resource at server s111, which are associated with each other by routes r11, r12 and r111 and with entity resource e11 by path r1, and information resource at server s12 is also associated with entity resource e112, so that entity resource e11 is associated with entity resource e 112. The virtual resources comprise information resources at the server s21, information resources at the server s22 and information resources at the server s31, the virtual resources are mutually related through routes r21 and r31 and are related with entity resources e11 through paths r2 and r3, the information resources at the server s21 and the information resources at the server s31 are simultaneously mutually related with the information resources at the server s22, and the information resources can be transmitted and shared among the three. In fig. 3, the entity resource e11 may also be directly associated with the entity resource e12, various resources are associated and matched with the real estate where the entity resource e12 is located, and the entity resource e12 may also have an independent virtual resource, fig. 3 is only an example of association, and the association between information resources at a specific server may establish various networking connection modes and structures, such as distributed, centralized, distributed, and clustered. All servers associated with entity resource e11 in FIG. 3 through paths r1, r2, and r3 and their content information resources, etc. form virtual resources associated with entity resource e 11; other entity resources directly and indirectly associated with entity resource e11 such as: entity resource e12 and entity resource e112, form the entity resource associated with entity resource e 11.
S202: and predicting dynamic changes of the network virtual resources and the social entity resources through the neural network.
In the embodiment, the mapping and matching relationship between the internet server and the real estate is named effectively, and the association between the servers and the association between the server contents form a resource dynamic topological graph of the named data network together, which can be reflected on the association between the real estate. The resources have dynamic properties, such as changes of the scale, type, density and breadth of server resources, changes of the density, the breadth and characteristics of user groups, changes of contents, changes of entity resources and the like, and changes of a future network can be predicted according to the strategies of transition and statistics of historical data combined with neural network learning, so that changes and values of real estate can also be predicted. The entity resources, the servers, the contents and the user groups form a network closed loop circulation development relationship, the resource data are quantified, benign development and change of the network closed loop circulation relationship are effectively managed and controlled according to the real estate of the entity resources, the real estate of the servers, the uniqueness and the certainty of the real estate of the user groups and the regional characteristics of the real estate, the resource scheduling is accurate and real-time, the benign and stable development of social economy is further realized, and the stability of the virtual resources and the entity resources and the safety of network services are guaranteed. According to the network closed loop cycle development relationship, the resource scheduling direction and the like, the invention ensures the high efficiency and reliability of information transmission by constructing a network routing transmission fast and high-speed green channel strategy method.
The dynamic changes of the virtual resources and the entity resources are predicted according to the transition and statistics of historical data and the strategy of neural network learning. Specifically, according to the historical data changes of the entity resources, the information resources, the number of servers and the real estate value and the changes of the corresponding value description function and the value relation function parameter, a neural network learning system of the entity resource supply and demand, the information resource supply and demand and the real estate value is constructed, the dynamic changes of the virtual resources and the entity resources are predicted, the entity resource supply and demand, the information resource supply and demand, the server demand, the scale of a user group and the like at a certain real estate can be quantified, and the supply and demand range, the supply and demand quantity and the like of the content can be determined.
FIG. 4 is a schematic diagram of a neural network system of a virtual resource and physical resource association model according to the present invention. As shown in FIG. 4, FIG. 4 may represent a simplified neural network learning system based on a multi-input, multi-output model of associating virtual resources with physical resources based on real estate. In fig. 4, first, initial values of management rules, real estate, entity resources and user quantities can be determined and initialized approximately in a quantitative manner, so that the server quantity and the content information resource quantity of virtual resources can be determined according to a functional relationship and an actual deployment situation, the service application quantity can be determined according to the initial values of the management rules, the real estate, the entity resources and the user quantities in a quantitative manner, and meanwhile, the virtual resources and the service application quantity are influenced with each other, the service application quantity can be adjusted according to the virtual resource quantity, the virtual resource quantity can also be adjusted according to the requirements of the service application quantity, and the supply and demand balance can be achieved between the virtual resources and the service. The management rule, real estate, entity resources, virtual resources and service application amount can finally influence the obtained number of online and offline real users, the management rule, the real estate and the entity resources can be adjusted again according to the number of the real users, further the virtual resource amount and the service application amount can be determined again, if the obtained fluctuation of the number of the real users is not large, the fact that the supply and demand of the entity resources and the virtual resources reach a balance is shown, the dynamic learning process is achieved, the balance can be broken through new management rules, service applications or entity resources and the like, and the system can continue to adjust until the balance is reached.
S203: and establishing a network closed loop cycle development model according to social entity resources, the network server, the content of the network virtual resources and the user group of the network server resources. S204: and configuring network virtual resources and social entity resources according to the network closed loop cycle development model. S205: and according to the network closed loop cycle development relationship and the resource scheduling direction, performing information transmission and resource scheduling by adopting an optimal control strategy, and constructing a fast and high-speed green channel for network routing transmission.
Specifically, S203 may be performed simultaneously with S202. In S203-S205, changes and adjustments in management rules and policies may affect the effects of entity resource supply demand, information resource supply demand, and real estate value, as well as network closed loop cycle development. And according to the network closed loop cycle development relationship, the resource scheduling direction and the like, an optimal control strategy is adopted for information transmission and resource scheduling, and the high efficiency and reliability of information transmission are ensured by constructing a network routing transmission fast and high-speed green channel strategy method. The content information resource server can be constructed near real estate entity resources, near user groups or in other places for safe, efficient and available route transmission according to network routing and transmission conditions. FIG. 5 is a schematic diagram of a closed loop cycle development relationship between virtual resources and physical resources according to the present invention. As shown in fig. 5, the real resources at the offline real estate are integrated into online virtual resources, and the online information resources are formed by the content information resources at a server at a real estate for information delivery service users; wherein the server content information resource further can form a business application at a real estate or the server content information resource is formed according to a specific business application and serves for the specific business application; various business application services various users, and the positions of the online users and the offline users form the distribution of the users at various real estate positions; the supply and demand quantity, the supply and demand range and the supply and demand users of entity resources, information resources and service application can be regulated and controlled according to the number and the positions of the users, so that the effect of the closed loop cycle development of the network is influenced.
Specifically, through the steps of S101 to S204 in the above embodiment of the present invention, the following resource allocation effect can be achieved. A supermarket comprises an online store, a server of the online store is located in the supermarket, and after a period of statistics, a user who often visits the supermarket goes to other online stores to shop clothes after shopping in the online store. It is concluded that a clothing store brick and mortar store can be opened by the supermarket for clothes. The embodiment of the invention can also achieve the effect of resource allocation among different servers, such as: the online shop server of a national chain supermarket is located in Beijing, and most users accessing the online shop are found to be from Shanghai after a period of statistics. It is concluded that a branch of a supermarket can be set up in the Shanghai.
FIG. 6 is a schematic structural diagram of a first embodiment of a real estate-based resource allocation apparatus according to the present invention. As shown in fig. 6, the resource allocation apparatus based on real estate in this embodiment includes: an acquisition module 601, an association module 602, and a configuration module 603. The obtaining module 601 is configured to obtain characteristic information of real estate and characteristic information of a network server; the association module 602 is configured to associate the feature information of the real estate with the feature information of the network server to obtain association information; the configuration module 603 is configured to configure network virtual resources and social entity resources according to the association information.
The resource allocation apparatus based on real estate provided in this embodiment is used for executing the resource allocation method based on real estate in the embodiment shown in fig. 1, and has the same technical features and technical effects, which are not described herein again.
Further, in the above implementation, the configuration module 603 is specifically configured to,
naming the associated information, wherein the association between the servers and the association between the server contents form a resource dynamic topological graph of the named data network together, and the resource dynamic topological graph reflects the network virtual resources and the social entity resources on the association between the characteristic information of the real estate and the real estate;
predicting dynamic changes of network virtual resources and social entity resources through a neural network;
establishing a network closed loop cycle development model according to social entity resources, the content of the network server, the content of the network virtual resources and the user group of the network server resources;
and configuring network virtual resources and social entity resources according to the network closed loop cycle development model.
The resource allocation apparatus based on real estate provided in this embodiment is used for executing the resource allocation method based on real estate in the embodiment shown in fig. 2, and has the same technical features and technical effects, which are not described herein again.
Optionally, in the foregoing embodiment, the obtaining module 601 is specifically configured to analyze characteristics of the address, property, distribution, structure, density, usage, age, category, and the like of the real estate to obtain characteristic information of the real estate;
and planning the resources of the network server according to the relation among the user, the resources and the service application to obtain the characteristic information of the network server.
Optionally, in the foregoing embodiment, the association module 602 is specifically configured to map and match addresses and property rights of the real property with each other to obtain the association information.
The resource allocation apparatus based on real estate provided in this embodiment is used for executing the resource allocation method based on real estate in the foregoing embodiment, and has the same technical features and technical effects, which are not described herein again.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (9)
1. A resource allocation method based on real estate is characterized by comprising the following steps:
acquiring characteristic information of real estate and characteristic information of a network server;
associating the characteristic information of the real estate with the characteristic information of the network server to obtain associated information;
configuring network virtual resources and social entity resources according to the associated information, wherein the network virtual resources comprise network information resources and a network server, and the social entity resources comprise offline entity resources;
the associating the characteristic information of the real estate with the characteristic information of the network server to obtain associated information includes: and mapping and matching the address and the property right of the real estate with the network server to obtain the associated information.
2. The method of claim 1,
the configuring of the network virtual resources and the social entity resources according to the association information comprises:
naming the association information to enable the association between the servers and the association between the server contents to jointly form a resource dynamic topological graph of the named data network, wherein the resource dynamic topological graph reflects the network virtual resources and the social entity resources on the association between the characteristic information of the real estate and the real estate.
3. The method of claim 2, wherein after naming the association information such that the association between the servers and the association between the server contents together form a dynamic topology of resources of the named data network, further comprising:
predicting dynamic changes of the network virtual resources and the social entity resources through a neural network.
4. The method of claim 3, wherein after naming the association information such that the association between servers and the association between server contents together form a dynamic topology of resources of a named data network, further comprising:
and establishing a network closed loop cycle development model according to the social entity resources, the network server, the content of the network virtual resources and the user group of the network server resources.
5. The method of claim 4, wherein after establishing a network closed loop cycle development model according to the social entity resources and the network server, the content of the network virtual resources, and the user group of the network server resources, the method further comprises:
configuring the network virtual resources and the social entity resources according to the network closed loop cycle development model;
and according to the network closed loop cycle development relationship and the resource scheduling direction, performing information transmission and resource scheduling by adopting an optimal control strategy, and constructing a fast and high-speed green channel for network routing transmission.
6. The method of claim 1, wherein the obtaining the characteristic information of the real estate and the characteristic information of the network server comprises:
analyzing characteristics of the real estate, such as address, property right, distribution, structure, density, purpose, age, category and the like to obtain characteristic information of the real estate;
and planning the resources of the network server according to the relation among the user, the resources and the service application to obtain the characteristic information of the network server.
7. A real estate-based resource configuration apparatus, comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring the characteristic information of the real estate and the characteristic information of the network server;
the association module is used for associating the characteristic information of the real estate with the characteristic information of the network server to obtain association information;
the configuration module is used for configuring network virtual resources and social entity resources according to the association information, the network virtual resources comprise network information resources and network servers, and the social entity resources comprise offline entity resources;
the association module is specifically configured to map and match the address and property right of the real estate with the network server to obtain the association information.
8. The apparatus of claim 7, wherein the configuration module is specifically configured to,
naming the association information to enable the association between the servers and the association between the server contents to jointly form a resource dynamic topological graph of a named data network, wherein the resource dynamic topological graph reflects the network virtual resources and the social entity resources on the association between the characteristic information of the real estate and the real estate;
predicting dynamic changes of the network virtual resources and the social entity resources through a neural network;
establishing a network closed loop cycle development model according to the social entity resources, the network server, the content of the network virtual resources and the user group of the network server resources;
configuring the network virtual resources and the social entity resources according to the network closed loop cycle development model;
and according to the network closed loop cycle development relationship, the resource scheduling direction and the like, performing information transmission and resource scheduling by adopting an optimal control strategy, and constructing a fast and high-speed green channel for network routing transmission.
9. The apparatus of claim 7, wherein the obtaining module is specifically configured to,
analyzing characteristics of the real estate, such as address, property right, distribution, structure, density, purpose, age, category and the like to obtain characteristic information of the real estate;
planning the resources of the network server according to the relation among the users, the resources and the service application to obtain the characteristic information of the network server;
the association module is specifically configured to map and match addresses and property rights of the real estate and the network server with each other to obtain the association information.
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