CN115314355A - Electric power communication network architecture system and method based on deterministic network - Google Patents
Electric power communication network architecture system and method based on deterministic network Download PDFInfo
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Abstract
The invention provides a power communication network architecture system based on a deterministic network, which comprises a control layer, an infrastructure layer and a knowledge layer; a control layer, which is used for fitting services and strategies, and adopts a knowledge-based scheduling mechanism according to the service requirements of users to form a determined route and resource strategy which meet the requirements of specific service quality and network behavior characteristics, so as to realize decision adaptation of the route and the scheduling; the infrastructure layer is used for matching strategies and resources, consists of a series of TSN network devices, and is used for mapping the routing and scheduling functions into refined network resource combinations to realize data forwarding; and the knowledge layer is used for fitting resources with knowledge, is in communication connection with the infrastructure layer and the control layer, is responsible for collecting and storing the network resources of the infrastructure layer in real time, realizes a dynamic allocation strategy of the network resources by learning a resource allocation strategy of the control layer, and timely feeds back the learned scheduling strategy to the control layer.
Description
Technical Field
The invention relates to the technical field of network communication, in particular to a power communication network architecture system and a power communication network architecture method based on a deterministic network.
Background
The power communication network is used as an important support and guarantee of a power grid and is an important basis for realizing intellectualization and interaction of the power grid and operation control of a large power grid. With the continuous and deep development and promotion of smart power grids and ubiquitous power internet of things, new technologies such as 5G communication, ICT infrastructure and holographic communication are emerging, so that more and more new services are accessed to a network, and power communication services are developing to large-bandwidth low-delay services such as videos, multimedia and precise loads, and new requirements and challenges are brought to a power communication network. Because the traditional power communication network architecture adopts a best-effort design mode, the switching mode is single, the transmission delay of a data packet in the network is difficult to determine, and the network controllability is weak. Therefore, the current power system urgently needs to introduce new technology and architecture to provide deterministic and low-latency differentiated services.
A Deterministic Network (DetNet) is a Network that is recently proposed to guarantee Deterministic bandwidth, delay, jitter, and packet loss rate. The bottom layer of the system guarantees the real-time performance and the time delay certainty of data transmission through the Ethernet TSN technology and methods such as resource reservation, route display, redundant transmission and the like on the premise of guaranteeing the accurate synchronization of time. The deterministic network system model has the characteristics of punctuality, reliability and large scale, is deeply fused with the existing power communication network architecture, and is considered as a key technical platform for power grid perception, calculation and analysis capability. The method can match core requirements of power grid industry on service manageability, controllability and differentiation processing, provides a brand new technical selection of ubiquitous, flexible, efficient and stable end-to-end data transmission service for the power access network and the core network, and improves network architecture supporting force.
Therefore, the invention provides a three-layer model of the power communication network fusing the deterministic network technology from the basic concept of the deterministic network. The role of each layer is elaborated from the aspect of architectural functional design. In order to obtain the real-time network state and autonomously make an optimal decision, the cooperative work of a management control module of a control layer and a management module of a knowledge layer is mainly analyzed, and finally, a real-time information feedback system of a deterministic network is realized.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to solve the technical problem of how to effectively reduce the end-to-end time delay of data transmission of an electric power communication network, and provides an electric power communication network architecture and a method based on a deterministic network. Due to the particularity of the deterministic network, the network performance analysis of the deterministic network under different application scenarios is crucial. The core idea of a Software Defined Network (SDN) is to separate control and forwarding, and achieve programmability and simplicity of operation of management and control. It has been widely used in power communication networks and smart grids. Therefore, based on the concept of SDN control forwarding separation, a three-layer deterministic network architecture similar to the SDN is constructed. Wherein the control layer is completely separated from the technical facility layer, and the knowledge layer can communicate with the two layers to feed back information in time.
The technical scheme is as follows: the invention provides a power communication network architecture system based on a deterministic network for solving the technical problems, which comprises a control layer, an infrastructure layer and a knowledge layer;
a control layer, which is used for fitting services and strategies, and adopts a knowledge-based scheduling mechanism according to the service requirements of users to form a determined route and resource strategy which meet the requirements of specific service quality and network behavior characteristics, so as to realize decision adaptation of the route and the scheduling;
the infrastructure layer is used for matching strategies and resources, consists of a series of TSN network devices, and is used for mapping the routing and scheduling functions into refined network resource combinations to realize data forwarding;
and the knowledge layer is used for fitting resources with knowledge, is in communication connection with the infrastructure layer and the control layer, is responsible for collecting and storing the network resources of the infrastructure layer in real time, realizes a dynamic allocation strategy of the network resources by learning a resource allocation strategy of the control layer, and timely feeds back the learned scheduling strategy to the control layer.
Furthermore, the control layer is responsible for realizing routing and scheduling functions, bearing services upwards, and controlling the data layer downwards, and comprises a data analysis module, a resource management module and a path calculation module, and adopts a knowledge-based scheduling mechanism, and the method comprises the following steps: the data analysis module carries out abstract modeling on the user service request to realize the mapping from the service index to the service model; the path calculation module calculates a deterministic path of the service according to the service model and the routing algorithm; the resource management module adopts different scheduling algorithms according to the feedback information of the service type path and the knowledge layer to realize the resource allocation among the nodes;
the service requirement in the data analysis module includes a service basic parameter B and a network benefit R, and the basic parameter is defined as a quintuple B = (s, d, l, t) max R), s is the source node, d is the destination node, l is the data stream length, t max To maximum end-to-end delayR is the allocation rate; the network benefit is defined as
Where v is the traffic class, c p For operator revenue, c s The standard grade gain is obtained, delta is time delay, lambda is jitter, and epsilon is packet loss rate; if the total number of the services requested by the user is m, the basic parameters and the network benefits which need to be processed by the analysis module are respectively (B) 1 ,B 2 ,...,B m) and (R1 ,R 2 ,...,R m ) In summary, the business requirement model I is expressed as:
the service model S refers to a service performance index and a necessary service function requirement, wherein the performance index is defined as Q = (t, delta, lambda and epsilon), wherein t is a throughput rate, delta is a time delay, lambda is a jitter rate, and epsilon is a packet loss rate; the service function requirements F include: network function F N Functional dependency relationship F Q And network function dependent resource type F R I.e. F = (F) N ,F Q ,F R ) (ii) a When the number of service requests is m, the service model is expressed as follows:
wherein ,Qi And F i And respectively representing the performance index of the ith service and the corresponding service function requirement, i belongs to (1, m).
The routing addressing function in the path computation module combines the service requirement matrix S defined above with the routing algorithm through the mapping function
Mapping to obtain a service path, wherein a routing algorithm Rt refers to a shortest path algorithm or a K shortest path algorithm,
the mapping function is used for selecting all possible transmission paths for the service according to the service performance requirement, and the process of converting the service requirement into the service path by the control layer is expressed as follows:
after the service path is established, data transmission is carried out, and if the application requirement cannot be met or the constraint condition of route adjustment cannot be met, path calculation is carried out again;
when the service path meets the condition, the resource management module reasonably distributes resources by adopting a scheduling algorithm based on a Circular Queue Forwarding (CQF) mechanism or asynchronous shaping ATS (automatic traffic Forwarding) according to the path P and the feedback information of the knowledge layer, so that the service end-to-end delay is minimized and the network resource utilization is maximized.
Further, the infrastructure layer is located at the lowest layer of the whole architecture and includes a deterministic forwarding device and a deterministic processing device, the deterministic forwarding device has no routing function and only forwards data; the deterministic processing device not only has data forwarding capability, but also has a processing function of implementing data by programming, specifically:
the infrastructure layer functions are implemented by node state information, service capabilities and function instances, where N is defined as all physical nodes N in the network i I is the number of physical nodes; the state information of the node is defined as F = (N) l ,N s ,N d ,N im ) Element components in the state information respectively represent node positions, node types, node connectivity and node importance; service capability is defined as C = (C) c ,C h ,C t ) Including computing power C c Buffer capacity C h And transmission ability C t Wherein each class of service capability is specifically divided by a subscript j; function example E = (E) c ,E h ,E t ) Resource service capability of the corresponding node, wherein E c To compute function instances, E h For example of a caching function, E t For the transmission of a function instance, i.e. a service instance of node n on the jth class capability of a transmission resource instance E, is defined as E, where
Respectively representing the service instances of the node on the ith class of capabilities of the compute, cache and transmit functions, i e (1, j). Based on the above definitions, the resource instantiation result of the physical node on which the kth service node depends on the service path P is:
the mapping from the service path to the data layer service instance resource combination is therefore represented as:
wherein ,
a mapping function is represented which converts the nodes traversed by the path P into refined resource instances according to the service capabilities C and the service instances F. d is a radical of i The resource instantiation result, i ∈ (1, k), of the ith service node is represented.
Furthermore, the knowledge layer is communicated with the infrastructure layer and the control layer through a programmable interface and comprises an enhanced knowledge management module and a state management information base; the state management information base stores a service resource combination example for real-time updating of equipment states, the enhanced knowledge management module records a scheduling strategy of a control layer, learns scheduling algorithms with different service requirements by combining a machine learning algorithm, and predicts an optimal scheduling strategy of a data stream according to the learned knowledge, wherein the knowledge is defined as K = (lh, br, D) max ,D T ,C l ) Lh is the data flow length, data burst rate br, maximum end-to-end delay D max Flow cutoff time D T And link capability C l 。
Further, the control layer and the knowledge layer cooperate to realize a timely and accurate feedback mechanism, which includes: when the control layer performs data stream scheduling, the control layer firstly analyzes the data stream to obtain the performance requirements of the data stream, including tolerable maximum time delay, data packet length and data burst rate; then, mapping the route and the service according to the analyzed performance model of the data stream to obtain a deterministic service path; secondly, the control layer requests the existing scheduling knowledge including synchronous scheduling or asynchronous scheduling from the knowledge layer, and selects a corresponding scheduling strategy according to the underlying network resource state recorded by the information state database; meanwhile, the knowledge layer carries out intelligent learning decision according to the existing scheduling algorithm and traffic characteristics, the learned knowledge is used for predicting the scheduling strategy of the subsequent traffic, and finally, the routing and scheduling strategy is issued to the infrastructure layer for corresponding forwarding and processing.
Furthermore, the knowledge management module and the equipment information state database of the knowledge layer collect and update the running state information of the bottom layer forwarding equipment, and autonomously send state update information to the management module when the running state of the bottom layer forwarding equipment changes; the enhanced knowledge management module periodically sends state maintenance information to the bottom forwarding equipment to prevent the communication with the knowledge layer independently when a fault occurs, and the control layer directly accesses the information state database to obtain real-time network equipment running state information when carrying out data flow scheduling distribution, so that an appropriate strategy is selected to carry out optimal distribution according to service requirements; the enhancement management module excavates and learns the algorithm of knowledge according to the demand of the control layer, and sends corresponding knowledge to the control layer, thereby realizing intelligent management and decision.
The invention also provides a power communication network resource scheduling method realized by the power communication network architecture system based on the deterministic network, which comprises the following steps:
step 1, aiming at a deterministic service of a power grid, a control layer obtains a performance requirement of the service through a data analysis module and maps the performance requirement into a service function model S;
step 2, transmitting the service function model to a routing control module, and combining a routing algorithm to realize a deterministic transmission path;
step 3, the resource management module obtains resource strategy related knowledge from the knowledge layer, and invokes a scheduling algorithm to allocate resources by combining the transmission path P;
step 4, according to the equipment state information recorded by the state information base of the knowledge layer, if the service resource combination meets the routing constraint and the service performance requirement, the scheduling happens at the moment, the control layer determines a path allocation resource to the bottom layer, completes the execution of a buffer mechanism, a queue scheduling mechanism and a path selection mechanism of the deterministic requirement, and transfers an allocation command to the infrastructure layer; if the scheduling condition is not met, performing scheduling calculation and strategy learning again;
step 5, the infrastructure layer receives the dispatching command of the control layer and transmits the service data packet; and after the data stream transmission is finished, updating the network state and storing the state information in a state information base of the knowledge layer.
Has the advantages that: compared with the prior art, the technical scheme adopted by the invention has the following beneficial technical effects:
the invention discloses a novel electric power communication network architecture and a method based on a deterministic network, which adopt the deterministic network architecture based on the SDN, are fused with the existing electric power network architecture, and realize the requirements of low time delay, high reliability and the like of synchronous transmission and dispatching automation among substations by setting a professional level and applying core technologies such as clock synchronization, route display and the like.
The novel electric power communication network architecture and method based on the deterministic network support reasonable coexistence of multi-deterministic service and common service by taking deterministic transmission as a core, provide efficient and convenient management through an efficient queue management mechanism and an information feedback mechanism, realize deterministic service guarantee and simultaneously inherit the traditional advantages of optical transmission.
The novel electric power communication network architecture and the method based on the deterministic network have the characteristics of low cost and multiplexing of the Ethernet, and overcome the defects that the traditional electric power architecture has poor expandability and cannot effectively support time-sensitive services and burst services. The deterministic network architecture is used for an electric power comprehensive networking scene and provides resources and deterministic service guarantees for business decisions.
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FIG. 1 is a schematic diagram of a deterministic network-based power communications network architecture of an embodiment of the present invention;
FIG. 2 is a flow chart of a deterministic network-based power communications network communication method of an embodiment of the present invention;
FIG. 3 is a schematic diagram of an information feedback mechanism based on a deterministic network according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a deterministic network-based management function according to an embodiment of the present invention.
Detailed Description
The technical scheme of the invention is further explained in detail by combining the attached drawings:
in the era of rapid increase of data flow, the existing internet often has the problems of data congestion, high packet loss rate, no guarantee of time delay and the like. The deterministic service function provided by the deterministic network can ensure that data transmission with special requirements can meet the requirements of extremely low time delay, zero packet loss and high reliable service quality in any network environment. Based on a deterministic network architecture, the method is fused with the existing communication network architecture, and provides a solution for data transmission of the power communication network.
The electric power communication network architecture based on the deterministic network according to the embodiment of the present invention, as shown in fig. 1, includes: an infrastructure layer, a control layer, and a knowledge layer.
Specifically, the infrastructure layer is composed of a series of TSN network devices, and is connected to the control layer in communication, for determining and forwarding data. And the control layer consists of a plurality of controllers, logically forms a central controller, is in communication connection with the infrastructure layer and is responsible for controlling and managing the bottom-layer equipment. And the knowledge layer is in communication connection with the infrastructure layer and the control layer and is responsible for collecting and storing the network resources of the infrastructure layer in real time, realizing a dynamic allocation strategy of the network resources by learning a resource allocation strategy of the control layer and timely feeding back the learned scheduling strategy to the control layer.
The infrastructure layer and the control layer realize control and forwarding separation, and the knowledge layer is communicated with the infrastructure layer and the control layer to form a dynamic real-time feedback mechanism so as to determine a determined transmission path of the data stream and reasonably allocate resources.
According to some embodiments of the invention, as shown in fig. 1, the infrastructure layer contains two classes of deterministic network nodes, deterministic edge nodes and deterministic forwarding nodes. Deterministic edge nodes can serve as the starting or ending point of a deterministic flow, with their primary functions including add or delete packet ordering, packet replication, and combining. The deterministic forwarding node only implements a DetNet forwarding sublayer, is responsible for routing the message from the source to the destination, and is dedicated to determining the data forwarding of the network. When receiving control information of the control layer, the data forwarding of the service is realized, and meanwhile, the self state information is provided for the control layer, so that the real-time update of the control layer to the network topology is ensured. It also provides node state and resource use information to control and knowledge plane, and real-time updates own running state information for control layer to better perform resource allocation and routing. Specifically, the infrastructure layer functions to implement a refined resource service combination of routing and resource allocation policies, and instantiates nodes mainly by using three attributes of node state information, service capability and function instances. The node state information is defined as a set of node positions, node types, node connectivity and node importance; service capabilities include computing capability C c Buffer capacity C h And transmission capacity C t (ii) a The resource service capability of the corresponding node of the function instance; the above attributes are passed through a mapping function
And instantiating the resources of the physical nodes to obtain a service instance resource combination for the knowledge layer to access and store.
According to some embodiments of the present invention, as shown in FIG. 1, the control layer is made up of a plurality of controllers, effectively forming a centralized logical controller. Each controller consists of a plurality of control modules, and comprises a resource management module, a path calculation module, a flow scheduling module and a data analysis module, all the modules work cooperatively to control and manage the underlying equipment, and the network state can be obtained and the corresponding knowledge algorithm can be called in time through interaction with a knowledge plane.
Specifically, the data analysis module carries out abstract modeling on the user service request to realize the mapping from the service index to the service model; the path calculation module calculates a deterministic path of the service according to the service model and a routing algorithm, such as a shortest path algorithm; meanwhile, the resource management module adopts a scheduling algorithm according to the feedback information of the service type path and the knowledge layer to realize resource allocation among the nodes.
The scheduling algorithm adopted in the present invention can be divided into two modes, namely synchronous scheduling and asynchronous scheduling. The method is characterized in that a synchronous scheduling algorithm is adopted on the basis of a cyclic forwarding queue or a cyclic forwarding queue specified by a cycle, and the network adopts a clock synchronization protocol and a frame preemption mechanism of a TSN time sensitive network, so that the quick transmission of the time delay sensitive stream is realized, and the extremely low packet loss rate is ensured. And the asynchronous scheduling algorithm adopts an asynchronous traffic shaper ATS which is based on an urgent class scheduler (UBS) to realize deterministic transmission of each flow. Its advantages are no need of strict clock synchronization, high expandability and full use of network bandwidth.
According to some embodiments of the invention, as shown in fig. 1, the knowledge layer consists of an enhanced knowledge management module and a device information state database, which is responsible for collecting and storing network state information, such as the state of flows flowing through each network node. Meanwhile, the existing scheduling algorithm is mined and learned according to the requirements of the control plane, and the network state information and the intelligent learning algorithm can be sent to the control plane according to the requirements of the control plane.
The enhanced knowledge management module is composed of a plurality of devices, each device manages a region and is mainly responsible for communicating with the forwarding nodes of the infrastructure layer and collecting and updating the running state information of the forwarding devices of the bottom layer, such as link transmission delay, residual cache space, available bandwidth, forwarding delay of end devices and the like. And aggregating the collected information into an equipment information status database. And sending state updating information to the management module of the lower layer forwarding equipment independently whenever the running state of the lower layer forwarding equipment changes. In addition, the enhanced knowledge management module can periodically send state maintenance information to the bottom forwarding equipment so as to prevent the failure from autonomously communicating with the knowledge layer.
According to the electric power communication network networking method based on the deterministic network in the embodiment of the invention, the method adopts the electric power communication network architecture based on the deterministic network architecture, and a flow chart of a service scheduling method is shown in fig. 2, and comprises the following steps:
(1) When the user request arrives, the control layer analyzes the data packet through the data analysis module, thereby obtaining the service function requirement of the service and converting the service into a service function model;
(2) Transmitting the service function model to a routing control module, and combining a routing algorithm to realize a deterministic transmission path P;
(3) The resource management module obtains resource strategy related knowledge from the knowledge layer, and calls a scheduling algorithm to judge the allocation of resources by combining a transmission path P;
(4) According to the equipment state information recorded by the state information base of the knowledge layer, if the service resource combination meets the routing constraint and the service performance requirement, the scheduling is already carried out, the control layer determines a path allocation resource to the bottom layer, completes the execution of a buffer mechanism, a queue scheduling mechanism and a path selection mechanism of the deterministic requirement, and transfers an allocation command to the infrastructure layer; and if the scheduling conditions are not met, performing scheduling calculation and strategy learning again.
(5) The infrastructure layer receives the scheduling command of the control layer and transmits the service data packet; and after the data stream transmission is finished, updating the network state and storing the state information in a state information base of the knowledge layer.
The schematic diagram of the layers among the modules of the present invention is shown in fig. 1. The system function module includes: a deterministic network architecture based on SDN, a deterministic network information feedback mechanism. The deterministic network requires a limited upper delay limit and jitter and an extremely low packet loss rate, which not only puts higher requirements on the forwarding capability of a forwarding layer, but also puts more strict control capability on upper layer management. In order to realize timely and accurate information feedback, a knowledge management module and an equipment information state database are enhanced in a knowledge layer and cooperatively processed with a resource management module of a control layer to form a closed-loop information feedback mechanism.
And (3) realizing the power communication architecture function of the deterministic network:
the network node adopts deterministic time delay guarantee, the power core networking architecture mainly comprises a knowledge layer, a control layer and an infrastructure layer, a deterministic network architecture and a protocol are deployed at each layer, the expandability and the cooperative service capability of the deterministic power architecture are completed through cooperative processing of each layer, and a schematic diagram of the deterministic power communication network architecture is shown in fig. 1.
Implementation of the feedback function of the power communication architecture of the deterministic network, as shown in fig. 3:
the information feedback function is based on the enhanced management module and the deterministic routing protocol, and realizes information interaction between the knowledge layer and the control layer; and realizing communication with an infrastructure layer based on the information state equipment library, and acquiring the changed network state in time. And sending state updating information to the management module of the lower layer forwarding equipment independently whenever the running state of the lower layer forwarding equipment changes. In addition, the enhanced knowledge management module can periodically send state maintenance information to the bottom forwarding equipment so as to prevent the failure from autonomously communicating with the knowledge layer. When the control layer performs data stream scheduling, the control layer firstly analyzes the data stream to obtain the performance requirements of the data stream, such as tolerable maximum time delay, data packet length, data burst rate and the like; then according to the analyzed performance model of the data flow, mapping of the route and the service is carried out, and a deterministic service path is obtained; secondly, the control layer requests existing scheduling knowledge, such as synchronous scheduling or asynchronous scheduling, from the knowledge layer, and selects a corresponding scheduling strategy according to the underlying network resource state recorded by the information state database; meanwhile, the knowledge layer can carry out intelligent learning decision according to the existing scheduling algorithm and traffic characteristics, and the learned knowledge can be used for predicting the scheduling strategy of the subsequent traffic. And finally, issuing the routing and scheduling strategies to an infrastructure layer for corresponding forwarding and processing.
Implementation of power communication architecture management functions of deterministic networks, as shown in fig. 4:
the control layer is mainly responsible for resource and calculation management of the whole framework and mainly comprises a resource management module, a path calculation module, a flow scheduling module and a data analysis module, all the modules work cooperatively to control and manage bottom equipment, and network states can be obtained and corresponding scheduling algorithms can be called in time through interaction with a knowledge plane.
In summary, on the basis of the SDN deterministic network architecture, the present invention provides a deterministic network-based converged architecture and method for an electric power communication network system, supports large-scale deterministic service services, provides a flexible and extensible architecture, and implements functions of low delay, high-speed mobility, high reliability, low packet loss, etc. of electric power communication.
Claims (7)
1. A power communication network architecture system based on a deterministic network is characterized by comprising a control layer, an infrastructure layer and a knowledge layer;
a control layer, which is used for fitting services and strategies, and forming a determined route and resource strategy meeting the requirements of specific service quality and network behavior characteristics by adopting a knowledge-based scheduling mechanism aiming at the service requirements of users, so as to realize the decision adaptation of the route and the scheduling;
the infrastructure layer is used for matching strategies and resources, consists of a series of TSN network devices, and is used for mapping the routing and scheduling functions into refined network resource combinations to realize data forwarding;
and the knowledge layer is used for fitting resources with knowledge, is in communication connection with the infrastructure layer and the control layer, is responsible for collecting and storing the network resources of the infrastructure layer in real time, realizes a dynamic allocation strategy of the network resources by learning a resource allocation strategy of the control layer, and timely feeds back the learned scheduling strategy to the control layer.
2. The deterministic network-based power communication network architecture system of claim 1, wherein the control layer is responsible for implementing routing and scheduling functions, upward carries traffic, and downward controls the data layer, and comprises a data analysis module, a resource management module and a path computation module, and adopts a knowledge-based scheduling mechanism, and the method comprises the following steps: the data analysis module carries out abstract modeling on the user service request to realize the mapping from the service index to the service model; the path calculation module calculates a deterministic path of the service according to the service model and the routing algorithm; the resource management module adopts different scheduling algorithms according to the feedback information of the service type path and the knowledge layer to realize the resource allocation among the nodes;
the service requirement in the data analysis module includes a service basic parameter B and a network benefit R, and the basic parameter is defined as a quintuple B = (s, d, l, t) max R), s is the source node, d is the destination node, l is the data stream length, t max R is the distribution rate for the maximum end-to-end delay; the network benefit is defined as
Wherein v is the service class, c p For operator revenue, c s The standard grade gain is obtained, delta is time delay, lambda is jitter rate, and epsilon is packet loss rate; if the total number of the services requested by the user is m, the basic parameters and the network benefits which need to be processed by the analysis module are respectively (B) 1 ,B 2 ,...,B m) and (R1 ,R 2 ,...,R m ) In summary, the business requirement model I is expressed as:
the service model S refers to a service performance index and a necessary service function requirement, wherein the performance index is defined as Q = (t, delta, lambda and epsilon), wherein t is a throughput rate, delta is a time delay, lambda is a jitter rate, and epsilon is a packet loss rate; the service function requirements F include: network function F N Functional dependency relationship F Q And network function dependent resource type F R I.e. F = (F) N ,F Q ,F R ) (ii) a When the number of service requests is m, the service model is expressed as:
wherein ,Qi And F i Respectively representing the performance index of the ith service and the corresponding service function requirement, i belongs to (1, m);
the route addressing function in the path calculation module combines the service requirement matrix S defined above with the routing algorithm through a mapping function
Mapping to obtain a service path, wherein a routing algorithm Rt refers to a shortest path algorithm or a K shortest path algorithm,
the mapping function is used for selecting all possible transmission paths for the service according to the service performance requirement, and the process of converting the service requirement into the service path by the control layer is expressed as follows:
after the service path is established, data transmission is carried out, and if the application requirement cannot be met or the constraint condition of routing adjustment cannot be met, path calculation is executed again;
when the service path meets the condition, the resource management module reasonably distributes resources by adopting a scheduling algorithm based on a Circular Queue Forwarding (CQF) mechanism or asynchronous shaping ATS (automatic traffic Forwarding) according to the path P and the feedback information of the knowledge layer, so that the service end-to-end delay is minimized and the network resource utilization is maximized.
3. The deterministic network-based power communication network architecture system of claim 1,
the infrastructure layer is positioned at the bottommost layer of the whole framework and comprises deterministic forwarding equipment and deterministic processing equipment, and the deterministic forwarding equipment does not have a routing function and only forwards data; the deterministic processing device not only has data forwarding capability, but also has processing functions for implementing data by programming, specifically:
the infrastructure layer functions are implemented by node state information, service capabilities and function instances, where N is defined as all physical nodes N in the network i I is the number of physical nodes; the state information of the node is defined as F = (N) l ,N s ,N d ,N im ) Element components in the state information respectively represent node positions, node types, node connectivity and node importance; service capability is defined as C = (C) c ,C h ,C t ) Including computing power C c Buffer capacity C h And transmission capacity C t Wherein each class of service capability is specifically divided by a subscript j; function example E = (E) c ,E h ,E t ) Resource service capability of the corresponding node, wherein E c To calculate function instances, E h For example of a caching function, E t For the transport of a function instance, i.e. a service instance of node n on class j capability of transport resource instance E is defined as E, where
Respectively representing service instances of the nodes on the ith type capability of the computing, caching and transmitting functions, i e (1, j), and based on the definition, the resource instantiation result of the physical node on which the kth service node depends on the service path P is as follows:
the mapping from the service path to the data layer service instance resource combination is therefore represented as:
wherein ,
representing a mapping function that transforms the nodes traversed by the path P into refined resource instances according to the service capabilities C and the service instances F, d i The resource instantiation result, i ∈ (1, k), of the ith service node is represented.
4. The deterministic network-based power communication network architecture system of claim 1,
the knowledge layer is communicated with the infrastructure layer and the control layer through a programmable interface and comprises an enhanced knowledge management module and a state management information base; the state management information base stores a service resource combination example for real-time updating of equipment states, the enhanced knowledge management module records a scheduling strategy of a control layer, learns scheduling algorithms with different service requirements by combining a machine learning algorithm, and predicts an optimal scheduling strategy of a data stream according to the learned knowledge, wherein the knowledge is defined as K = (lh, br, D) max ,D T ,C l ) Lh is the data flow length, data burst rate br, maximum end-to-end delay D max Flow cutoff time D T And link capability C l 。
5. A deterministic network based power communication network architecture system according to claim 4,
the control layer with knowledge layer collaborative work realizes timely accurate feedback mechanism, includes: when the control layer performs data stream scheduling, the control layer firstly analyzes the data stream to obtain the performance requirements of the data stream, including tolerable maximum time delay, data packet length and data burst rate; then, mapping the route and the service according to the analyzed performance model of the data stream to obtain a deterministic service path; secondly, the control layer requests the existing scheduling knowledge including synchronous scheduling or asynchronous scheduling from the knowledge layer, and selects a corresponding scheduling strategy according to the underlying network resource state recorded by the information state database; meanwhile, the knowledge layer carries out intelligent learning decision according to the existing scheduling algorithm and traffic characteristics, the learned knowledge is used for predicting the scheduling strategy of the subsequent traffic, and finally, the routing and scheduling strategy is issued to the infrastructure layer for corresponding forwarding and processing.
6. A deterministic network based power communication network architecture system according to claim 4,
the knowledge management module and the equipment information state database of the knowledge layer collect and update the running state information of the bottom layer forwarding equipment, and autonomously send state update information to the management module when the running state of the bottom layer forwarding equipment changes; the enhanced knowledge management module periodically sends state maintenance information to the bottom forwarding equipment to prevent the communication with the knowledge layer independently when a fault occurs, and the control layer directly accesses the information state database to obtain real-time network equipment running state information when carrying out data flow scheduling distribution, so that an appropriate strategy is selected to carry out optimal distribution according to service requirements; the enhancement management module excavates and learns the algorithm of knowledge according to the demand of the control layer, and sends corresponding knowledge to the control layer, thereby realizing intelligent management and decision.
7. The method for scheduling power communication network resources, implemented by the power communication network architecture system based on deterministic networks according to any of claims 1 to 6, characterized in that the method comprises the following steps:
step 1, aiming at a power grid deterministic service, a control layer obtains a performance requirement of the service through a data analysis module and maps the performance requirement into a service function model S;
step 2, transmitting the service function model to a routing control module, and combining a routing algorithm to realize a deterministic transmission path;
step 3, the resource management module obtains resource strategy related knowledge from the knowledge layer, and invokes a scheduling algorithm to allocate resources by combining the transmission path P;
step 4, according to the equipment state information recorded by the state information base of the knowledge layer, if the service resource combination meets the routing constraint and the service performance requirement, the scheduling is already carried out at this moment, the control layer determines a path allocation resource to the bottom layer, completes the execution of a buffer mechanism, a queue scheduling mechanism and a path selection mechanism of the deterministic requirement, and transfers an allocation command to the infrastructure layer; if the scheduling conditions are not met, performing scheduling calculation and strategy learning again;
step 5, the infrastructure layer receives the dispatching command of the control layer and transmits the service data packet; and after the data stream transmission is finished, updating the network state and storing the state information in a state information base of the knowledge layer.
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