CN115189908A - Random attack survivability evaluation method based on network digital twin - Google Patents
Random attack survivability evaluation method based on network digital twin Download PDFInfo
- Publication number
- CN115189908A CN115189908A CN202210569319.0A CN202210569319A CN115189908A CN 115189908 A CN115189908 A CN 115189908A CN 202210569319 A CN202210569319 A CN 202210569319A CN 115189908 A CN115189908 A CN 115189908A
- Authority
- CN
- China
- Prior art keywords
- node
- service
- network
- time
- delay
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 54
- 230000005540 biological transmission Effects 0.000 claims abstract description 222
- 238000012545 processing Methods 0.000 claims abstract description 66
- 230000000903 blocking effect Effects 0.000 claims abstract description 50
- 238000004088 simulation Methods 0.000 claims abstract description 45
- 238000000034 method Methods 0.000 claims abstract description 35
- 238000013507 mapping Methods 0.000 claims abstract description 7
- 230000008569 process Effects 0.000 claims description 14
- 239000000126 substance Substances 0.000 claims description 13
- 230000006870 function Effects 0.000 claims description 12
- 230000000977 initiatory effect Effects 0.000 claims description 6
- 239000003999 initiator Substances 0.000 claims description 3
- 238000012854 evaluation process Methods 0.000 abstract 1
- 238000012935 Averaging Methods 0.000 description 6
- 230000004083 survival effect Effects 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 230000003993 interaction Effects 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000002904 solvent Substances 0.000 description 2
- RZVAJINKPMORJF-UHFFFAOYSA-N Acetaminophen Chemical compound CC(=O)NC1=CC=C(O)C=C1 RZVAJINKPMORJF-UHFFFAOYSA-N 0.000 description 1
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 230000001934 delay Effects 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 238000013209 evaluation strategy Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000007257 malfunction Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000007711 solidification Methods 0.000 description 1
- 230000008023 solidification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
- 230000035899 viability Effects 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/20—Network architectures or network communication protocols for network security for managing network security; network security policies in general
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0852—Delays
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1416—Event detection, e.g. attack signature detection
Landscapes
- Engineering & Computer Science (AREA)
- Computer Security & Cryptography (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Computer Hardware Design (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Environmental & Geological Engineering (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The invention discloses a random attack survivability evaluation method based on a network digital twin body, belongs to the technical field of network survivability evaluation, and solves the problem that the survivability evaluation result is low in accuracy due to the fact that part of influencing factors with large influences cannot be considered in the existing random attack survivability evaluation process. The method comprises the following steps: mapping the network entity into a network digital twin; performing time delay simulation on the network digital twin body to acquire time delay information of the network digital twin body; respectively acquiring transmission delay, processing delay, blocking rate and reliability facing random attack of real-time service and non-real-time service based on the delay information of the network digital twin; and obtaining a random attack survivability evaluation result based on the transmission delay, the processing delay, the blocking rate and the reliability facing random attack of the real-time service and the non-real-time service, and taking the random attack survivability evaluation result as the random attack survivability evaluation result of the network entity.
Description
Technical Field
The invention relates to the technical field of network survivability evaluation, in particular to a random attack survivability evaluation method based on a network digital twin body.
Background
In recent years, the internet and mobile internet industries have been vigorously developed, and have reached the stage of technical maturity and business model solidification. Since 2020, under the influence of epidemic situations, various industries greatly expand online working modes and various services, and together with the development of technologies such as artificial intelligence, digital twins and block chains, the universe gradually becomes a future integrated solution based on the development basis of the existing mobile internet, the comprehensive integration of various application modes and the comprehensive utilization of various key technologies.
The future development of the metas can be divided into two phases. The first stage puts high requirements on the virtual world for the requirements of metauniverse-enabled social and entertainment, immersive content experience and virtual social, and the stable and continuous high-performance experience brought to the user. In the second stage, the universe is the all-true Internet, so that life, industry and industry are enabled, the life and working modes of people are changed, and finally, the digitization of an economic system is realized. The physical world operation will be greatly affected by the failure of the metasma and related digital twins due to accidents and accidents, etc.
Therefore, at the beginning of the current stage of design, it is important to consider the important enabling means in the meta universe-the survivability of the digital twin to simulate the physical world, and the ability to recover and complete tasks in the event of a corresponding failure or malfunction. Survivability is an important safety measure in a physical world system, and means that the system can provide the capability of completing the task in time under the condition that nodes or links in the system fail after an accident, a fault or an attack. The purpose of researching the survivability of the digital twin is to enable the digital twin to simulate the physical world system to obtain the optimal service performance with the minimum cost or improve the cost of the enemy to reduce the network performance when the physical world system is subjected to random attack or external force attack. Through the evaluation reference of the twin body, the judgment on the survivability of the physical system is quickly formed, so as to help the command decision to decide the actions of supplementing or starting backup and the like at the next stage.
Survivability was originally measured by cohesion and connectivity, and currently, the methods for survivability study mainly include the following methods:
acquiring a transmission optimal path according to the predicted task completion time and task completion cost based on an interrupt fault-tolerant routing algorithm; (2) An autonomous routing algorithm (SARA) is provided by combining two different types of system nodes, the interaction pressure of information among a plurality of nodes can be reduced, the saved resources are used for increasing the correct transmission rate, and the capability of processing the fault node is improved; (3) A centralized evaluation strategy incorporating survivability design is established, and performance degradation caused by problem nodes is relieved; (4) A modeling method based on failure data is provided by analyzing survivability allowance of the system; (5) The topological structure characteristics of the system are analyzed, and an analysis method based on time periods is introduced; (6) A survivability measuring method based on a topological structure and system capacity; (7) The viability of the system was measured by the cost of destroying the system with the enemy.
The random attack survivability evaluation refers to the evaluation that the performance of a node or a link is reduced or fails due to the attack of external non-specific directivity on a network entity, so that the normal function cannot be met; the existing random attack survivability evaluation method mainly considers the problems of resource balance, routing strategy and system structure, and does not comprehensively consider the factors of reliability, network efficiency, service type, service utility, cost and the like, so that the accuracy of the random attack survivability evaluation result is low.
Disclosure of Invention
In view of the foregoing analysis, embodiments of the present invention are directed to providing a method for assessing survivability of a random attack based on a network digital twin, so as to solve the problem that the accuracy of survivability assessment results is low due to the fact that some influencing factors having large influences are not considered in the existing random attack survivability assessment process.
The invention discloses a random attack survivability evaluation method based on a network digital twin body, which comprises the following steps:
mapping the network entity into a network digital twin body, and acquiring nodes and links in the network digital twin body obtained by mapping;
performing time delay simulation on the network digital twin body to acquire time delay information of the network digital twin body;
respectively acquiring transmission delay, processing delay, blocking rate and reliability facing random attack of real-time service and non-real-time service based on the delay information of the network digital twin;
and obtaining a random attack survivability evaluation result based on the transmission delay, the processing delay, the blocking rate and the reliability facing random attack of the real-time service and the non-real-time service, and taking the random attack survivability evaluation result as the random attack survivability evaluation result of the network entity.
On the basis of the scheme, the invention also makes the following improvements:
further, the obtaining a random attack survivability evaluation result includes:
constructing a network utility expression facing random attack based on the acquired transmission delay, processing delay, blocking rate and reliability facing random attack of the real-time service and the non-real-time service;
constructing constraint conditions and target functions of random attack survivability evaluation based on a network utility expression facing random attack and a random attack-oriented crash failure proportion;
obtaining an optimal solution of the random attack survivability based on the constraint condition and the objective function of the random attack survivability evaluation;
and substituting the optimal solution of the random attack survivability into a network utility expression facing the random attack to obtain a random attack survivability evaluation result.
Further, the network utility expression facing random attack is as follows:
wherein n is v Representing attacked sectionsTotal number of dots, n e Representing the total number of links between attacked nodes, and N representing the total number of service terminal nodes;
representing originating nodes s from a service i Successful transmission of real-time traffic to a terminating node s j The reliability of time-oriented random attack;
representing originating nodes s from a service i Successful transmission of non-real time traffic to a terminating node s j The reliability of time-oriented random attack;
representing originating nodes s from a service i Transmitting real-time traffic to a terminating node s j (ii) arrival rate of;
representing originating nodes s from a service i Transmitting non-real-time traffic to a terminating node s j (ii) arrival rate of;
respectively representing the transmission time delay of real-time service and non-real-time service;
respectively representing the processing time delay of real-time service and non-real-time service;
respectively represent
The weight of (c);
respectively represent
The weight of (c); I.C. A r 、I nr Respectively representing the capacity of real-time service and the capacity of non-real-time service in the whole network digital twin.
Further, the objective function of the random attack survivability evaluation is:
wherein N is 1 Representing a total number of nodes in the network digital twin; c. C v Representing the cost of a randomly attacking node, c e Represents the cost of a random attack link;
the constraint condition of the random attack survivability evaluation is as follows:
st.U ra (n v ,n e )≤T h2 U ra (0,0) (3)
wherein, U ra0 Represents n v ＝0,n e Initial utility U in random attack mode when =0 ra (0,0)，T h2 Representing the proportion of crash failure in a random attack mode;
will be shown in formula (2)
Set of n at minimum v ,n e Optimal solution as survivability for random attacks
And
at this time, the random attack survivability evaluation result is
Further, the nodes comprise a network transmission node and a terminal node;
the terminal nodes comprise service terminal nodes and a control center;
when the service terminal node is used as a service initiator, the service terminal node is called a service initiation node;
when the service terminal node acts as a service receiver, it is called a service termination node.
Further, in the present invention,
wherein the content of the first and second substances,
m represents the total number of links between nodes in the network digital twin;
representing the average node degree of the network;
L ij representing originating nodes s from a service i Sending real-time traffic to a service termination node s j The set of all network transmission nodes on the transmission path of (a),
numL ij a set of representations L ij Number of network transmission nodes; e ij Representing originating nodes s from a service i Sending real-time traffic to a service termination node s j The transmission path of (2) a set of links between all network transmission nodes;
L ig representing originating nodes s from a service i Sending non-real-time traffic to a management and control center s g The set of all network transmission nodes on the transmission path of (a),
L gj representing slave management and control centres s g Sending non-real-time traffic to a service termination node s j Set of all nodes on the transmission path of，
numL ig 、numL gj Respectively represent a set L ig 、L gj The number of network transmission nodes in (1); e ig Representing originating nodes s from a service i Sending non-real-time traffic to a management and control node s g The set of links between all network transmission nodes on the transmission path; e gj Indicating the sending of non-real-time traffic from a policing node to a service terminating node s j The transmission path of (2) transmits a set of links between nodes over all networks.
Further, when the service start node s i Sending real-time traffic to a terminating node s via a network transport node j Transmission delay of real-time traffic
Expressed as:
wherein, T uplink_s,n Indicating the uplink delay, T, between the service initiation node and the network transmission node downlink_n,t Representing the downlink delay between the network transmission node and the service termination node; w is a ac_s,n The access queuing time delay of the data access network transmission node of the service starting node is equal to the access queuing time delay of the data access network transmission node of the service terminal node; w is a ac_n,t The access queuing time delay of a data access service termination node of a network transmission node is represented and is equal to the access queuing time delay of a data access service terminal node of the network transmission node;
a set of representations L ij The network transmission node in (1) accesses the next network transmission node
Access queuing delay;
representing network transport nodes
The transmission queuing delay; t is cross Representing the average transmission time delay of the link between every two network transmission nodes;
when the service starts node s i Via network transmission nodes and control centers s g Sending non-real-time traffic to a terminating node s j Transmission delay of time, non-real time traffic
Expressed as:
wherein, T uplink_n,g 、T downlink_n,g Respectively representing uplink time delay and downlink time delay between the control center and the network transmission node; w is a ac_n,g Representing the access queuing time delay of the data access control center of the network transmission node; w is a ac_g,n Representing the access queuing time delay of a data access network transmission node of a management and control center;
a set of representations L ig The network transmission node in (1) accesses the next network transmission node
Access queuing delay;
representing network transport nodes
The sending queuing delay;
a set of representations L gj Network transmission node in access network transmission node
Access queuing delay;
representing network transport nodes
Transmission queuing delay.
Further, when the service start node s i Sending real-time traffic to a terminating node s via a network transport node j Processing delay of real-time traffic
Expressed as:
wherein the content of the first and second substances,
representing network transport nodes
The processing delay of (2); t is j Representing the processing time delay of the service termination node, which is equal to the processing time delay of the service terminal node;
when the service starts node s i Via network transmission nodes and control centers s g Sending non-real-time traffic to a terminating node s j Processing delay of time, non-real time traffic
Expressed as:
wherein the content of the first and second substances,
representing network transport nodes
The processing delay of (2);
representing network transport nodes
Processing delay of, T g And representing the processing time delay of the management and control center.
Further, when the service originating node s i Sending real-time traffic to a terminating node s via a network transport node j Blocking rate of real-time traffic
Expressed as:
wherein the content of the first and second substances,
representing the traffic access blocking probability of the traffic originating node,
representing the traffic access blocking probability of the traffic terminating node,
respectively representing network transmission nodes
To be connected withThe blocking probability is entered and the blocking probability is sent;
representing the transmission blocking probability of the e-th link;
when the service starts node s i Via network transmission nodes and control centers s g Sending non-real-time traffic to a terminating node s j Blocking rate of time, non-real time traffic
Expressed as:
wherein the content of the first and second substances,
represents the traffic access blocking probability of the traffic originating node,
respectively representing network transmission nodes
Access blocking probability and sending blocking probability;
respectively representing network transmission nodes
Access blocking probability, transmission blocking probability.
Further, performing time delay simulation on the network digital twin to acquire time delay information of the network digital twin, wherein the time delay information includes:
executing multiple times of random service simulation, wherein the random service simulation is divided into random real-time service simulation and random non-real-time service simulation; generating time delay parameters of each node and each link according to the random service during each simulation;
and acquiring the time delay information of the network digital twin body based on the time delay parameters of each node and each link in the multiple random service simulation processes.
Compared with the prior art, the invention can realize at least one of the following beneficial effects:
the random attack survivability evaluation method based on the network digital twin body overcomes the defects of the prior art, and utilizes the overall efficiency based on service-oriented application to construct a network utility function to measure the random attack survivability of the digital twin body simulation physical world system so as to characterize and evaluate the task completion capability of the network entity before and after encountering random attack.
Meanwhile, considering that various resources of nodes in a network entity are very limited, a node fault can cause task congestion, information loss and time delay increase. Therefore, the method provided by the invention can be used for simulating various characteristics influencing the survival of the random attack, so that the transmission delay, the processing delay, the blocking rate and the reliability facing the random attack of the real-time service and the non-real-time service are obtained, and the random attack survival evaluation method based on the network digital twin body is finally formed by matching the network utility facing the random attack, so that the survival of the random attack of the digital twin body can be evaluated from multiple dimensions, and the characteristics of the physical entity mapped by the random attack can be comprehensively evaluated.
In the invention, the technical schemes can be combined with each other to realize more preferable combination schemes. Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
The drawings, in which like reference numerals refer to like parts throughout, are for the purpose of illustrating particular embodiments only and are not to be considered limiting of the invention.
Fig. 1 is a flow chart of a random attack survivability evaluation method based on a network digital twin.
Detailed Description
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate preferred embodiments of the invention and together with the description, serve to explain the principles of the invention and not to limit the scope of the invention.
Example 1
The embodiment of the invention discloses a survivability evaluation method based on a network digital twin body, a flow chart is shown in fig. 1, and the specific process is described as follows:
step S1: mapping the network entity into a network digital twin body, and acquiring nodes and links in the network digital twin body obtained by mapping;
specifically, nodes and links in the network entity are mapped to nodes and links, respectively, in the network digital twin. The nodes include network transmission nodes and terminal nodes. In particular, the amount of the solvent to be used,
the network transmission node is used for completing the transmission of services, such as a satellite access node in satellite communication.
The terminal nodes comprise service terminal nodes and a control center;
when the service terminal node is used as a service initiator, the service terminal node is called a service initiation node; when the service terminating node acts as a service receiver, it is called a service terminating node. When processing real-time services, only the interaction between the service terminal node and the network transmission node is involved in consideration of the requirement of real-time; the specific implementation process is as follows: and the service initial node sends the real-time service to the network transmission node, and the network transmission node sends the real-time service to the service terminal node after processing.
The control center is a special terminal node, and relates to interaction among the service terminal node, the control center and the network transmission node when processing non-real-time service; the specific implementation process is as follows: and the network transmission node also sends part of tasks of the non-real-time processing service to the control center for processing in the process of processing the non-real-time service, and the control center feeds back the processing result to the network transmission node, and then the network transmission node processes the processing result and sends the processing result to the service terminal node. In the process, the management and control center completes the processing of part of non-real-time services so as to relieve the processing pressure of the network transmission nodes.
Step S2: performing time delay simulation on the network digital twin body to acquire time delay information of the network digital twin body; the time delay information of the network digital twin comprises:
(1) The delay information of each network transmission node comprises:
the access queuing delay of the data access network transport node of the service terminal node,
access queuing delay for non-current network transmission nodes to access current network transmission nodes,
the transmission of the queuing delay time is delayed,
processing time delay;
(2) The time delay information of the service terminal node comprises:
access queuing delay of a data access service terminal node of a network transmission node,
processing time delay;
an uplink delay and a downlink delay between the service terminal node and the network transmission node; here, when describing an uplink, it means that the service terminal node transmits data to the network transmission node, and at this time, the service terminal node serves as a service start node; when describing the downlink, the network transmission node sends data to the service terminal node, and at this time, the service terminal node is used as a service termination node;
(3) The time delay information of the management and control center comprises:
the data access of the network transmission node controls the access queuing delay of the center,
the sending queuing time delay of the control center is controlled,
processing time delay;
controlling uplink time delay and downlink time delay between a center and a network transmission node; here, when describing an uplink, it means that the management and control center sends data to the network transmission node; when describing downlink, the network transmission node sends data to the management and control center.
(4) Average transmission delay of links between two network transmission nodes.
The specific process is as follows:
step S21: executing multiple times of random service simulation, wherein the random service simulation is divided into random real-time service simulation and random non-real-time service simulation; generating time delay parameters of each node and each link according to the random service during each simulation; the generated delay parameters of the nodes and the links comprise:
(1) The delay parameter of each network transmission node comprises:
the data of each service terminal node is accessed to the access queuing delay parameter of the current network transmission node,
an access queuing delay parameter for a non-current network transmission node to access a current network transmission node,
the queuing delay parameter is transmitted and,
processing the time delay parameter;
(2) The time delay parameter of the service terminal node comprises:
the data of each network transmission node is accessed into the access queuing delay parameter of each service terminal node,
processing the time delay parameter;
uplink delay parameters and downlink delay parameters between the service terminal node and each network transmission node;
(3) When the random non-real-time service simulation is executed, the method also comprises a time delay parameter of a control center, and comprises the following steps:
the access queuing delay parameter of the data access control center of the network transmission node,
a sending queuing delay parameter of the control center,
processing the time delay parameter;
and the uplink delay parameter and the downlink delay parameter between the control center and the network transmission node.
(4) And transmitting the transmission delay parameter of the link between every two network transmission nodes.
It should be noted that, in the simulation process, according to the delay characteristics and service classification of the network entity and the actual network operation characteristics, the queuing delay parameter and the processing delay parameter of each node and the transmission delay parameter of the link between every two network transmission nodes are generated according to the random service; the size of the time delay parameter is represented by a model and parameters which obey certain probability distribution, so that the time delay estimation of the network digital twin is realized. In the specific implementation process, different time delays are set for different services; in particular, the amount of the solvent to be used,
access queuing delay parameter and transmission queuing delay parameter: the index distribution is conformed;
processing a time delay parameter: can be distributed in an exponential way or in a normal way;
transmission delay parameters: for a fixed wired link, the propagation delay conforms to normal distribution with smaller variance; for a wireless link, according to the difference of the propagation distance, the propagation delay accords with normal distribution with relatively large variance and mean value;
the setting of the delay parameters not only conforms to a certain probability distribution, but also needs to consider the range of the probability distribution; the parameter selection range of the probability distribution is directly related to the service type; common random services include video, voice, and data; the transmission rate of the video service is 384kbps, the transmission rate of the voice service is 64kbps, and the transmission rate of the data service is 128kbps. Therefore, based on the transmission rate and the processing efficiency of different services, each time delay parameter is selected according to certain probability distribution; after all the time delay parameters are determined, each simulation time delay can be obtained through simulation. Illustratively, the queuing delay is selected as an exponential distribution, and when the transmission service is a video class, a voice class, or a data class, the set queuing delay is sequentially reduced on the basis of meeting the exponential distribution.
Step S22: acquiring time delay information of the network digital twin based on time delay parameters of each node and each link in a multiple random service simulation process, wherein the specific acquisition mode is as follows:
(1) The method for acquiring the time delay information of each network transmission node comprises the following steps:
the access queuing time delay of the data access network transmission node of the service terminal node is as follows: the average value of the access queuing delay parameters of the data access current network transmission node of each service terminal node in the multiple random service delay simulation;
the access queuing time delay of the non-current network transmission node accessing the current network transmission node is as follows: the average value of access queuing delay parameters of non-current network transmission nodes accessed to the current network transmission nodes in multiple random service delay simulations;
the transmission queuing delay is: the average value of the sending queuing delay parameters of the current network transmission node in the multiple random service delay simulation;
processing time delay: average value of processing delay parameter of current network transmission node in multiple times of random service delay simulation;
(2) The method for acquiring the time delay information of the service terminal node comprises the following steps:
the access queuing delay of the data access service terminal node of the network transmission node is as follows: the data of each network transmission node is accessed to the average value of the access queuing delay parameters of each service terminal node in multiple random service delay simulations;
the processing time delay is as follows: averaging the delay parameters of all service terminal nodes in multiple random service delay simulations;
the uplink delay between the service terminal node and the network transmission node is: averaging uplink delay parameters between all service terminal nodes and each network transmission node in multiple random service delay simulations;
the downlink delay between the service terminal node and the network transmission node is: averaging downlink delay parameters between all service terminal nodes and each network transmission node in multiple random service delay simulations;
(3) The acquisition mode of the time delay information of the control center comprises the following steps:
the access queuing time delay of the data access control center of the network transmission node is as follows: average value of access queuing delay parameters of the data access control center of each network transmission node in multiple random non-real-time service delay simulations;
the sending queuing time delay of the control center is as follows: the average value of the sending queuing delay parameters of the management and control center in the multiple random non-real-time service delay simulation;
the processing time delay is as follows: averaging the processing delay parameters of the management center in multiple random non-real-time service delay simulation;
the uplink time delay between the control center and the network transmission node is as follows: the average value of uplink delay parameters between a control center and each network transmission node in multiple random non-real-time service delay simulation;
the downlink delay between the management and control center and the network transmission node is as follows: and (3) averaging downlink delay parameters between the control center and each network transmission node in multiple random non-real-time service delay simulation.
(4) The average transmission delay of the links between two network transmission nodes is: and averaging transmission delay parameters of links between every two network transmission nodes in multiple random service delay simulations.
And step S3: respectively acquiring transmission delay, processing delay, blocking rate and reliability facing random attack of real-time service and non-real-time service based on the delay information of the network digital twin;
(1) Transmission delay of real-time service and non-real-time service
When the service starts node s i Sending real-time traffic to a terminating node s via a network transport node j Transmission delay of real-time traffic
Can be expressed as:
wherein, T uplink_s,n The uplink time delay between the service starting node and the network transmission node is represented and is equal to the uplink time delay between the service terminal node and the network transmission node; t is a unit of downlink_n,t Indicating a downlink delay between the network transmission node and the service termination node equal to the downlink delay between the service termination node and the network transmission node; w is a ac_s,n The access queuing time delay of the data access network transmission node of the service starting node is equal to the access queuing time delay of the data access network transmission node of the service terminal node; w is a ac_n,t The access queuing time delay of a data access service termination node of a network transmission node is represented and is equal to the access queuing time delay of a data access service terminal node of the network transmission node; l is a radical of an alcohol ij Representing originating nodes s from a service i Sending real-time traffic to a service termination node s j The set of all network transmission nodes on the transmission path of (a),
numL ij a set of representations L ij The number of network transmission nodes in (1);
a set of representations L ij Network transmission node in the network access next network transmission node
Access queuing delay;
representing network transport nodes
The transmission queuing delay; t is cross Representing the average transmission delay of the link between two network transmission nodes.
When the service starts node s i Via network transmission nodes and control centers s g Sending non-real time jobsService to termination node s j Transmission delay of time, non-real time traffic
Can be expressed as:
wherein, T uplink_n,g 、T downlink_n,g Respectively representing uplink time delay and downlink time delay between the control center and the network transmission node; w is a ac_n,g Representing the access queuing time delay of the data access control center of the network transmission node; w is a ac_g,n Representing the access queuing time delay of a data access network transmission node of a management and control center; l is ig Representing originating nodes s from a service i Sending non-real-time traffic to a management and control center s g The set of all network transmission nodes on the transmission path of (a),
L gj representing slave management centres s g Sending non-real-time traffic to a service termination node s j The set of all nodes on the transmission path of (c),
numL ig 、numL gj respectively represent a set L ig 、L gj The number of network transmission nodes in (1);
a set of representations L ig The network transmission node in (1) accesses the next network transmission node
Access queuing delay;
representing network transport nodes
The sending queuing delay;
a set of representations L gj Network transmission node in the network access network transmission node
Access queuing delay;
representing network transport nodes
Transmission queuing delay.
(2) Processing delay for real-time traffic and non-real-time traffic
When the service starts node s i Sending real-time traffic to a terminating node s via a network transport node j Processing delay of real-time traffic
Can be expressed as:
wherein the content of the first and second substances,
representing network transport nodes
The processing delay of (2); t is j The processing delay of the service termination node is represented and is equal to the processing delay of the service terminal node.
When the service starts node s i Via network transmission nodes and control centers s g Sending non-real-time traffic to a terminating node s j Processing delay of time, non-real time traffic
Can be expressed as:
wherein the content of the first and second substances,
representing network transport nodes
The processing delay of (2);
representing network transport nodes
Processing delay of, T g And representing the processing time delay of the management and control center.
(3) Blocking rate for real-time traffic and non-real-time traffic
When the service starts node s i Sending real-time traffic to a terminating node s via a network transport node j Blocking rate of real-time traffic
Can be expressed as:
wherein the content of the first and second substances,
representing the traffic access blocking probability of the traffic originating node,
representing the traffic access blocking probability of the traffic terminating node,
respectively representing network transmission nodes
Access blocking probability and sending blocking probability;
indicating the transmission blocking probability of the E-th link, E ij Representing originating nodes s from a service i Sending real-time traffic to a service termination node s j The transmission path of (2) a set of links between all network transmission nodes;
when the service starts node s i Via network transmission nodes and control centers s g Sending non-real-time traffic to a terminating node s j Blocking rate of time, non-real time traffic
Can be expressed as:
wherein the content of the first and second substances,
representing the traffic access blocking probability of the traffic originating node,
(4) Reliability of real-time services and non-real-time services for random attack;
in the random attack process, the cost of attacking one node is c v The cost of attacking a link is c e When c is v → infinity or c e → infinity denotes that only link or node is attacked, if n is attacked v A node, n e A link with an average node degree of
The probability of each node and each edge being hit is
Reliability of the node in the random attack mode
Then the link is reliable in a random attack mode
Thereby obtaining:
from the service originating node s i Successful transmission of real-time traffic to a terminating node s j Temporal random attack oriented reliabilityDegree of rotation
Can be expressed as:
n v representing the total number of attacked nodes, n e Representing the total number of links between the attacked nodes; n is a radical of 1 Representing a total number of nodes in the network digital twin, M representing a total number of links between nodes in the network digital twin;
representing the average node degree of the network;
from the service originating node s i Successful transmission of non-real time traffic to a terminating node s j Reliability of time-oriented random attack
Can be expressed as:
and step S4: and obtaining a random attack survivability evaluation result based on the obtained transmission delay, processing delay, blocking rate and reliability facing random attack of the real-time service and the non-real-time service, and taking the random attack survivability evaluation result as the random attack survivability evaluation result of the network entity. Specifically, the following is performed:
step S41: constructing a network utility expression facing random attack based on the acquired transmission delay, processing delay, blocking rate and reliability facing random attack of the real-time service and the non-real-time service;
network utility U facing random attack ra (n v ,n e ) The expression is as follows:
wherein N represents the total number of service terminal nodes;
representing a random attack oriented originating node s from a service i Successful transmission of real-time traffic to a terminating node s j The reliability of (2);
representing a random attack oriented originating node s from a service i Successful transmission of non-real time traffic to a terminating node s j The reliability of (2);
representing originating nodes s from a service i Successful transmission of real-time traffic to a terminating node s j (ii) arrival rate of;
representing originating nodes s from a service i Successful transmission of non-real time traffic to a terminating node s j (ii) arrival rate of;
respectively represent
The weight of (a) is determined,
respectively represent
The weight of (c); i is r 、I nr The capacity of real-time service and the capacity of non-real-time service in the whole network digital twin are respectively represented, and the two parameters can be obtained through simulation.
Step S42: constructing constraint conditions and target functions of random attack survivability evaluation based on a network utility expression facing random attack and a random attack-oriented crash failure proportion;
the objective function of the random attack survivability assessment is as follows:
the constraint condition of the random attack survivability evaluation is as follows:
st.U ra (n v ,n e )≤T h2 U ra (0,0) (12)
wherein, U ra0 Represents n v ＝0,n e Initial utility U in random attack mode at time of =0 ra (0,0)，T h2 Representing the proportion of crash failure in a random attack mode;
step S43: obtaining an optimal solution of the random attack survivability based on the constraint conditions and the objective function of the random attack survivability evaluation; that is, will be expressed in the formula (12)
Set of n at minimum v ,n e Optimal solution as survivability for random attacks
And
step S44: the optimal solution of the random attack survivability is brought into a network utility expression (11) facing the random attack to obtain the evaluation result of the random attack survivability
In summary, compared with the prior art, the random attack survivability evaluation method based on the network digital twin provided by the embodiment of the invention overcomes the defects of the prior art, and utilizes the overall effectiveness based on service-oriented application to construct a network utility function to measure the random attack survivability of the digital twin simulation physical world system so as to characterize and evaluate the task completion capability of the network entity before and after encountering random attack. Meanwhile, considering that various resources of nodes in a network entity are very limited, a node fault can cause task congestion, information loss and time delay increase. Therefore, the method provided by the invention can be used for simulating various characteristics influencing the survival of the random attack, so that the transmission delay, the processing delay, the blocking rate and the reliability facing the random attack of the real-time service and the non-real-time service are obtained, and the random attack survivability evaluation method based on the network digital twin is finally formed by matching with the network utility facing the random attack.
Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program, which is stored in a computer readable storage medium, to instruct related hardware. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (10)
1. A random attack survivability evaluation method based on network digital twins is characterized by comprising the following steps:
mapping the network entity into a network digital twin body, and acquiring nodes and links in the network digital twin body obtained by mapping;
performing time delay simulation on the network digital twin body to acquire time delay information of the network digital twin body;
respectively acquiring transmission delay, processing delay, blocking rate and reliability facing random attack of real-time service and non-real-time service based on the delay information of the network digital twin;
and obtaining a random attack survivability evaluation result based on the transmission delay, the processing delay, the blocking rate and the reliability facing random attack of the real-time service and the non-real-time service, and taking the random attack survivability evaluation result as the random attack survivability evaluation result of the network entity.
2. The method according to claim 1, wherein the obtaining a random attack survivability evaluation result comprises:
constructing a network utility expression facing random attack based on the acquired transmission delay, processing delay, blocking rate and reliability facing random attack of the real-time service and the non-real-time service;
constructing constraint conditions and target functions of random attack survivability evaluation based on a network utility expression facing random attack and a random attack-oriented crash failure proportion;
obtaining an optimal solution of the random attack survivability based on the constraint conditions and the objective function of the random attack survivability evaluation;
and substituting the optimal solution of the random attack survivability into a network utility expression facing the random attack to obtain a random attack survivability evaluation result.
3. The method for assessing survivability of random attack based on network digital twin according to claim 2, wherein the network utility expression facing random attack is as follows:
wherein n is v Representing the total number of attacked nodes, n e Representing the total number of links between attacked nodes, and N representing the total number of service terminal nodes;
representing originating nodes s from a service i Successful transmission of real-time traffic to a terminating node s j The reliability of time-oriented random attack;
representing originating nodes s from a service i Successful transmission of non-real time traffic to a terminating node s j The reliability of time-oriented random attack;
representing originating nodes s from a service i Transmitting real-time traffic to a terminating node s j (ii) arrival rate of;
representing originating nodes s from a service i Transmitting non-real-time traffic to a terminating node s j (ii) arrival rate of;
respectively representing the transmission time delay of real-time service and non-real-time service;
respectively representing the processing time delay of real-time service and non-real-time service;
respectively represent
The weight of (c);
respectively represent
The weight of (c); i is r 、I nr Respectively representing the capacity of real-time service and the capacity of non-real-time service in the whole network digital twin.
4. The method according to claim 3, wherein the random attack survivability evaluation method based on the network digital twin is characterized in that,
the objective function of the random attack survivability assessment is as follows:
wherein N is 1 Representing a total number of nodes in the network digital twin; c. C v Representing the cost of a randomly attacking node, c e Represents the cost of a random attack link;
the constraint condition of the random attack survivability evaluation is as follows:
st.U ra (n v ,n e )≤T h2 U ra (0,0) (3)
wherein, U ra0 Represents n v ＝0,n e Initial utility U in random attack mode at time of =0 ra (0,0)，T h2 Representing the proportion of crash failure in a random attack mode;
will be shown in formula (2)
Set of n at minimum v ,n e Optimal solution as survivability for random attacks
And
at this time, the random attack survivability evaluation result is
5. The network digital twin-based random attack survivability evaluation method according to claim 3 or 4, wherein the nodes comprise a network transmission node and a terminal node;
the terminal nodes comprise service terminal nodes and a control center;
when the service terminal node is used as a service initiator, the service terminal node is called a service initiation node;
when the service terminal node acts as a service receiver, it is called a service termination node.
6. The method according to claim 5, wherein the network digital twin-based random attack survivability evaluation method,
wherein, the first and the second end of the pipe are connected with each other,
m represents the total number of links between nodes in the network digital twin;
representing the average node degree of the network;
L ij representing originating nodes s from a service i Sending real-time traffic to a service termination node s j The set of all network transmission nodes on the transmission path of (a),
numL ij a set of representations L ij The number of network transmission nodes in (1); e ij Representing originating nodes s from a service i Sending real-time trafficService-to-service termination node s j The transmission path of (2) a set of links between all network transmission nodes;
L ig representing originating nodes s from a service i Sending non-real-time traffic to a management and control center s g The set of all network transmission nodes on the transmission path of (a),
L gj representing slave management and control centres s g Sending non-real-time traffic to a service termination node s j The set of all nodes on the transmission path of (c),
numL ig 、numL gj respectively represent a set L ig 、L gj The number of network transmission nodes in (1); e ig Representing originating nodes s from a service i Sending non-real-time traffic to a management and control node s g The transmission path of (2) a set of links between all network transmission nodes; e gj Indicating the sending of non-real-time traffic from a policing node to a service terminating node s j The transmission path of (2) transmits a set of links between nodes over all networks.
7. The method according to claim 6, wherein the random attack survivability evaluation method based on the network digital twin is characterized in that,
when the service starts node s i Sending real-time traffic to a terminating node s via a network transport node j Transmission delay of real-time traffic
Expressed as:
wherein, T uplink_s,n Representing the uplink delay between the service originating node and the network transmission node,T downlink_n,t representing the downlink delay between the network transmission node and the service termination node; w is a ac_s,n The access queuing delay of the data access network transmission node of the service starting node is equal to the access queuing delay of the data access network transmission node of the service terminal node; w is a ac_n,t The access queuing time delay of a data access service termination node of a network transmission node is represented and is equal to the access queuing time delay of a data access service terminal node of the network transmission node;
a set of representations L ij The network transmission node in (1) accesses the next network transmission node
Access queuing delay;
representing network transport nodes
The sending queuing delay; t is a unit of cross Representing the average transmission time delay of a link between every two network transmission nodes;
when the service starts node s i Via network transmission nodes and control centers s g Sending non-real-time traffic to a terminating node s j Transmission delay of time, non-real time traffic
Expressed as:
wherein, T uplink_n,g 、T downlink_n,g Respectively representing uplink time delay and downlink time delay between the control center and the network transmission node; w is a ac_n,g Representing the access queuing time delay of the data access control center of the network transmission node; w is a ac_g,n Representing the access queuing time delay of a data access network transmission node of a management and control center;
a set of representations L ig Network transmission node in the network access next network transmission node
Access queuing delay;
representing network transport nodes
The transmission queuing delay;
a set of representations L gj Network transmission node in the network access network transmission node
Access queuing delay;
representing network transport nodes
Transmission queuing delay.
8. The method according to claim 7, wherein the method is used when a service initiation node s is used i Sending real-time traffic to a terminating node s via a network transport node j Processing delay of real-time service
Expressed as:
wherein the content of the first and second substances,
representing network transport nodes
The processing delay of (2); t is a unit of j Representing the processing time delay of the service termination node, which is equal to the processing time delay of the service terminal node;
when the service starts node s i Via network transmission nodes and control centers s g Sending non-real-time traffic to a terminating node s j Processing delay of time, non-real time traffic
Expressed as:
wherein the content of the first and second substances,
representing network transport nodes
The processing delay of (2);
representing network transport nodes
Processing delay of, T g And representing the processing time delay of the management and control center.
9. The method according to claim 8, wherein the method is performed when a service initiation node s is used i Sending real-time traffic to a terminating node s via a network transport node j Blocking rate of real-time traffic
Expressed as:
wherein the content of the first and second substances,
representing the traffic access blocking probability of the traffic originating node,
representing the traffic access blocking probability of the traffic terminating node,
respectively representing network transmission nodes
Access blocking probability and sending blocking probability;
representing the transmission blocking probability of the e-th link;
when the service starts node s i Via network transmission nodes and control centers s g Sending non-real-time traffic to a terminating node s j Blocking rate of time, non-real time traffic
Expressed as:
wherein the content of the first and second substances,
represents the traffic access blocking probability of the traffic originating node,
respectively representing network transmission nodes
Access blocking probability and sending blocking probability;
respectively representing network transmission nodes
Access blocking probability, transmission blocking probability.
10. The random attack survivability evaluation method based on the network digital twin according to claim 1, wherein the time delay simulation of the network digital twin to obtain the time delay information of the network digital twin comprises:
executing multiple times of random service simulation, wherein the random service simulation is divided into random real-time service simulation and random non-real-time service simulation; generating time delay parameters of each node and each link according to the random service during each simulation;
and acquiring the time delay information of the network digital twin body based on the time delay parameters of each node and each link in the multiple random service simulation processes.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210569319.0A CN115189908B (en) | 2022-05-24 | 2022-05-24 | Random attack survivability evaluation method based on network digital twin |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210569319.0A CN115189908B (en) | 2022-05-24 | 2022-05-24 | Random attack survivability evaluation method based on network digital twin |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115189908A true CN115189908A (en) | 2022-10-14 |
| CN115189908B CN115189908B (en) | 2024-05-14 |
Family
ID=83512742
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210569319.0A Active CN115189908B (en) | 2022-05-24 | 2022-05-24 | Random attack survivability evaluation method based on network digital twin |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115189908B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115865761A (en) * | 2022-12-07 | 2023-03-28 | 安世亚太科技股份有限公司 | Network entity task activity cost evaluation method considering blocking feedback |
| CN117933840A (en) * | 2024-03-21 | 2024-04-26 | 中国民用航空总局第二研究所 | Digital twin-driven flight ground guarantee delay diagnosis method, system and equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107204871A (en) * | 2017-04-19 | 2017-09-26 | 天津大学 | Wireless sensor network biological treatability appraisal procedure based on Evolutionary Game Model |
| CN108847969A (en) * | 2018-06-05 | 2018-11-20 | 北京航空航天大学 | Network business reliability analysis method based on information flow |
| CN111295660A (en) * | 2017-11-02 | 2020-06-16 | 区块链控股有限公司 | Computer-implemented system and method for connecting blockchains to digital twins |
| CN114448487A (en) * | 2020-10-30 | 2022-05-06 | 安世亚太科技股份有限公司 | Digital twin body of satellite network management and control system and efficiency evaluation method thereof |
-
2022
- 2022-05-24 CN CN202210569319.0A patent/CN115189908B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107204871A (en) * | 2017-04-19 | 2017-09-26 | 天津大学 | Wireless sensor network biological treatability appraisal procedure based on Evolutionary Game Model |
| CN111295660A (en) * | 2017-11-02 | 2020-06-16 | 区块链控股有限公司 | Computer-implemented system and method for connecting blockchains to digital twins |
| US20200295936A1 (en) * | 2017-11-02 | 2020-09-17 | nChain Holdings Limited | Computer-implemented systems and methods for linking a blockchain to a digital twin |
| CN108847969A (en) * | 2018-06-05 | 2018-11-20 | 北京航空航天大学 | Network business reliability analysis method based on information flow |
| CN114448487A (en) * | 2020-10-30 | 2022-05-06 | 安世亚太科技股份有限公司 | Digital twin body of satellite network management and control system and efficiency evaluation method thereof |
Non-Patent Citations (1)
| Title |
|---|
| 陈婉玲;刘青松;林洁群;: "浅析人工智能在数字孪生城市中的应用", 信息通信技术与政策, no. 03 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115865761A (en) * | 2022-12-07 | 2023-03-28 | 安世亚太科技股份有限公司 | Network entity task activity cost evaluation method considering blocking feedback |
| CN117933840A (en) * | 2024-03-21 | 2024-04-26 | 中国民用航空总局第二研究所 | Digital twin-driven flight ground guarantee delay diagnosis method, system and equipment |
| CN117933840B (en) * | 2024-03-21 | 2024-05-31 | 中国民用航空总局第二研究所 | Digital twin-driven flight ground guarantee delay diagnosis method, system and equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115189908B (en) | 2024-05-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112181666B (en) | Equipment assessment and federal learning importance aggregation method based on edge intelligence | |
| CN109862610B (en) | D2D user resource allocation method based on deep reinforcement learning DDPG algorithm | |
| CN115189908A (en) | Random attack survivability evaluation method based on network digital twin | |
| CN111629380B (en) | Dynamic resource allocation method for high concurrency multi-service industrial 5G network | |
| CN113315978B (en) | Collaborative online video edge caching method based on federal learning | |
| CN111526208A (en) | High-concurrency cloud platform file transmission optimization method based on micro-service | |
| Huang et al. | Enabling DNN acceleration with data and model parallelization over ubiquitous end devices | |
| CN110620820A (en) | Ubiquitous power Internet of things intelligent management system | |
| CN116669111A (en) | Mobile edge computing task unloading method based on blockchain | |
| CN114372581A (en) | Block chain-based federal learning method and device and computer equipment | |
| CN116579418A (en) | Privacy data protection method for model segmentation optimization under federal edge learning environment | |
| CN115190027A (en) | Natural fault survivability evaluation method based on network digital twin body | |
| CN115189910A (en) | Network digital twin-based deliberate attack survivability evaluation method | |
| CN112115499A (en) | Safe transmission method based on block chain and edge cache | |
| TW202327380A (en) | Method and system for federated reinforcement learning based offloading optimization in edge computing | |
| CN107707383B (en) | Put-through processing method and device, first network element and second network element | |
| CN112491508A (en) | Data transmission method and device based on transmission process self-adaption | |
| Jing et al. | Enhancing Soft AC Based Reliable Offloading for IoV with Edge Computing | |
| CN112906745A (en) | Integrity intelligent network training method based on edge cooperation | |
| CN117724853B (en) | Data processing method and device based on artificial intelligence | |
| CN117978623B (en) | Method, device and equipment for constructing tough data sharing network for coping with network attack | |
| CN114385359B (en) | Cloud edge task time sequence cooperation method for Internet of things | |
| CN113645055B (en) | Implementation method suitable for multi-factor routing protocol in complex battlefield environment | |
| CN111813539B (en) | Priority and collaboration-based edge computing resource allocation method | |
| CN117237004B (en) | Energy storage device transaction processing method and device and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |