Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented 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.
In an embodiment, fig. 1 is a flowchart of a power communication network evaluation method provided in the embodiment of the present invention, where the method may be implemented by a power communication network evaluation device, and the power communication network evaluation device may be implemented in the form of hardware and/or software, where the method is applicable to the situation of timely evaluating a network architecture and a resource scheduling system of a novel power communication network.
As shown in fig. 1, a power communication network evaluation method provided in this embodiment may include:
s110, generating a network evaluation request according to at least one service requirement in a service domain of the power communication network.
In the embodiment of the invention, the service requirement refers to a specific requirement of the service, and the service requirement can comprise a time delay requirement, an accuracy requirement, a reliability requirement and the like. The service domain refers to a service obtained by abstract modeling of various services generated by diversified scenes in the power communication network, and may include various tasks and service attributes thereof in the power communication network, and exemplary service attributes may include service types, service data volume sizes, service demand types, service levels, and the like. A network evaluation request may be understood as a request to evaluate the power communication network's capabilities and economies based on how well the traffic is compatible with the power communication network.
In particular, the power communication network service domain may include a plurality of different services applied to different usage scenarios, and exemplary service domains may include a command dispatch service, a distribution automation service, an equipment unmanned patrol service, and the like. At least one business requirement in the business domain may be selected to generate a network evaluation request to evaluate the power communication network's capabilities and economies based on the network evaluation request, which may evaluate the power communication network's network architecture and resource scheduling system based on the business requirement.
S120, determining at least one service function chain meeting the network evaluation request in a logic domain of the power communication network, and determining a first matching degree of the network evaluation request and the service function chain.
In the embodiment of the invention, the logic domain refers to the steps of logically dividing the existing power communication network, then abstracting out the functions of different physical components to split or combine, and forming a service function set, wherein the logic domain can comprise specific attributes of service functions, and the specific attributes can comprise the types of the service functions, the amount of resources consumed by the service functions for processing unit flow, the performance index of the service functions for processing the unit flow, and the like. A service function chain refers to a set of service functions formed by service functions in a logical domain according to the traffic demands in a network evaluation request. The first degree of matching may be understood as a mapping matching probability between the traffic demand in the network evaluation request and the service function chain in the power communication network logical domain.
Specifically, a plurality of different service functions exist in a logic domain of the power communication network to meet different service requirements, corresponding service functions can be searched in the logic domain based on the service requirements in the generated network evaluation request, the service functions meeting the service requirements are formed into a service function chain, at least one service function chain can be determined in the logic domain of the power communication network, the matching degree of the service function chain and the network evaluation request can be obtained based on the determined service function chain, and mapping from the service domain of the power communication network to the logic domain is performed.
S130, mapping the service functions included in each service function chain to physical equipment of a physical domain in the power communication network, and determining a second matching degree of each service function chain and the physical equipment.
In the embodiment of the present invention, the physical device refers to a device that provides basic resources and operates network functions in the power communication network, and exemplary physical devices may include an access network device, a transmission network device, a core network device, and the like. The physical domain refers to abstract modeling of physical devices in the power communication network that provide basic resources and run network functions, and may include specific attributes of the physical devices, which may include device types, device location information, and amounts of device-usable resources of the physical devices, and the like. The second matching degree can be understood as a mapping probability obtained by matching a service function in a service function chain with a physical device in a physical domain, and the service function is formed by splitting and combining functions abstracted from the physical device, a single physical device can correspond to a plurality of service functions, and a single service function can also be matched with a plurality of physical devices.
Specifically, a plurality of physical devices capable of providing different service functions exist in a physical domain of the power communication network, the service functions included in each service function chain obtained above can be mapped to the physical domain of the power communication network under the condition of meeting resource requirements, the physical devices for realizing the service functions are searched and determined in the physical domain, the matching degree of each service function chain and the physical devices can be determined, and mapping from the logic domain of the power communication network to the physical domain is performed.
And S140, determining the matching probability of the service function chain and the performance index of the physical equipment in the power communication network based on the first matching degree and the second matching degree, and determining the fitting entropy corresponding to the matching probability.
In the embodiment of the invention, the performance index refers to an index for evaluating the service capability provided by the service function chain, and the performance index can comprise a time delay index, a reliability index, an accuracy index and the like. The fit entropy refers to a quantized value that measures the fit degree between the service capability provided by the service function chain group and the service capability required by the service, and can be divided into a plurality of parts based on the multidimensional property of the service capability.
Specifically, the matching probability of the performance indexes of the service function chain and the physical equipment in the power communication network can be determined based on the obtained first matching degree and the obtained second matching degree, that is, the matching probability of the service capability of different performance indexes provided by the service function chain and the basic resources and the running network functions of different performance indexes provided by the physical equipment can be obtained, the corresponding fitting entropy can be determined through calculation according to the obtained matching probability, and the corresponding time delay fitting entropy can be obtained through calculation according to the matching probability of the time delay indexes of the service function chain and the physical equipment.
And S150, determining and evaluating a network utility value of the power communication network based on the fit entropy and the resource use cost of the service function chain.
In the embodiment of the invention, the resource use cost refers to the sum of resources to be consumed by the service function chain group matched with the service, and the resource type can comprise computing resources, storage resources, spectrum resources and power resources. The network utility value refers to a quantized value used to evaluate the service capability and economy of the power communication network.
Specifically, the network utility value of the power communication network may be evaluated based on the degree of agreement between the capabilities of the service function chain group of traffic matching in the power communication network and the demands thereof and the service costs required to be consumed to implement these service functions, and the network utility value may be used to evaluate the service capabilities and economics of the power communication network.
According to the technical scheme of the embodiment of the invention, the network evaluation request is generated according to the service requirement of the power communication network, the service function chain meeting the service requirement in the network evaluation request is determined in a logic domain, the first matching degree of the network evaluation request and the service function chain is determined, the service function is mapped to the physical equipment, the second matching degree of each service function chain and the physical equipment is determined, the matching probability of the service function chain and the performance index of the physical equipment in the power communication network is determined based on the obtained first matching degree and the second matching degree, the fitting entropy corresponding to the matching probability is determined, the network utility value of the power communication network is determined based on the fitting entropy and the resource use cost of the service function chain, the problem that the power communication network lacks a perfect evaluation system is solved, the timely evaluation of the network architecture and the resource scheduling system of the power communication network based on the fitting degree of the service and the network is realized, and the accuracy of the network evaluation is improved.
On the basis of the above embodiment, the power communication network includes at least a service domain, a logic domain and a physical domain, the service domain includes a service requirement of at least one service, the service requirement includes a service type, a service data amount, and a service resource requirement, the service resource requirement includes at least a delay requirement, a reliability requirement, and a precision requirement, the logic domain includes at least one service function, attribute information of the service function includes a service function category, a service function resource requirement amount, and a service function performance index, the service function resource requirement amount includes at least a calculation resource requirement amount, a storage resource requirement amount, a spectrum resource requirement amount, and a power resource requirement amount, the service function performance index includes at least a delay, a reliability, and a precision, the physical domain includes at least one physical device, the attribute information of the physical device includes a physical component type, a location information, and a residual resource amount, and the residual resource amount includes at least a calculation resource amount, a storage resource amount, a spectrum resource amount, and a power resource amount.
Specifically, the power communication network may be at least divided into a service domain, a logic domain, and a physical domain, and the service, service functions, and physical devices in the power communication network are separated. The business domain may include business requirements of at least one business, which may include business categories, business data volumes, and business resource requirements, which may include at least latency requirements, reliability requirements, and accuracy requirements. The logical field may include at least one service function, and attribute information of the service function may include a service function class, a service function resource demand amount, and a service function performance index, and exemplary service function classes may include a firewall, a routing forwarding, a gateway, and the like. The service function resource requirements may include at least computing resource requirements, storage resource requirements, spectrum resource requirements, and power resource requirements, and the service function performance metrics may include at least latency, reliability, and accuracy. The physical domain may include at least one physical device, and the attribute information of the physical device may include a physical component type, location information, and a remaining resource amount, which may include at least a computing resource amount, a storage resource amount, a spectrum resource amount, and a power resource amount.
On the basis of the above embodiment, the power communication network evaluation method includes:
For service function chains which are not matched with the physical equipment, mapping the service function chains with other physical equipment in sequence, and determining the fit entropy of the service function chains with the other physical equipment respectively;
Determining the optimal fit entropy in the fit entropies, and judging whether the service function resource demand of all the service functions in the service function chain is smaller than or equal to the residual resource quantity of the target physical equipment corresponding to the optimal fit entropy;
If yes, and the target physical device does not reach the maximum bearing number of the bearing service function chain, mapping the service function chain to the target physical device.
In the embodiment of the invention, the optimal fit entropy can be understood as the fit entropy which is obtained and represents the fit entropy with the highest fit degree between the service function chain and the physical equipment. The target physical device may be understood as a physical device having the highest degree of agreement with the service function chain among other physical devices.
Specifically, the power communication network evaluation method may further include mapping the service function chain with other physical devices in the physical domain in sequence for a service function chain that is not matched with the physical devices, so as to obtain probabilities of mapping service functions in the service function chain to the other physical devices, and determining fitting entropies of the service function chain and the other physical devices respectively. The optimal fitting entropy can be determined from the obtained fitting entropies, and the physical equipment with the highest fitting degree with the service function chain can be obtained. Whether the service function resource demand of all the service functions in the service function chain is smaller than or equal to the residual resource quantity of the target physical equipment corresponding to the optimal fit entropy can be judged, whether the target physical equipment can meet the resources required by the service function chain can be judged, if the target physical equipment can meet the resources, and the target physical equipment does not reach the maximum bearing number of the bearing service function chain, can continue to bear the service function chain, and can map the service function chain to the target physical equipment.
In an embodiment, fig. 2 is a flowchart of another power communication network evaluation method according to the embodiment of the present invention, where, based on the foregoing embodiments, at least one service function chain that satisfies a network evaluation request is determined in a logic domain of a power communication network, a first matching degree of the network evaluation request and the service function chain is determined, service functions included in each service function chain are mapped to physical devices in a physical domain in the power communication network, a second matching degree of each service function chain and the physical devices is determined, a matching probability of performance indexes of the service function chain and the physical devices in the power communication network is determined based on the first matching degree and the second matching degree, and a fitting entropy corresponding to the matching probability is determined, and a process of evaluating a network utility value of the power communication network is further optimized and expanded based on the fitting entropy and a resource usage cost of the service function chain.
As shown in fig. 2, another power communication network evaluation method provided in this embodiment may include:
s210, generating a network evaluation request according to at least one service requirement in a service domain of the power communication network.
S220, extracting all business requirements included in the network evaluation request.
Specifically, all the service requirements included in the obtained network evaluation request may be extracted, and the service requirements may include service requirement types and grades.
S230, determining service functions allocated to each service requirement in a logic domain.
Specifically, service function allocation can be performed on the obtained service requirements in the power communication network logic domain, so that the allocated service functions can meet the corresponding service requirements.
S240, constructing corresponding service functions into service function chains according to each service requirement.
Specifically, the required service functions can be collected for each service requirement, and all corresponding service functions can be constructed into a service function chain to meet each service requirement.
S250, counting the ratio of the number of service functions meeting the service demands to the total number of all the service demands in each service function chain as a first matching degree.
Specifically, the ratio of the number of service functions meeting the service requirements to the total number of all the service requirements in each service function chain can be counted as a first matching degree, so as to obtain the matching degree between the service function chain and the service requirements, and whether the service requirements can be met or not. Further, the service resource requirements that the performance index of the service function at least including the service function is greater than or equal to the service requirements are satisfied, and the time delay, reliability and accuracy index of the exemplary service function are greater than or equal to the service resource requirements of the service requirements, so that the service can be provided for the service.
S260, mapping the service functions of the service function chains to at least one physical device of the physical domain for each service function chain.
Specifically, the service functions in each service function chain can be mapped to at least one physical device in the physical domain, and the corresponding physical device is searched to provide the service functions. Further, the remaining data amount of the physical device is at least greater than the sum of service function resource requirements of the service functions carried by the service function chain, so that the service functions can be provided.
S270, counting the number of matching service functions with the mapped physical devices in the service function chain, and taking the ratio of the number to the total number of the service functions as a second matching degree.
Specifically, the number of matching between the service function and the mapped physical devices can be counted in the service function chain, and the ratio of the number of matching to the total number of the service functions can be used as a second matching degree to determine whether the physical devices in the physical domain can provide the required resource amount for the service function chain, and further, the service function resource requirement amount which can at least include the service function is smaller than or equal to the residual resource amount of the physical devices, so that the service function requirement can be met.
S280, obtaining matching degree mapping relations respectively corresponding to the time delay index, the reliability index and the precision index in the performance index.
Specifically, the matching degree mapping relation corresponding to the time delay index, the reliability index and the precision index in the performance index can be obtained, so as to obtain the matching relation among the corresponding service requirement, the service function and the physical equipment.
S290, determining the matching probability of each service function and the physical equipment in the service function chain by the matching degree mapping relation of the time delay index, the matching degree mapping relation of the reliability index and the matching degree mapping relation of the accuracy index.
Specifically, the obtained first matching degree and second matching degree may be used to determine the matching probability between each service function and the physical device in the service function chain through the matching degree mapping relationship of the time delay index, the matching degree mapping relationship of the reliability index, and the matching degree mapping relationship of the accuracy index, and an exemplary, real method may include weighting operation and setting a calculation equation. Exemplary, the probability of matching the service function with the physical device in the service function chain is as follows:
wherein,Ndelay is the maximum number of classes of delay capability, and Pk is the probability that the class of delay capability service is k.
S2100, determining the sum of the matching probabilities of all service functions of the service function chains with different performance indexes respectively.
Specifically, the sum of the matching probabilities of all the service functions of the service function chain and the physical device, which determine the different performance indexes, may be calculated separately, and the sum of the matching probabilities may include the sum of the matching probabilities of the delay indexes, the sum of the matching probabilities of the reliability indexes, and the sum of the matching probabilities of the accuracy indexes, as an example.
S2110, taking the weighted sum of the matching probabilities of different delay indexes as the fit entropy of the service function chain.
Specifically, a weighted sum of the matching probabilities of different delay indexes can be used as a delay fit entropy of the corresponding service function chain, and an exemplary delay fit entropy expression is as follows:
Wherein Edelay is a delay fit entropy, Ndelay is a maximum class number of delay capability, and Pi is a probability that the service class of delay capability is i.
S2120, respectively counting the sum of resource occupation of service functions of the service function chains on the resource demand of different types of service functions for each service function chain.
Specifically, for each service function chain, the sum of resource occupation of service functions of the service function chain on the resource demand of different types of service functions can be counted, and the resource types can include computing resources, storage resources, spectrum resources and power resources.
S2130, calling a preset resource cost mapping relation to determine the resource use cost corresponding to the sum of the resource occupation of the service function chain.
In the embodiment of the invention, the preset resource cost mapping relation can be the mapping relation between the occupied resources of the service functions in the service function chain set in advance according to different types of resources and the use cost of various types of resources.
Specifically, a preset resource cost mapping relationship may be invoked to determine a resource usage cost corresponding to a sum of occupation of various types of resources of the service function chain, and an exemplary sum of occupation of resources of the service function l is as follows:
cost=Ds(c+r+f+p)
The cost is the sum of the resource occupation of the service function l, the Ds is the data size processed by the service function l, and c, r, f and p are the required computing resource, storage resource, spectrum resource and power resource of the service function l respectively.
S2140, for each service function chain, determining the resource use cost and the network utility value corresponding to the fitting entropy of the service function chain by calling a preset network benefit mapping relation.
In the embodiment of the invention, the preset network benefit mapping relation can be understood as a mapping relation between the resource use cost, the fit entropy and the network utility value which are set in advance based on the characteristics of the power communication network.
Specifically, for each service function chain, a preset network benefit mapping relationship may be invoked to determine a resource usage cost of the service function chain and a network utility value corresponding to a fitting entropy, where the smaller the fitting entropy is, the smaller the resource usage cost is, the larger the network utility value is, and the larger the fitting entropy is, the larger the resource usage cost is, the smaller the network utility value is, and the exemplary network utility value is as follows:
Wherein E is the fit entropy, cost is the resource use cost, and χ1,χ2,χ3 is the normal number.
And S2150, taking the sum of the network utility values of all service function chains as the network benefit value of the power communication network.
Specifically, the sum of the network utility values of all the service function chains can be used as the network benefit value of the power communication network to evaluate the fit degree of the power communication network and the business and the economical efficiency of the power communication network.
According to the technical scheme of the embodiment of the invention, a network evaluation request is generated through service requirements, all service requirements in the network evaluation request are extracted, service functions are distributed in a logic domain according to the service requirements, a service function chain is constructed, a first matching degree is obtained according to the ratio of the number of the service functions to the total number of the service requirements, the service functions of the service function chain are respectively mapped to physical equipment, the number of the matching of the service functions of the service function chain and the mapped physical equipment is counted to obtain a second matching degree, the matching probability of each service function and the physical equipment in the service function chain is determined through the matching degree mapping relation of time delay indexes, the matching degree mapping relation of reliability indexes and the matching degree mapping relation of accuracy indexes, the fit entropy of all the service functions of the service function chain with different performance indexes is determined, the resource occupation sum of the service function chain resource demand is calculated, the network utility value corresponding to the service function chain is determined, the network benefit value of the power communication network is obtained, the problem of a complete evaluation system of the power communication network is solved, and the accuracy of the network evaluation system of the power communication network on the basis of the service and the accuracy of the communication network is improved.
In an embodiment, fig. 3 is a flowchart of another power communication network evaluation method according to an embodiment of the present invention, and based on the foregoing embodiments, the embodiment is taken as a preferred embodiment, and a process for establishing a three-domain model of a power communication network, a process for matching services with the three-domain model, and a process for evaluating the power communication network by calculating a utility value of the network are specifically described.
As shown in fig. 3, another power communication network evaluation method provided in this embodiment may include:
and S310, providing a three-domain model of the power communication network, dividing the power communication network into a service domain, a logic domain and a physical domain, and modeling each domain.
In particular, a three-domain model may be proposed based on the power communication network, which divides the network into a traffic domain, a logical domain and a physical domain. Fig. 4 is a three-domain model diagram of an electric power communication network, provided by the embodiment of the invention, including a service domain, a logic domain and a physical domain, where, as shown in fig. 4, the physical domain is an abstract modeling of a physical device that provides basic resources and running network functions in a novel electric power communication network. The logic domain is a service function set formed by logically dividing the existing power grid physical network, and then abstracting out the functions of different physical components to split or combine. The business domain is a model of various business abstractions generated for diversified scenes in a novel power communication network. Illustratively, the service domain may be defined as:
S={s1,s2,...,sk,...}
wherein sk is the kth service (k is more than or equal to 1 and less than or equal to Ns),To describe the specific requirements of this service,Representing the type of service k, dsk represents the data size of service k, Rk represents the type and class description of service k requirements, which may mainly take into account latency, accuracy and reliability. The correlation correspondence table is as follows:
table 1 business demand and demand level correspondence table
Table 2 service demand level table
The logical field may be defined as:
L={l1,l2,...lk,...}
wherein, lk is the kth service function,To describe specific attributes of this service function, wherein,A class representing a service function lk, such as firewall, routing forwarding, gateway, etc.; Representing the amount of resources consumed by the service function lk to process a unit flow, including in particular calculating the amount of resourcesStorage resource amountSpectrum resource amountAmount of power resourcesRepresented asPerformance index for representing service function/k processing unit flow, specifically including time delayReliability ofPrecision ofRepresented as
The physical domain may be defined as:
W={w1,w2,...wk,...}
wherein wk is the kth physical device,To describe specific properties of this physical device, whereinRepresenting the physical device type of entity wk, such as access network devices, transport network devices, and core network devices, resk representing the location information of entity wk,Representing the amount of resources available to the entity wk, including in particular the amount of computational resourcesStorage resource amountSpectrum resource amountAmount of power resourcesRepresented as
S320, modeling the service execution flow as a three-layer matching process based on the established three-domain model.
Specifically, the service execution flow in the power communication network can be regarded as a three-layer matching process, fig. 5 is a three-domain matching schematic diagram provided by the embodiment of the present invention, and the service execution process is regarded as a matching process with a three-domain model, as shown in fig. 5, firstly, a network evaluation request can be formed according to the service requirement in the service domain, and one or more service function chains meeting the requirement can be found in the logic domain according to all service function types in the request. And then matching and mapping the service functions in the service function chain with the physical devices in the physical domain under the condition of meeting the resource requirement, wherein the service functions are formed by splitting and combining the functions abstracted by the physical devices, so that a single physical device can correspond to a plurality of service functions, and the single service function can be matched with a plurality of physical devices.
In one embodiment, after S320, the method further includes:
defining a mapping probability matrix from a business domain to a logic domain service function chain;
A mapping probability matrix of logical domain to physical domain is defined.
Specifically, a mapping probability matrix of a business domain to a logical domain service function chain can be definedThe matrix size NS×NSFC is as follows:
wherein NSFC represents the number of service function chains, matrix elementsThe probability pij that the service si maps to the service function chain SFCj is represented.
The service function chain group SFCGi matching the service si can be expressed as a set of service function chains SFCj in the logical domain mapped with the existence probability of the service si, i.e
The relation between service function chains and service functions in the logic domain passes through the incidence matrixAnd (3) representing. The mapping probability matrix RS→L of the service functions of the service domain and the logical domain can be passed throughIs a line normalized representation of (c).
A logical domain to physical domain mapping probability matrix RL→W, a matrix size NL×NW, may be defined as follows:
wherein the elements areRepresenting the probability pjk that the service function lj maps to the physical component wk.
S330, defining a fitting entropy according to the characteristics of the service in the power communication network to evaluate the fitting degree of the power network and the service requirement.
Specifically, according to the characteristics of the service in the power communication network, the fit entropy can be defined to evaluate the fit degree of the power network and the service requirement. Can be described according to the time delay requirement, the reliability requirement and the precision requirement of the service sk＝{sourcek,Dsk,RkThe service functions in the logic domain form a service function chain according to the service requirements, and the service function chain meeting the service requirements is not unique because of the performance diversity of the single service function, and the service function chain meeting the service requirements is set as a set and is called a service function chain group. Exemplary, one of the service function chains isWherein Ni,k is the number of service functions in the ith service function chain matched with the service sk, and defines the service function chainTime delay service class of (v)Fdelay is the mapping of the delay level of the value, and the reliability service level can be defined by the samePrecision class of serviceExemplary, the service function chain matching the service sk has Nk pieces, defining matching probability groupsIndicating the probability of matching each service function chain. Because the matched service function chain has uncertainty, the provided service level is also uncertain, and taking delay capability as an example, the capability probability set of the service function chain group matched with the service can be expressed as:
wherein,Ndelay is the maximum class number of the time delay capability, Pk is the probability that the service class of the time delay capability is k, and the capability class of each service function chain in the service function chain group is expected according to the matching probability.
The same can be said to specifically represent reliability and accuracy capabilities. Meanwhile, defining a fit entropy to measure the fit degree between the service capability provided by the service function chain group and the service capability required by the service, denoted as E, wherein the fit entropy is divided into a plurality of parts due to the multidimensional property of the service capability, if the delay statistics requirement of the service is thatThe expression defining the delay fit entropy is:
Wherein Edelay is a delay fit entropy, Ndelay is a maximum class number of delay capability, and Pk is a probability that the service class of delay capability is k.
The same can define the expression of reliable fit entropy Erel and precision fit entropy Eprec. The fitting entropy consists of a weighted sum of the parts, expressed as
E=λdelayEdelay+λrelErel+λprecEprec
Wherein lambdadelay,λrel and lambdaprec are weighting coefficients of delay fit entropy Edelay, reliable fit entropy Erel and precision fit entropy Eprec.
S340, defining a network utility value to comprehensively evaluate the capacity and the economical efficiency of the power network based on the fit entropy.
Specifically, the network utility value may be defined based on the obtained fitting entropy to comprehensively evaluate the capability and the economical efficiency of the power network. The network utility value depends on the degree of agreement between the capabilities of the service function chain groups matched by the traffic in the network and the demands thereof and the service cost required to be consumed for realizing the service functions, and the degree of agreement between the traffic and the service function chain groups matched by the traffic is expressed by the entropy of agreement, and the service cost and the expression of the network utility value are introduced next.
The service cost refers to the sum of resources to be consumed by service function chain groups matched with the service, the resource types are divided into computing resources, storage resources, spectrum resources and power resources, taking service function l as an example, the service function l is used with the cost related to the data volume Ds processed by the service function l and the use cost of various types of resources of the service function, and is defined as
cost=Ds(c+r+f+p)
The cost is the sum of the resource occupation of the service function l, the Ds is the data size processed by the service function l, and c, r, f and p are the required computing resource, storage resource, spectrum resource and power resource of the service function l respectively.
The utility of the power system is related to the business service cost and the fit entropy E, the smaller the E value is, the smaller the cost value is, the larger the value of the system utility value U is, the larger the E value is, the larger the cost value is, and the smaller the value of the system utility value U is. From the above properties, a special form of the network utility function can be deduced
Wherein E is the fit entropy, cost is the resource use cost, and χ1,χ2,χ3 is the normal number.
According to the technical scheme of the embodiment of the invention, the three-domain model of the power communication network is established, the service execution flow is modeled as a three-layer matching process, the fitting entropy is defined to evaluate the fitting degree of the power network and the service demand according to the characteristics of the service in the power communication network, the network efficiency is defined to comprehensively evaluate the capacity and the economical efficiency of the novel power network based on the obtained fitting entropy, the problem that the power communication network lacks a perfect evaluation system is solved, the network architecture and the resource scheduling system of the power communication network are evaluated in time based on the fitting degree of the service and the network, and the accuracy of network evaluation is improved.
On the basis of the above embodiment, the power communication network evaluation method further includes:
Based on the defined fitting entropy, the optimization problem of the power communication network is proposed, and an optimization matching algorithm of the business-service function chain-physical equipment based on the fitting entropy is proposed.
Specifically, the fit entropy and economy of the novel power network and all services in the network can be optimized, and the following optimization problem is formed:
C7:SevL(k)≥Ri(k),SevL∈SFCGi,1≤k≤3
Wherein NY represents the number of services in the service domain, NL represents the number of service functions in the logical domain, NW represents the number of physical devices in the physical domain, Ei represents the entropy of the service function chain to which the service i matches; represents the maximum amount of computing resources that can be provided by the physical component k, and similarly,Indicating the maximum amount of storage resources,Indicating the maximum amount of frequency resources,Representing the maximum amount of power resources, sevL (k) represents the k-th dimension capability level of the service function chain, Ri (k) represents the k-th dimension requirement of traffic si, and SFCGi represents the set of service function chains that traffic si matches. Constraint C1, C2, C3 and C4 respectively represent that the computing resource, the storage resource, the frequency resource and the power resource required by the service function chain cannot exceed the maximum value of the mapped physical equipment, C5 and C6 represent normalization limitation of mapping probability, and C7 represents that the service level of the matched service function chain is larger than the service requirement level of the service.
Matching algorithm based on fitting entropy optimization is shown in the following table:
In an embodiment, fig. 6 is a schematic structural diagram of an electric power communication network evaluation device according to an embodiment of the invention. The present embodiment can perform the above-described implementation. The embodiment can be suitable for the situation of timely evaluating the network architecture and the resource scheduling system of the novel power communication network, and the device can be realized in a hardware/software mode and can be configured in electronic equipment.
As shown in fig. 6, the power communication network evaluation apparatus provided in the present embodiment includes a request acquisition module 401, a request matching module 402, a service chain module 403, a fitting entropy module 404, and a network evaluation module 405, wherein:
A request acquisition module 401, configured to generate a network evaluation request according to at least one service requirement in a service domain of the power communication network;
A request matching module 402, configured to determine at least one service function chain that satisfies the network evaluation request in a logic domain of the power communication network, and determine a first matching degree between the network evaluation request and the service function chain;
a service chain module 403, configured to map service functions included in each service function chain to physical devices in a physical domain in the power communication network, and determine a second matching degree between each service function chain and the physical devices;
the fitting entropy module 404 is configured to determine a matching probability of the performance index of the physical device and the service function chain in the power communication network based on the first matching degree and the second matching degree, and determine a fitting entropy corresponding to the matching probability;
A network evaluation module 405 for determining a network utility value for evaluating the power communication network based on the fit entropy and the resource usage cost of the service function chain.
According to the technical scheme of the embodiment of the invention, the network evaluation request is generated according to the service requirement of the power communication network, the service function chain meeting the service requirement in the network evaluation request is determined in a logic domain, the first matching degree of the network evaluation request and the service function chain is determined, the service function is mapped to the physical equipment, the second matching degree of each service function chain and the physical equipment is determined, the matching probability of the service function chain and the performance index of the physical equipment in the power communication network is determined based on the obtained first matching degree and the second matching degree, the fitting entropy corresponding to the matching probability is determined, the network utility value of the power communication network is determined based on the fitting entropy and the resource use cost of the service function chain, the problem that the power communication network lacks a perfect evaluation system is solved, the timely evaluation of the network architecture and the resource scheduling system of the power communication network based on the fitting degree of the service and the network is realized, and the accuracy of the network evaluation is improved.
On the basis of the above embodiment, the power communication network includes at least a service domain, a logic domain and a physical domain, the service domain includes a service requirement of at least one service, the service requirement includes a service type, a service data amount, and a service resource requirement, the service resource requirement includes at least a delay requirement, a reliability requirement, and a precision requirement, the logic domain includes at least one service function, attribute information of the service function includes a service function category, a service function resource requirement amount, and a service function performance index, the service function resource requirement amount includes at least a calculation resource requirement amount, a storage resource requirement amount, a spectrum resource requirement amount, and a power resource requirement amount, the service function performance index includes at least a delay, a reliability, and a precision, the physical domain includes at least one physical device, the attribute information of the physical device includes a physical component type, a location information, and a residual resource amount, and the residual resource amount includes at least a calculation resource amount, a storage resource amount, a spectrum resource amount, and a power resource amount.
Based on the above embodiment, the request matching module 402 includes:
And the demand extraction unit is used for extracting all the service demands included in the network evaluation request.
And the function determining unit is used for determining the service functions allocated to each service requirement in the logic domain.
And the function chain construction unit is used for constructing corresponding service functions into service function chains aiming at each service requirement.
And the first matching degree determining unit is used for counting the ratio of the number of service functions meeting the service requirements to the total number of all the service requirements in each service function chain as a first matching degree, wherein the service resource requirements meeting the service function performance index at least comprising the service functions are larger than or equal to the service requirements.
Based on the above embodiment, the service chain module 403 includes:
And the function mapping unit is used for mapping the service functions of the service function chains to at least one physical device of the physical domain for each service function chain, wherein the residual data quantity of the physical device is at least larger than the sum of the service function resource demands of the carried service functions.
And the second matching degree determining unit is used for counting the number of matching service functions with the mapped physical devices in the service function chain, and taking the ratio of the number to the total number of the service functions as the second matching degree, wherein the matching at least comprises that the service function resource demand of the service functions is smaller than or equal to the residual resource quantity of the physical devices.
On the basis of the above embodiment, the fitting entropy module 404 includes:
The mapping relation acquisition unit is used for acquiring the matching degree mapping relation respectively corresponding to the time delay index, the reliability index and the precision index in the performance index.
And the matching probability determining unit is used for determining the matching probability of each service function and the physical equipment in the service function chain through the matching degree mapping relation of the time delay index, the matching degree mapping relation of the reliability index and the matching degree mapping relation of the accuracy index respectively.
And the probability sum determining unit is used for determining the sum of the matching probabilities of all the service functions of the service function chains with different performance indexes respectively.
And the fitting entropy determining unit is used for taking the weighted sum of the matching probabilities of different time delay indexes as the fitting entropy of the service function chain.
Based on the above embodiment, the network evaluation module 405 includes:
the resource occupation sum determining unit is used for respectively counting the resource occupation sum of the service functions of the service function chains on the resource demand of the service functions of different types for each service function chain.
The resource use cost determining unit is used for calling a preset resource cost mapping relation to determine the resource use cost corresponding to the sum of the resource occupation of the service function chain.
The network utility value determining unit is used for determining the network utility value corresponding to the resource use cost and the fitting entropy of the service function chains by calling the preset network benefit mapping relation for each service function chain.
And the network benefit value determining unit is used for taking the sum of the network utility values of all the service function chains as the network benefit value of the power communication network.
On the basis of the above embodiment, the power communication network evaluation apparatus further includes:
and the agreeing entropy determining module is used for mapping the service function chains with other physical devices in sequence aiming at the service function chains which are not matched with the physical devices, and determining agreeing entropy of the service function chains with the other physical devices respectively.
The resource quantity judging module is used for determining the optimal fit entropy in the fit entropies and judging whether the service function resource demand quantity of all the service functions in the service function chain is smaller than or equal to the residual resource quantity of the target physical equipment corresponding to the optimal fit entropy.
And the mapping module is used for mapping the service function chain to the target physical equipment if the service function chain is not loaded and the target physical equipment does not reach the maximum load number for loading the service function chain.
The power communication network evaluation device provided by the embodiment of the invention can execute any power communication network evaluation method provided by the embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method. Reference is made to the description of any method embodiment of the invention for details not described in this embodiment.
In an embodiment, fig. 7 is a schematic structural diagram of an electronic device for implementing the parking space prediction method according to the embodiment of the present invention. Electronic device 50, which may be used to implement embodiments of the present invention, is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 7, the electronic device 50 includes at least one processor 51, and a memory such as a Read Only Memory (ROM) 52, a Random Access Memory (RAM) 53, etc. communicatively connected to the at least one processor 51, wherein the memory stores a computer program executable by the at least one processor, and the processor 51 may perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM) 52 or the computer program loaded from the storage unit 58 into the Random Access Memory (RAM) 53. In the RAM 53, various programs and data required for the operation of the electronic device 50 can also be stored. The processor 51, RAM 52 and RAM 53 are connected to each other by a bus 54. An input/output (I/O) interface 55 is also connected to bus 54.
Various components in the electronic device 50 are connected to the I/O interface 55, including an input unit 56 such as a keyboard, mouse, etc., an output unit 57 such as various types of displays, speakers, etc., a storage unit 58 such as a magnetic disk, optical disk, etc., and a communication unit 59 such as a network card, modem, wireless communication transceiver, etc. The communication unit 59 allows the electronic device 50 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunications networks.
The processor 51 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 51 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 51 performs the various methods and processes described above, such as the power communication network assessment method.
In some embodiments, the power communication network assessment method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 58. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 50 via the ROM 52 and/or the communication unit 59. When the computer program is loaded into RAM 53 and executed by processor 51, one or more steps of the power communication network assessment method described above may be performed. Alternatively, in other embodiments, the processor 51 may be configured to perform the power communication network assessment method by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include being implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be a special or general purpose programmable processor, operable to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user, for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback), and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a Local Area Network (LAN), a Wide Area Network (WAN), a blockchain network, and the Internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.