CN115514645B - A reliability-based underlying network resource backup method and device - Google Patents
A reliability-based underlying network resource backup method and device Download PDFInfo
- Publication number
- CN115514645B CN115514645B CN202211144070.5A CN202211144070A CN115514645B CN 115514645 B CN115514645 B CN 115514645B CN 202211144070 A CN202211144070 A CN 202211144070A CN 115514645 B CN115514645 B CN 115514645B
- Authority
- CN
- China
- Prior art keywords
- resource
- resources
- reliability
- network
- virtual
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 26
- 238000012163 sequencing technique Methods 0.000 claims abstract description 36
- 238000013507 mapping Methods 0.000 claims description 15
- 238000004891 communication Methods 0.000 claims description 13
- 238000000354 decomposition reaction Methods 0.000 claims description 11
- 238000013468 resource allocation Methods 0.000 description 10
- 238000004458 analytical method Methods 0.000 description 6
- 238000004808 supercritical fluid chromatography Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000015556 catabolic process Effects 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Classifications
-
- 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
- H04L41/08—Configuration management of networks or network elements
- H04L41/0893—Assignment of logical groups to network elements
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1095—Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The invention discloses a reliability-based bottom network resource backup method and device, wherein the method comprises the steps of respectively calculating failure rate, service rate and utilization rate corresponding to bottom core resources and bottom edge resources, obtaining reliability of all resource subnetworks in the bottom core resources, and sequencing the reliability of all resource subnetworks in the bottom edge resources according to the reliability, wherein each resource subnetwork comprises bottom nodes and bottom links, and respectively backing up all resource subnetworks in the bottom core resources and backing up all bottom resource subnetworks in the bottom edge resources according to a sequencing result of the reliability by using reserved backup resources. By adopting the invention, the unreliable bottom layer resources are quickly and effectively backed up according to the effective distinction between the core resources and the edge resources of the bottom layer network and the reliability sequencing result of each sub-resource.
Description
Technical Field
The invention relates to the field of operation and maintenance of power communication networks, in particular to a bottom network resource backup method and device based on reliability.
Background
With the rapid increase in the number and types of power services, the resource requirements of power services for power communication networks have increased rapidly. To address the problem of insufficient power communication network resources, network function virtualization (network function virtualization, NFV) techniques are proposed. In the NFV environment, the legacy network is divided into an underlying network and a chain of service functions (service function chain, SFC). The underlying network may employ virtualization techniques to virtualize a single physical network device into multiple virtual network elements. The service function chain can be quickly constructed according to the service requirements. As each SFC needs to share underlying network resources with other SFCs, the SFC is more prone to failure or performance degradation. Therefore, NFV technology improves the utilization of underlying network resources, but the reliability of SFC is reduced.
Disclosure of Invention
The embodiment of the invention provides a bottom network resource backup method and device based on reliability, which are used for quickly and effectively backing up unreliable bottom resources.
In order to achieve the above objective, a first aspect of the embodiments of the present application provides a reliability-based backup method for a bottom network resource, which includes performing network virtualization on a target power communication network to obtain a bottom network structure and a virtual network structure;
dividing the virtual network structure to obtain virtual core resources and virtual edge resources in the virtual network structure;
obtaining a bottom core resource and a bottom edge resource in the bottom network structure according to the mapping relation between the bottom network structure and the virtual network structure;
Respectively calculating failure rate, service rate and utilization rate corresponding to the bottom core resource and the bottom edge resource, obtaining reliability of each resource subnet in the bottom core resource and reliability of each resource subnet in the bottom edge resource, and sequencing according to the reliability;
and according to the sequencing result of the reliability, respectively backing up each resource subnet in the bottom layer core resources and backing up each bottom layer resource subnet in the bottom layer edge resources by using reserved backup resources.
In a possible implementation manner of the first aspect, the partitioning the virtual network structure to obtain a virtual core resource and a virtual edge resource in the virtual network structure specifically includes:
and dividing the virtual network structure by adopting a K-core decomposition theory, dividing the nodes and corresponding links of two cores and below into bottom layer edge resources, and dividing the nodes and corresponding links of three cores and above into bottom layer core resources.
In a possible implementation manner of the first aspect, the mapping relationship between the underlying network structure and the virtual network structure specifically is:
the virtual nodes of the virtual network structure are borne on the bottom layer nodes of the bottom layer network structure, and the virtual links of the virtual network structure are borne on the bottom layer paths of the bottom layer network structure.
In a possible implementation manner of the first aspect, the calculating, respectively, the failure rate, the service rate, and the utilization rate corresponding to the bottom core resource and the bottom edge resource, to obtain the reliability of each resource subnet in the bottom core resource and the reliability of each resource subnet in the bottom edge resource specifically includes:
The reliability of the bottom layer core resource or the bottom layer edge resource is a linear weighted sum of the corresponding failure rate, the corresponding service rate and the corresponding utilization rate, and in the linear weighting, the failure rate weighting factor, the service rate weighting factor and the utilization rate weighting factor are required to be set according to the routing strategy of the target power communication network.
In a possible implementation manner of the first aspect, the failure rate includes a node failure rate and a link failure rate;
The node failure rate is the ratio of the number of times of node failure to the maximum value of the number of times of node failure in a period of time;
the link failure rate is the ratio of the number of times of occurrence of link failure to the maximum value of the number of times of link failure in a period of time.
In a possible implementation manner of the first aspect, the service ratio is a ratio of a number of network bearer type services to a maximum value of the number of bearer services.
In a possible implementation manner of the first aspect, the utilization rate includes a node utilization rate and a link utilization rate;
The node utilization rate is the ratio of the available bandwidth quantity of the current node to the total bandwidth quantity of the current node;
The link utilization is the ratio of the current link available bandwidth amount to the current link total bandwidth amount.
In a possible implementation manner of the first aspect, the sorting and sorting according to the reliability size specifically includes:
And respectively carrying out descending arrangement according to the reliability of each resource subnet in the bottom layer core resource and the reliability of each resource subnet in the bottom layer edge resource.
In a possible implementation manner of the first aspect, the backing up each sub-network of core resources in the bottom layer core resources and backing up each sub-network of bottom layer resources in the bottom layer edge resources by using reserved backup resources according to the sequencing result of reliability specifically includes:
Backing up the last core resource sub-network in the bottom layer core resource sequencing result for a plurality of times, and removing the core resource sub-network from the sequencing result after backing up until reserved backup resources reach the residual proportional capacity;
and backing up the last edge resource sub-network in the edge core resource sequencing result for a plurality of times, and removing the edge resource sub-network from the sequencing result after backing up until the reserved backup resource reaches the residual proportional capacity.
The second aspect of the embodiment of the application provides a bottom network resource backup device based on reliability, which comprises a virtual module, a first network resource backup module, a second network resource backup module and a third network resource backup module, wherein the virtual module is used for carrying out network virtualization on a target power communication network to obtain a bottom network structure and a virtual network structure;
the division module is used for dividing the virtual network structure to obtain virtual core resources and virtual edge resources in the virtual network structure;
The mapping module is used for obtaining a bottom core resource and a bottom edge resource in the bottom network structure according to the mapping relation between the bottom network structure and the virtual network structure;
The sequencing module is used for respectively calculating the failure rate, the service rate and the utilization rate corresponding to the bottom core resource and the bottom edge resource, obtaining the reliability of each resource subnet in the bottom core resource and the reliability of each resource subnet in the bottom edge resource and sequencing according to the reliability;
and the backup module is used for backing up each resource subnet in the bottom layer core resources and backing up each bottom layer resource subnet in the bottom layer edge resources respectively by using reserved backup resources according to the sequencing result of the reliability.
Compared with the prior art, the method and the device for backing up the bottom network resources based on the reliability provided by the embodiment of the invention have the advantages that the core resources and the edge resources of the virtual network are identified by adopting the K-kernel decomposition iterative algorithm, then the bottom network resources corresponding to the virtual network are accurately found according to the mapping relation, and the reliability ordering is carried out on each sub-resource in the bottom network resources according to the operation parameters of the bottom network resources. The core resources and the edge resources of the bottom layer network are effectively distinguished, and the reliability sequencing is carried out on each sub-resource, so that the reasonability of subsequent allocation as backup resources is guaranteed, more backup resources are concentrated to be used for the unreliable resources, especially the backups of the unreliable sub-resources in the core resources of the bottom layer network, and the availability and the resource allocation rate of the virtual network are further effectively improved.
Drawings
FIG. 1 is a schematic flow chart of a reliability-based underlying network resource backup method according to an embodiment of the present invention;
FIG. 2 is a graph showing a comparison of virtual network availability after using different backup methods according to an embodiment of the present invention;
fig. 3 is a comparison chart of virtual network resource allocation success rates after using different backup methods according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, an embodiment of the present invention provides a reliability-based backup method for bottom-layer network resources, including:
and S10, carrying out network virtualization on the target power communication network to obtain a bottom network structure and a virtual network structure.
S11, dividing the virtual network structure to obtain virtual core resources and virtual edge resources in the virtual network structure.
And S12, obtaining a bottom layer core resource and a bottom layer edge resource in the bottom layer network structure according to the mapping relation between the bottom layer network structure and the virtual network structure.
S13, respectively calculating failure rates, service rates and utilization rates corresponding to the bottom core resources and the bottom edge resources, obtaining reliability of each resource subnet in the bottom core resources and reliability of each resource subnet in the bottom edge resources, and sequencing according to the reliability, wherein each resource subnet comprises bottom nodes and bottom links.
And S14, backing up each resource subnet in the bottom layer core resources and backing up each bottom layer resource subnet in the bottom layer edge resources respectively by using reserved backup resources according to the sequencing result of the reliability.
In a network virtualization environment, a conventional network is divided into an underlying network and a virtual network. The underlying network using undirected graph G c＝(Nc,Ec) is built by the underlying network service provider and is primarily responsible for providing the underlying network resources. The underlying network includes an underlying node and an underlying link, each represented by an underlying node set using N c, and E c represents an underlying link set. Bottom layer nodeHaving computing resource attributes, useAnd (3) representing. Underlying linksHaving bandwidth resource attributes, usageAnd (3) representing.
Virtual network usage G v＝(Nv,Ev) is represented by the service provider, which is primarily responsible for carrying specific power traffic. The invention mainly researches the virtual network of the service function chain type. The virtual network includes virtual nodes and virtual link resources, and each uses N v to represent a virtual node set of a service function chain, and E v to represent a virtual link set of the service function chain. Virtual nodeHaving computing resource attributes, useAnd (3) representing. Virtual linksHaving bandwidth resource attributes, usageAnd (3) representing.
When the backup of the resources of the bottom network is studied, the topology characteristics of the bottom network are ignored, and the problem of low resource backup efficiency exists. Therefore, the embodiment of the invention divides network resources based on network characteristics and K kernel decomposition theory, and adopts a targeted resource backup strategy according to the resource characteristics.
Illustratively, S11 specifically includes:
and dividing the virtual network structure by adopting a K-core decomposition theory, dividing the nodes and corresponding links of two cores and below into bottom layer edge resources, and dividing the nodes and corresponding links of three cores and above into bottom layer core resources.
Because the topology of the virtual network is generally widely distributed, network resources at different locations have different characteristics. For example, when a network node has more edges in the network, the current node has higher reliability. Conversely, when an underlying node has only one edge connected, the probability that the node is unavailable is greater. To analyze the characteristics of network resources in a network, embodiments of the present invention analyze from a graphical perspective. The graph analysis tool is compared with the K kernel decomposition theory, so that the K kernel decomposition theory is a graph analysis tool with good use effect. The K kernel decomposition adopts a multiple iteration mechanism, so that network resources of different layers in the network topology can be obtained very efficiently.
Based on the analysis, the invention adopts K kernel decomposition theory to divide the network. The nodes and links below the core are edge networks, and the core networks are core networks. The number of degrees 1 and 2 is limited, and 3 or more nodes with high reliability are found. And adopting an iterative clipping strategy, and firstly deleting the node with the degree of 1 and the connected links. And secondly, deleting the node with the degree of 2 and the connected links. At this time, the remaining nodes are all nodes with a degree of 3.
And then dividing the bottom layer resources bearing the virtual network structure into bottom layer core resources and bottom layer edge resources.
The mapping relationship between the underlying network structure and the virtual network structure specifically includes:
the virtual nodes of the virtual network structure are borne on the bottom layer nodes of the bottom layer network structure, and the virtual links of the virtual network structure are borne on the bottom layer paths of the bottom layer network structure.
The calculating the failure rate, the service rate and the utilization rate corresponding to the bottom core resource and the bottom edge resource respectively, to obtain the reliability of each resource subnet in the bottom core resource and the reliability of each resource subnet in the bottom edge resource specifically includes:
The reliability of the bottom layer core resource or the bottom layer edge resource is a linear weighted sum of the corresponding failure rate, the corresponding service rate and the corresponding utilization rate, and in the linear weighting, the failure rate weighting factor, the service rate weighting factor and the utilization rate weighting factor are required to be set according to the routing strategy of the target power communication network.
Illustratively, the failure rates include a node failure rate and a link failure rate;
The node failure rate is the ratio of the number of times of node failure to the maximum value of the number of times of node failure in a period of time;
the link failure rate is the ratio of the number of times of occurrence of link failure to the maximum value of the number of times of link failure in a period of time.
The more times a failure occurs over a period of time, the more likely the current physical resource fails. The failure rate of nodes and links is expressed in terms of the number of failures that occur over a period of time. The physical resources include physical nodes and physical links, collectively denoted by re i. Failure rate of physical node and physical link respectivelyAndThe expression is calculated using the formula (1) and the formula (2), respectively.Representing the maximum number of node failures occurring over a period of time.Representing physical nodes over a period of timeThe number of failures occurred.Representing the maximum number of failures of the link over a period of time.Representing physical links over a period of timeThe number of failures occurred.
Illustratively, the traffic ratio is a ratio of a number of network bearer type traffic to a maximum number of bearer traffic.
Illustratively, the utilization includes node utilization and link utilization;
The node utilization rate is the ratio of the available bandwidth quantity of the current node to the total bandwidth quantity of the current node;
The link utilization is the ratio of the current link available bandwidth amount to the current link total bandwidth amount.
The more the number of services carried on the physical resources in a period of time, the higher the importance of the current resources, and the more the backup is needed. BN (re i) represents the traffic ratio on the physical resource, calculated using equation (3).Indicating the number of j-th traffic carried on the physical resource re i. maxBN denotes the maximum number of traffic carried on a single underlying network resource. The greater the number of services, the more reliability needs to be improved.
Illustratively, the sorting according to the reliability size specifically includes:
And respectively carrying out descending arrangement according to the reliability of each resource subnet in the bottom layer core resource and the reliability of each resource subnet in the bottom layer edge resource.
The greater the utilization of the physical resource over a period of time, the more likely the resource fails, and the more needed the backup. Physical nodeResource utilization of (2)Calculated using equation (4). Wherein, Representing a current physical nodeIs used to determine the amount of available bandwidth,Representing a current physical nodeIs used to determine the total bandwidth amount of the system.
Physical linkResource utilization of (2)Calculated using equation (5). Wherein, Representing a current physical linkIs used to determine the amount of available bandwidth,Representing a current physical linkIs used to determine the total bandwidth amount of the system.
In order to improve the effect of the analysis of the reliability of the resources, the invention firstly calculates the reliability of the network resources and secondly analyzes the characteristics of various resources based on the characteristics of the reliability of the resources.
Reliability of physical resource re i Calculated using equation (6).
The degree of a node is expressed in terms of the number of edges that the node connects. The degree of a link is represented using the sum of the degrees of the two nodes of the link. In the aspect of the characteristics of the edge nodes and the links, the number of the nodes and the links is large for meeting the purpose of access, but the degrees of the nodes and the links and the number of the connected nodes are small. Under the dynamic routing strategy, the number of alternative nodes and links to be replaced is small, and the range of influence is relatively small when the failure rate is high. In the aspect of the characteristics of the core nodes and the links, the data exchange is aimed at, the number of the nodes and the links is large, and the types and the number of the loaded services are large. The reliability is relatively high by adopting multi-link and multi-node redundancy backup. The resource utilization rate is easily too high, and the reliability is easily not ensured.
In the embodiment of the invention, the reliability (Reliability of edge nodes and links) weights of the edge nodes and the links are distributed according to the network operation experience, wherein the weight of the failure rate is 45%, the weight of the traffic is 30% and the weight of the resource utilization rate is 25%. The reliability (Reliability of core nodes and links) weight of the core node and the link is distributed as 45% weight of the traffic, 35% weight of the resource utilization and 20% weight of the failure rate. The above weight factors need to be set according to the actual power grid communication network structure and the running state.
Illustratively, S14 specifically includes:
Backing up the last core resource sub-network in the bottom layer core resource sequencing result for a plurality of times, and removing the core resource sub-network from the sequencing result after backing up until reserved backup resources reach the residual proportional capacity;
and backing up the last edge resource sub-network in the edge core resource sequencing result for a plurality of times, and removing the edge resource sub-network from the sequencing result after backing up until the reserved backup resource reaches the residual proportional capacity.
Compared with the prior art, the bottom network resource backup method based on reliability provided by the embodiment of the invention has the advantages that the core resource and the edge resource of the virtual network are identified by adopting the K-kernel decomposition iterative algorithm, then the bottom network resource corresponding to the virtual network is accurately found according to the mapping relation, and the reliability ordering is carried out on each sub-resource in the bottom network resource according to the operation parameters of the bottom network resource. The core resources and the edge resources of the bottom layer network are effectively distinguished, and the reliability sequencing is carried out on each sub-resource, so that the reasonability of subsequent allocation as backup resources is guaranteed, more backup resources are concentrated to be used for the unreliable resources, especially the backups of the unreliable sub-resources in the core resources of the bottom layer network, and the availability and the resource allocation rate of the virtual network are further effectively improved.
In order to analyze the performance of the underlying network resource backup method (SFCRIAoRC) based on reliability adopted in the embodiment of the present invention, a GT-ITM tool is used in the verification experiment to generate the network environment. The generated network environment is composed of an underlying network and a service function chain. The underlay network uses a different number of underlay network nodes to simulate. The bottom network link adopts two bottom nodes to connect with a certain probability for simulation. The underlying network resource reliability promotion algorithm (SNRRIAoRI) that is based on resource importance is a common algorithm for resource backup. The algorithm uses the backup resource to backup the most important bottom layer resource, thereby improving the reliability of the bottom layer network. In order to simulate the network environment with limited backup resources, the bottom network resources with the backup capacity being 15% of the total amount of resources are adopted as backup resources.
To compare the performance of the two algorithms, the algorithm performance is compared from two dimensions of the availability of the virtual network and the resource allocation success rate of the virtual network. And when algorithm performance is compared, the bottom base link of [2%,3% ] is randomly selected from the bottom links as a fault link.
The result of the comparison of the availability of the virtual network is shown in fig. 2. As can be seen from fig. 2, the availability of the virtual network for both algorithms is relatively stable under different network environments. It is explained that both algorithms can get converged results under different network environments. The result analysis of the two algorithms shows that the virtual network availability is higher under the algorithm of the invention. The method is characterized in that the core and edge characteristics of the resources are used as important factors of resource backup, so that the reliability of the bottom network resources is improved. After the reliability of the bottom network resources is improved, more virtual network availability can be ensured.
The comparison result of the resource allocation success rate of the virtual network is shown in fig. 3. As can be seen from fig. 3, the resource allocation success rate of the virtual network of both algorithms is gradually improved under different network environments. After the network scale is increased, the two algorithms can use more bottom layer network resources, so that the resource allocation success rate of the virtual network is improved. The analysis of experimental results of the two algorithms shows that the resource allocation success rate of the virtual network under the algorithm of the invention is higher. The method is characterized in that the core and edge characteristics of the resources are used as important factors of resource backup, so that the reliability of the bottom network resources is improved. After the reliability of the bottom layer network resources is improved, more available resources can be provided for the virtual network, so that the resource allocation success rate of the virtual network is improved.
The embodiment of the application provides a bottom network resource backup device based on reliability, which comprises a virtual module, a dividing module, a mapping module, a sequencing module and a backup module.
And the virtual module is used for carrying out network virtualization on the target power communication network to obtain a bottom network structure and a virtual network structure.
The division module is used for dividing the virtual network structure to obtain virtual core resources and virtual edge resources in the virtual network structure.
And the mapping module is used for obtaining the bottom core resource and the bottom edge resource in the bottom network structure according to the mapping relation between the bottom network structure and the virtual network structure.
The sequencing module is used for respectively calculating the failure rate, the service rate and the utilization rate corresponding to the bottom core resource and the bottom edge resource, obtaining the reliability of each resource subnet in the bottom core resource and the reliability of each resource subnet in the bottom edge resource, and sequencing according to the reliability, wherein each resource subnet comprises a bottom node and a bottom link.
And the backup module is used for backing up each resource subnet in the bottom layer core resources and backing up each bottom layer resource subnet in the bottom layer edge resources respectively by using reserved backup resources according to the sequencing result of the reliability.
Compared with the prior art, the bottom network resource backup device based on reliability provided by the embodiment of the invention has the advantages that the core resource and the edge resource of the virtual network are identified by adopting the K-kernel decomposition iterative algorithm, then the bottom network resource corresponding to the virtual network is accurately found according to the mapping relation, and the reliability ordering is carried out on each sub-resource in the bottom network resource according to the operation parameters of the bottom network resource. The core resources and the edge resources of the bottom layer network are effectively distinguished, and the reliability sequencing is carried out on each sub-resource, so that the reasonability of subsequent allocation as backup resources is guaranteed, more backup resources are concentrated to be used for the unreliable resources, especially the backups of the unreliable sub-resources in the core resources of the bottom layer network, and the availability and the resource allocation rate of the virtual network are further effectively improved.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that changes and modifications may be made without departing from the principles of the invention, such changes and modifications are also intended to be within the scope of the invention.
Claims (9)
1. A bottom network resource backup method based on reliability is characterized by comprising the following steps of
Network virtualization is carried out on the target power communication network to obtain a bottom network structure and a virtual network structure;
dividing the virtual network structure to obtain virtual core resources and virtual edge resources in the virtual network structure;
Obtaining a bottom core resource and a bottom edge resource in the bottom network structure according to the mapping relation between the bottom network structure and the virtual network structure, wherein the virtual nodes of the virtual network structure are born on the bottom nodes of the bottom network structure, and the virtual links of the virtual network structure are born on the bottom paths of the bottom network structure;
Respectively calculating failure rate, service rate and utilization rate corresponding to the bottom core resource and the bottom edge resource, obtaining reliability of each resource subnet in the bottom core resource and reliability of each resource subnet in the bottom edge resource, and sequencing according to the reliability;
and according to the sequencing result of the reliability, respectively backing up each resource subnet in the bottom layer core resources and backing up each bottom layer resource subnet in the bottom layer edge resources by using reserved backup resources.
2. The method for backing up bottom layer network resources based on reliability according to claim 1, wherein the dividing the virtual network structure to obtain virtual core resources and virtual edge resources in the virtual network structure specifically comprises:
and dividing the virtual network structure by adopting a K-core decomposition theory, dividing the nodes and corresponding links of two cores and below into bottom layer edge resources, and dividing the nodes and corresponding links of three cores and above into bottom layer core resources.
3. The method for backing up bottom network resources based on reliability according to claim 1, wherein the calculating the failure rate, the service rate and the utilization rate corresponding to the bottom core resources and the bottom edge resources respectively to obtain the reliability of each resource subnet in the bottom core resources and the reliability of each resource subnet in the bottom edge resources specifically includes:
The reliability of the bottom layer core resource or the bottom layer edge resource is a linear weighted sum of the corresponding failure rate, the corresponding service rate and the corresponding utilization rate, and in the linear weighting, the failure rate weighting factor, the service rate weighting factor and the utilization rate weighting factor are required to be set according to the routing strategy of the target power communication network.
4. The reliability-based underlying network resource backup method of claim 3, wherein the failure rate comprises a node failure rate and a link failure rate;
The node failure rate is the ratio of the number of times of node failure to the maximum value of the number of times of node failure in a period of time;
the link failure rate is the ratio of the number of times of occurrence of link failure to the maximum value of the number of times of link failure in a period of time.
5. The method for backing up underlying network resources based on reliability as recited in claim 3, wherein said traffic ratio is a ratio of a number of network bearer type traffic to a maximum number of bearer traffic.
6. The reliability-based underlying network resource backup method of claim 3, wherein the utilization comprises node utilization and link utilization;
The node utilization rate is the ratio of the available bandwidth quantity of the current node to the total bandwidth quantity of the current node;
The link utilization is the ratio of the current link available bandwidth amount to the current link total bandwidth amount.
7. The method for backing up underlying network resources based on reliability according to claim 1, wherein said ranking is performed according to reliability, and specifically comprises:
And respectively carrying out descending arrangement according to the reliability of each resource subnet in the bottom layer core resource and the reliability of each resource subnet in the bottom layer edge resource.
8. The method for backing up bottom layer network resources based on reliability according to claim 7, wherein the backing up of each core resource subnet in the bottom layer core resources and backing up of each bottom layer resource subnet in the bottom layer edge resources are respectively performed by using reserved backup resources according to the sequencing result of reliability, specifically comprising:
Backing up the last core resource sub-network in the bottom layer core resource sequencing result for a plurality of times, and removing the core resource sub-network from the sequencing result after backing up until reserved backup resources reach the residual proportional capacity;
And backing up the last edge resource sub-network in the edge core resource sequencing result for a plurality of times, and removing the edge resource sub-network from the sequencing result after backing up until the reserved backup resource reaches the residual proportional capacity.
9. A reliability-based underlying network resource backup apparatus, comprising:
the virtual module is used for carrying out network virtualization on the target power communication network to obtain a bottom network structure and a virtual network structure;
the division module is used for dividing the virtual network structure to obtain virtual core resources and virtual edge resources in the virtual network structure;
The mapping module is used for obtaining a bottom core resource and a bottom edge resource in the bottom network structure according to the mapping relation between the bottom network structure and the virtual network structure, specifically, the virtual node of the virtual network structure is borne on the bottom node of the bottom network structure, and the virtual link of the virtual network structure is borne on the bottom path of the bottom network structure;
The sequencing module is used for respectively calculating the failure rate, the service rate and the utilization rate corresponding to the bottom core resource and the bottom edge resource, obtaining the reliability of each resource subnet in the bottom core resource and the reliability of each resource subnet in the bottom edge resource and sequencing according to the reliability;
and the backup module is used for backing up each resource subnet in the bottom layer core resources and backing up each bottom layer resource subnet in the bottom layer edge resources respectively by using reserved backup resources according to the sequencing result of the reliability.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211144070.5A CN115514645B (en) | 2022-09-20 | 2022-09-20 | A reliability-based underlying network resource backup method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211144070.5A CN115514645B (en) | 2022-09-20 | 2022-09-20 | A reliability-based underlying network resource backup method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115514645A CN115514645A (en) | 2022-12-23 |
| CN115514645B true CN115514645B (en) | 2024-12-03 |
Family
ID=84504187
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211144070.5A Active CN115514645B (en) | 2022-09-20 | 2022-09-20 | A reliability-based underlying network resource backup method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115514645B (en) |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114157583A (en) * | 2021-11-18 | 2022-03-08 | 广东电网有限责任公司 | Reliability-based network resource heuristic mapping method and system |
Family Cites Families (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003060696A (en) * | 2001-08-14 | 2003-02-28 | Oki Electric Ind Co Ltd | Router system |
| CN100499636C (en) * | 2004-06-14 | 2009-06-10 | 华为技术有限公司 | Method for guaranteeing end-to-end service quality reliability |
| US8990397B2 (en) * | 2009-07-31 | 2015-03-24 | Ntt Docomo, Inc. | Resource allocation protocol for a virtualized infrastructure with reliability guarantees |
| US10298977B2 (en) * | 2009-11-20 | 2019-05-21 | Time Warner Cable Enterprises Llc | Policy management arbitration by service group |
| US10097372B2 (en) * | 2014-01-09 | 2018-10-09 | Ciena Corporation | Method for resource optimized network virtualization overlay transport in virtualized data center environments |
| US10924363B2 (en) * | 2018-04-13 | 2021-02-16 | The Curators Of The University Of Missouri | Method and system for secure resource management utilizing blockchain and smart contracts |
| CN109639498B (en) * | 2018-12-27 | 2021-08-31 | 国网江苏省电力有限公司南京供电分公司 | A Quality of Service-Oriented Resource Flexible Allocation Method Based on SDN and NFV |
| CN111147307B (en) * | 2019-12-30 | 2022-04-29 | 重庆邮电大学 | Reliable deployment method of service function chain based on deep reinforcement learning |
| CN111526057B (en) * | 2020-04-30 | 2022-10-25 | 西安邮电大学 | A Service Type-Based Network Slicing Reliability Mapping Method |
| CN112636961B (en) * | 2020-12-15 | 2022-11-08 | 国网河南省电力公司信息通信公司 | Virtual network resource allocation method based on reliability and distribution strategy under network slice |
| CN113114514B (en) * | 2021-05-07 | 2022-06-14 | 广东电网有限责任公司电力调度控制中心 | Network resource backup method and system based on multi-attribute analytic hierarchy process |
-
2022
- 2022-09-20 CN CN202211144070.5A patent/CN115514645B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114157583A (en) * | 2021-11-18 | 2022-03-08 | 广东电网有限责任公司 | Reliability-based network resource heuristic mapping method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115514645A (en) | 2022-12-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112015583B (en) | A method, device and system for data storage | |
| CN107562531B (en) | A data equalization method and device | |
| US8478878B2 (en) | Placement of virtual machines based on server cost and network cost | |
| US20140149493A1 (en) | Method for joint service placement and service routing in a distributed cloud | |
| Beechu et al. | An energy-efficient fault-aware core mapping in mesh-based network on chip systems | |
| CN109451540A (en) | A kind of resource allocation methods and equipment of network slice | |
| CN114157583B (en) | Reliability-based network resource heuristic mapping method and system | |
| CN109347657B (en) | Method for constructing virtual data domain of scientific and technological service under SDN mode | |
| CN111682962A (en) | Power data network fault recovery method, system and storage medium | |
| CN112636961A (en) | Virtual network resource allocation method based on reliability and distribution strategy under network slice | |
| Samani et al. | Multilayer resource-aware partitioning for fog application placement | |
| CN111160661B (en) | Method, system and equipment for optimizing reliability of power communication network | |
| CN115514645B (en) | A reliability-based underlying network resource backup method and device | |
| CN112543920A (en) | Data reconstruction method, device, computer equipment, storage medium and system | |
| CN111181761B (en) | CDN node deployment method and device | |
| CN115361295B (en) | TOPSIS-based resource backup method, device, equipment and medium | |
| Liu et al. | Disaster-prediction based virtual network mapping against multiple regional failures | |
| Randles et al. | Biased random walks on resource network graphs for load balancing | |
| Huang et al. | Reliable redundant services placement in federated micro-clouds | |
| Nanda et al. | TAG: Traffic-Aware Global Live Migration to Enhance User Experience of Cloud Applications | |
| CN108183826B (en) | Multi-scale fusion network simulation task mapping method under heterogeneous environment | |
| CN114422375B (en) | Virtual network resource allocation method, device, medium and program product | |
| CN117544513B (en) | Novel Internet of things customized service providing method and device based on fog resources | |
| CN115378817B (en) | Resource backup method, device, equipment and storage medium of service function chain | |
| Hsu et al. | Adaptive replication for real-time applications based on mobile edge computing |
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 |