CN109242242B - Method and system for determining risk modeling of system protection private network business - Google Patents
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Abstract
The invention provides a method and a system for determining service risk of a system protection private network, and belongs to the field of communication of the system protection private network. The method comprises the following steps: step one, carrying out fault location on a system protection private network, determining a fault type and giving an alarm according to the fault type; step two, establishing a rerouting mechanism based on business risks to construct a route optimization mathematical model; and step three, constructing a route optimization model according to the route optimization mathematical model constructed by the rerouting mechanism based on the service risk and the stable control service borne on the communication link triggering automatic rerouting. The invention realizes the minimum weighted sum of the average transmission delay of the service and the balance degree of the whole network service. The invention effectively reduces the operation risk of the service, avoids the service loss and further enhances the robustness and the flexibility of the real-time system protection private network communication system.
Description
Technical Field
The present invention relates to the field of communications for systems protection private network networks, and more particularly to a method and system for determining risk modeling for systems protection private network services.
Background
Compared with the traditional WDM network, the Mesh networking is one of the main networking modes of the ASON network, and has the characteristics of flexibility and easy expansion. Under the networking mode, a plurality of recovery paths can be provided, the network security is improved, and the whole network resource is utilized to the maximum extent. In Mesh networking, in order to reconnect interrupted traffic, in addition to delaying the traditional dedicated protection and shared protection, instant restoration of traffic can be achieved by means of a rerouting mechanism.
The dynamic rerouting is one of core characteristics brought by GMPLS/ASON, is a protection mode giving consideration to both protection capability and resource utilization efficiency, and is revolutionary supplement and improvement to a traditional protection mode. With it, protection/restoration against multiple fiber breaks becomes possible.
Disclosure of Invention
The invention aims to effectively reduce the operation risk of a service, further enhance the robustness and stability of a real-time system protection private network, ensure the stable and reliable operation of a communication network and a power grid system, and provide a method for determining the service risk of the system protection private network, which comprises the following steps:
step one, carrying out fault location on a system protection private network, determining a fault type and giving an alarm according to the fault type;
step two, establishing a rerouting mechanism based on business risks to construct a route optimization mathematical model, specifically:
wherein the content of the first and second substances,
the average communication time of the service is taken as the average communication time of the service, Ti is the time delay of the service i, L is the number of the services, BD is the service balance degree, Li is the number of the services borne on the ith link, m is the number of network links, Tmax is the maximum service time delay, Lmax is the maximum number of the services borne by the links, alpha and beta are two constant coefficients, and the constraint part represents the service time delay constraint and the link service number constraint;
step three, performing a first step of cleaning the substrate,
according to the route optimization mathematical model established by the rerouting mechanism based on the service risk and the stable control service borne on the communication link triggering automatic rerouting, the route optimization model is established, specifically as follows:
initializing a stable control service in a system protection private network, constructing a network topology G (V, E, W), and setting a service list S (vs, vd);
wherein V is a node set, E is a link set, W is weight-time delay of each link, vs is a service starting node, and vd is a service destination node;
deleting the interruption link X in the network topology G to obtain a new network topology G';
searching the first k time delay shortest paths for each service in the service set S to form a service selectable path set Sk;
each service is regarded as a gene of the chromosome, the length of the chromosome is the number of the services, the gene coding adopts natural number coding, and the fitness function of the chromosome i is
Randomly generating an initial population, the selection function being a roulette selection method, chromosome i being selected with a probability of
The crossing process adopts a hybridization operation method based on position, the mutation process is to randomly change the positions of 1 gene in a certain chromosome, and an optimal combination is selected from the selectable path set of the service based on certain iteration times by adopting a traditional genetic algorithm;
and outputting the obtained service path combination, the average service communication time delay and the service balance degree, and judging the service path risk according to the output, wherein the smaller the average service communication time delay is, the lower the service path risk value is, and the service balance degree is at 0.
Optionally, step one is specifically to construct a network topology G, a service set S, and a failure alarm set a, when a random link Li in the network fails Fi, the service Si generates an abnormality at a host node, determines a failure type and generates alarm information Ai, forms a bipartite graph of the failure alarm set a and a suspected failure link set F, preprocesses the bipartite graph, simplifies the bipartite graph, and removes a set FN that must not fail from the set F, and leaves a set FY that must fail and a set FS that must fail; and finally determining the fault elements in the FS by using a fault locating algorithm, thereby determining a fault link set FF in the network.
Optionally, the rerouting mechanism is configured with an LSP from the first node a to the node K through the node D and the node G, and the fiber is broken between the node D and the node G, where the rerouting process is as follows:
after the FIU or OTU of the node D detects the alarm, the master GMPLS module is reported;
the node D is used for checking the affected intelligent service and sending a Notify message to the first node A by a GMPLS module;
after receiving the Notify message, the GMPLS module of the first node A calculates an end-to-end recovery PATH, then sends PATH message to the end node K direction through the intermediate node along the calculated PATH, and establishes reverse cross connection at each node along the PATH;
after receiving the PATH message, the GMPLS module of the end node K sends an RESV message to the first node A through the intermediate node, and positive cross connection is established at each node along the way;
after receiving the RESV message sent by the end node, the first node A opens the alarm monitoring and then sends the PATH message for opening the alarm to the downstream node. After receiving the message, the downstream nodes open the alarm monitoring to the new service path, and after the alarm monitoring of the whole LSP is opened, if the LSP is the unreleasable service, the old path is deleted.
The invention also provides a system for determining the business risk of the system protection private network, which comprises the following steps:
the fault positioning and warning unit is used for positioning the fault of the system protection private network, determining the fault type and giving an alarm according to the fault type;
a mathematical model building unit is used for building a rerouting mechanism based on business risks to build a route optimization mathematical model, and the method specifically comprises the following steps:
wherein the content of the first and second substances,
the average communication time of the service is taken as the average communication time of the service, Ti is the time delay of the service i, L is the number of the services, BD is the service balance degree, Li is the number of the services borne on the ith link, m is the number of network links, Tmax is the maximum service time delay, Lmax is the maximum number of the services borne by the links, alpha and beta are two constant coefficients, and the constraint part represents the service time delay constraint and the link service number constraint;
an optimization model unit is constructed, and a route optimization model is constructed according to the route optimization mathematical model constructed based on the traffic risk rerouting mechanism and the stable control traffic carried on the communication link triggering automatic rerouting, specifically as follows:
initializing a stable control service in a system protection private network, constructing a network topology G (V, E, W), and setting a service list S (vs, vd);
wherein V is a node set, E is a link set, W is weight-time delay of each link, vs is a service starting node, and vd is a service destination node;
deleting the interruption link X in the network topology G to obtain a new network topology G';
searching the first k time delay shortest paths for each service in the service set S to form a service selectable path set Sk;
each service is regarded as a gene of the chromosome, the length of the chromosome is the number of the services, the gene coding adopts natural number coding, and the fitness function of the chromosome i is
Randomly generating an initial population, the selection function being a roulette selection method, chromosome i being selected with a probability of
The crossing process adopts a hybridization operation method based on position, the mutation process is to randomly change the positions of 1 gene in a certain chromosome, and an optimal combination is selected from the selectable path set of the service based on certain iteration times by adopting a traditional genetic algorithm;
and outputting the obtained service path combination, the average service communication time delay and the service balance degree, and judging the service path risk according to the output, wherein the smaller the average service communication time delay is, the lower the service path risk value is, and the service balance degree is at 0.
Optionally, the fault location and warning unit specifically constructs a network topology G, a service set S, and a fault alarm set a, when a random link Li in the network has a fault Fi, the service Si generates an abnormality at a sink node, determines a fault type and generates alarm information Ai, forms a bipartite graph of the fault alarm set a and a suspected fault link set F, preprocesses the bipartite graph, simplifies the bipartite graph, and in the set F, removes a set FN that must not fail, and leaves a set FY that must fail and a set FS that is suspected to fail; and finally determining the fault elements in the FS by using a fault locating algorithm, thereby determining a fault link set FF in the network.
Optionally, the rerouting mechanism is configured with an LSP from the first node a to the node K through the node D and the node G, and the fiber is broken between the node D and the node G, where the rerouting process is as follows:
after the FIU or OTU of the node D detects the alarm, the master GMPLS module is reported;
the node D is used for checking the affected intelligent service and sending a Notify message to the first node A by a GMPLS module;
after receiving the Notify message, the GMPLS module of the first node A calculates an end-to-end recovery PATH, then sends PATH message to the end node K direction through the intermediate node along the calculated PATH, and establishes reverse cross connection at each node along the PATH;
after receiving the PATH message, the GMPLS module of the end node K sends an RESV message to the first node A through the intermediate node, and positive cross connection is established at each node along the way;
after receiving the RESV message sent by the end node, the first node A opens the alarm monitoring and then sends the PATH message for opening the alarm to the downstream node. After receiving the message, the downstream nodes open the alarm monitoring to the new service path, and after the alarm monitoring of the whole LSP is opened, if the LSP is the unreleasable service, the old path is deleted.
The invention has the advantages that:
(1) the invention realizes the minimum weighted sum of the average transmission delay of the service and the balance degree of the whole network service.
(2) The invention effectively reduces the operation risk of the service, avoids the service loss and further enhances the robustness and the flexibility of the real-time system protection private network communication system.
Drawings
FIG. 1 is a flow chart of a rerouting mechanism of a method for determining a risk of a system protecting a private network according to the present invention;
FIG. 2 is a diagram of a fault location and warning model architecture for a method of determining the business risk of a system protection private network in accordance with the present invention;
FIG. 3 is a diagram illustrating a second embodiment of a method for determining risk of a system protecting a private network according to the present invention;
FIG. 4 is a flow chart of a method of fault location and warning for determining a business risk of a system protection private network of the present invention;
FIG. 5 is a schematic diagram of an active convergence algorithm for determining the business risk of a system protection private network according to the present invention;
FIG. 6 is a flow chart of a method for determining business risk of a system protected private network of the present invention;
fig. 7 is a system architecture diagram for determining the business risk of a system protected private network according to the present invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for complete and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, the same units/elements are denoted by the same reference numerals.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
The present invention provides a method for determining a business risk of a system protection private network, as shown in fig. 6, including:
step one, carrying out fault location on a system protection private network, determining a fault type and giving an alarm according to the fault type;
as shown in fig. 4, the specific process of fault location is to construct a network topology G, a service set S, and a fault alarm set a shown in fig. 2 as inputs, to construct a bipartite graph shown in fig. 3, to find all related fault link sets F, to determine a fault type, and to alarm according to the fault type; secondly, preprocessing is carried out, a bipartite graph is simplified, in a set F, a set FN which must not fail is removed, and a set FY which must fail and a set FS which is suspected to fail are left; and finally determining the fault elements in the FS by using a fault locating algorithm, thereby determining a fault link set FF in the network.
As in the network topology G of fig. 2 with traffic S0, S1 and S2, when link L (5,10) fails, traffic S0 and S2 generate alarms a0 and a 2. The set of suspected failed links is { F (7,6), F (6,5), F (2,5), F (5,10), F (10,13) }, and the links { F (7,6), F (6,5) }areexcluded according to the service S1 being good. Finally, a bipartite graph as shown in the above graph is formed, and if the bipartite graph is a single-link failure scene, the failure link is necessarily (5, 10); in the case of a multi-link failure scenario, since a2 can only be caused by F (5,10), the inevitable failed link is (5,10), and the suspected failed links are (2,5) and (10,13), the set of failed links may be { F (2,5), F (5,10) }, { F (10,13), F (5,10) }, or { F (2,5), F (5,10), F (10,13) }.
Wherein the principle of fault localization is shown in fig. 5. FIG. 5 is a simple scenario of fault location, where the alarm information is first preprocessed to obtain the bipartite graph shown in FIG. 5, and the range of suspected faulty links is determined; according to the preprocessed information, determining a route that needs to send a detection service, and sending the detection service, as shown in fig. 5; and accurately positioning the position 1 of the fault link according to the alarm information generated by the detection service. For example, in the graph, link e12 and link e23 failed, resulting in the disruption of traffic spw1 and spw2, a bipartite graph is generated, demonstrating that the set of possible failure paths are { e12, e23} and { e23 }. Then the detection traffic is sent in link e12 and link e23 to determine the combination of the final failed links. The active fusion algorithm only locally sends detection services, the services are only 1 hop, the occupied resources are less, and the detection time is shorter.
Step two, establishing a rerouting mechanism based on business risks to construct a route optimization mathematical model, specifically:
wherein the content of the first and second substances,
the average communication time of the service is taken as the average communication time of the service, Ti is the time delay of the service i, L is the number of the services, BD is the service balance degree, Li is the number of the services borne on the ith link, m is the number of network links, Tmax is the maximum service time delay, Lmax is the maximum number of the services borne by the links, alpha and beta are two constant coefficients, and the constraint part represents the service time delay constraint and the link service number constraint;
as shown in fig. 1, the rerouting mechanism is configured with an LSP from the first node a to the node K through the node D and the node G, and the fiber between the node D and the node G is broken, and the rerouting process is as follows:
after the FIU or OTU of the node D detects the alarm, the master GMPLS module is reported;
the node D is used for checking the affected intelligent service and sending a Notify message to the first node A by a GMPLS module;
after receiving the Notify message, the GMPLS module of the first node A calculates an end-to-end recovery PATH, then sends PATH message to the end node K direction through the intermediate node along the calculated PATH, and establishes reverse cross connection at each node along the PATH;
after receiving the PATH message, the GMPLS module of the end node K sends an RESV message to the first node A through the intermediate node, and positive cross connection is established at each node along the way;
after receiving the RESV message sent by the end node, the first node A opens the alarm monitoring and then sends the PATH message for opening the alarm to the downstream node. After receiving the message, the downstream nodes open the alarm monitoring to the new service path, and after the alarm monitoring of the whole LSP is opened, if the LSP is the unreleasable service, the old path is deleted.
Step three, performing a first step of cleaning the substrate,
according to the route optimization mathematical model established by the rerouting mechanism based on the service risk and the stable control service borne on the communication link triggering automatic rerouting, the route optimization model is established, specifically as follows:
initializing, constructing a network topology G (V, E, W), and setting a service list S (vs, vd);
wherein V is a node set, E is a link set, W is weight-time delay of each link, vs is a service starting node, and vd is a service destination node;
deleting the interruption link X in the network topology G to obtain a new network topology G';
searching the first k time delay shortest paths for each service in the service set S to form a service selectable path set Sk;
each service is regarded as a gene of the chromosome, the length of the chromosome is the number of the services, the gene coding adopts natural number coding, and the fitness function of the chromosome i is
Randomly generating an initial population, the selection function being a roulette selection method, chromosome i being selected with a probability of
The crossing process adopts a hybridization operation method based on position, the mutation process is to randomly change the positions of 1 gene in a certain chromosome, and an optimal combination is selected from the selectable path set of the service based on certain iteration times by adopting a traditional genetic algorithm;
and outputting the obtained service path combination, the average service communication delay and the service balance degree.
The present invention further provides a system for determining a business risk of a system protection private network, as shown in fig. 7, the system 200 specifically includes:
the system comprises a fault positioning and warning unit 201, a network topology G, a service set S and a fault warning set A, wherein the fault positioning and warning unit is used for carrying out fault positioning on a system protection private network, determining a fault type and giving a warning according to the fault type, specifically, when a random link Li in the network has a fault Fi, the service Si generates an abnormality at a host node, determining the fault type and generating warning information Ai, forming a bipartite graph of the fault warning set A and a suspected fault link set F, preprocessing the bipartite graph, simplifying the bipartite graph, removing a set FN which is not necessarily faulted in the set F, and leaving a set FY which is necessarily faulted and a set FS which is suspected to be faulted; and finally determining the fault elements in the FS by using a fault locating algorithm, thereby determining a fault link set FF in the network.
A mathematical model building unit 202, which is used for building a rerouting mechanism based on business risks to build a routing optimization mathematical model, specifically:
wherein the content of the first and second substances,
the average communication time of the service is taken as the average communication time of the service, Ti is the time delay of the service i, L is the number of the services, BD is the service balance degree, Li is the number of the services borne on the ith link, m is the number of network links, Tmax is the maximum service time delay, Lmax is the maximum number of the services borne by the links, alpha and beta are two constant coefficients, and the constraint part represents the service time delay constraint and the link service number constraint;
wherein, the rerouting mechanism is configured with an LSP from the first node a to the node K via the node D and the node G, the fiber between the node D and the node G is broken, and the rerouting process is:
after the FIU or OTU of the node D detects the alarm, the master GMPLS module is reported;
the node D is used for checking the affected intelligent service and sending a Notify message to the first node A by a GMPLS module;
after receiving the Notify message, the GMPLS module of the first node A calculates an end-to-end recovery PATH, then sends PATH message to the end node K direction through the intermediate node along the calculated PATH, and establishes reverse cross connection at each node along the PATH;
after receiving the PATH message, the GMPLS module of the end node K sends an RESV message to the first node A through the intermediate node, and positive cross connection is established at each node along the way;
after receiving the RESV message sent by the end node, the first node A opens the alarm monitoring and then sends the PATH message for opening the alarm to the downstream node. After receiving the message, the downstream nodes open the alarm monitoring to the new service path, and after the alarm monitoring of the whole LSP is opened, if the LSP is the unreleasable service, the old path is deleted.
An optimization model building unit 203 builds a route optimization model according to the route optimization mathematical model built based on the rerouting mechanism of the service risk and the stable control service borne on the communication link triggering automatic rerouting, which is specifically as follows:
initializing a stable control service in a system protection private network, constructing a network topology G (V, E, W), and setting a service list S (vs, vd);
wherein V is a node set, E is a link set, W is weight-time delay of each link, vs is a service starting node, and vd is a service destination node;
deleting the interruption link X in the network topology G to obtain a new network topology G';
searching the first k time delay shortest paths for each service in the service set S to form a service selectable path set Sk;
each service is regarded as a gene of the chromosome, the length of the chromosome is the number of the services, the gene coding adopts natural number coding, and the fitness function of the chromosome i is
Randomly generating an initial population, the selection function being a roulette selection method, chromosome i being selected with a probability of
The crossing process adopts a hybridization operation method based on position, the mutation process is to randomly change the positions of 1 gene in a certain chromosome, and an optimal combination is selected from the selectable path set of the service based on certain iteration times by adopting a traditional genetic algorithm;
and outputting the obtained service path combination, the average service communication time delay and the service balance degree, and judging the service path risk according to the output, wherein the smaller the average service communication time delay is, the lower the service path risk value is, and the service balance degree is at 0.
The invention realizes the minimum weighted sum of the average transmission delay of the service and the balance degree of the whole network service.
The invention effectively reduces the operation risk of the service, avoids the service loss and further enhances the robustness and the flexibility of the real-time system protection private network communication system.
Claims (6)
1. A method for determining a business risk of a system protected private network, comprising:
step one, carrying out fault location on a system protection private network, determining a fault type and giving an alarm according to the fault type;
step two, establishing a rerouting mechanism based on business risks to construct a route optimization mathematical model, specifically:
wherein the content of the first and second substances,
the average communication time of the service is taken as the average communication time of the service, Ti is the time delay of the service i, L is the number of the services, BD is the service balance degree, Li is the number of the services borne on the ith link, m is the number of network links, Tmax is the maximum service time delay, Lmax is the maximum number of the services borne by the links, alpha and beta are two constant coefficients, and the constraint part represents the service time delay constraint and the link service number constraint;
step three, performing a first step of cleaning the substrate,
according to the route optimization mathematical model established by the rerouting mechanism based on the service risk and the stable control service borne on the communication link triggering automatic rerouting, the route optimization model is established, specifically as follows:
initializing a stable control service in a system protection private network, constructing a network topology G (V, E, W), and setting a service list S (vs, vd);
wherein V is a node set, E is a link set, W is weight-time delay of each link, vs is a service starting node, and vd is a service destination node;
deleting the interruption link X in the network topology G to obtain a new network topology G';
searching the first k time delay shortest paths for each service in the service set S to form a service selectable path set Sk;
regarding each service as a gene of a chromosome, wherein the length of the chromosome is the number of the services, the gene coding adopts natural number coding, and the fitness function of the chromosome i is as follows:
randomly generating an initial population, the selection function being a roulette selection method, chromosome i being selected with a probability of
The crossing process adopts a hybridization operation method based on position, the mutation process is to randomly change the positions of 1 gene in a certain chromosome, and an optimal combination is selected from the selectable path set of the service based on certain iteration times by adopting a traditional genetic algorithm;
and outputting the obtained service path combination, the average service communication time delay and the service balance degree, and judging the service path risk according to the output, wherein the smaller the average service communication time delay is, the lower the service path risk value is, and the service balance degree tends to be 0.
2. The method of claim 1, wherein: the method comprises the following steps that firstly, a network topology G, a service set S and a fault alarm set A are specifically constructed, when a random link Li in a network has a fault Fi, the service Si generates an abnormality at a host node, the fault type is determined, alarm information Ai is generated, a bipartite graph of the fault alarm set A and a suspected fault link set F is formed, the bipartite graph is preprocessed, the bipartite graph is simplified, in the set F, a set FN which is not necessarily faulted is removed, and a set FY which is necessarily faulted and a set FS which is necessarily faulted are left; and finally determining the fault elements in the FS by using a fault locating algorithm, thereby determining a fault link set FF in the network.
3. The method of claim 1, wherein: the rerouting mechanism is configured with an LSP from the first node A to the node K through the node D and the node G, the fiber between the node D and the node G is broken, and the rerouting process is as follows:
after the FIU or OTU of the node D detects the alarm, the master GMPLS module is reported;
the node D is used for checking the affected intelligent service and sending a Notify message to the first node A by a GMPLS module;
after receiving the Notify message, the GMPLS module of the first node A calculates an end-to-end recovery PATH, then sends PATH message to the end node K direction through the intermediate node along the calculated PATH, and establishes reverse cross connection at each node along the PATH;
after receiving the PATH message, the GMPLS module of the end node K sends an RESV message to the first node A through the intermediate node, and positive cross connection is established at each node along the way;
after receiving RESV information from the end node, the first node A opens alarm monitoring, and then sends PATH information for opening alarm to the downstream node, after receiving the information, the downstream node opens alarm monitoring to the new service PATH, and after the alarm monitoring of the whole LSP is opened, if the LSP is unreleasable service, the old PATH is deleted.
4. A business risk optimization modeling system of a system protection private network is characterized by comprising:
the fault positioning and warning unit is used for positioning the fault of the system protection private network, determining the fault type and giving an alarm according to the fault type;
a mathematical model building unit is used for building a rerouting mechanism based on business risks to build a route optimization mathematical model, and the method specifically comprises the following steps:
wherein the content of the first and second substances,
the average communication time of the service is taken as the average communication time of the service, Ti is the time delay of the service i, L is the number of the services, BD is the service balance degree, Li is the number of the services borne on the ith link, m is the number of network links, Tmax is the maximum service time delay, Lmax is the maximum number of the services borne by the links, alpha and beta are two constant coefficients, and the constraint part represents the service time delay constraint and the link service number constraint;
an optimization model unit is constructed, and a route optimization model is constructed according to the route optimization mathematical model constructed based on the traffic risk rerouting mechanism and the stable control traffic carried on the communication link triggering automatic rerouting, specifically as follows:
initializing a stable control service in a system protection private network, constructing a network topology G (V, E, W), and setting a service list S (vs, vd);
wherein V is a node set, E is a link set, W is weight-time delay of each link, vs is a service starting node, and vd is a service destination node;
deleting the interruption link X in the network topology G to obtain a new network topology G';
searching the first k time delay shortest paths for each service in the service set S to form a service selectable path set Sk;
regarding each service as a gene of a chromosome, wherein the length of the chromosome is the number of the services, the gene coding adopts natural number coding, and the fitness function of the chromosome i is as follows:
randomly generating an initial population, the selection function being a roulette selection method, chromosome i being selected with a probability of
The crossing process adopts a hybridization operation method based on position, the mutation process is to randomly change the positions of 1 gene in a certain chromosome, and an optimal combination is selected from the selectable path set of the service based on certain iteration times by adopting a traditional genetic algorithm;
and outputting the obtained service path combination, the average service communication time delay and the service balance degree, and judging the service path risk according to the output, wherein the smaller the average service communication time delay is, the lower the service path risk value is, and the service balance degree tends to be 0.
5. The system of claim 4, wherein: the method comprises the steps that a fault positioning and warning unit specifically constructs a network topology G, a service set S and a fault warning set A, when a random link Li in a network has a fault Fi, a service Si generates an abnormality at a host node, determines a fault type and generates warning information Ai to form a bipartite graph of the fault warning set A and a suspected fault link set F, the bipartite graph is preprocessed to simplify the bipartite graph, and a set FN which must not fail is removed from the set F, and a set FY which must fail and a set FS which must fail are left; and finally determining the fault elements in the FS by using a fault locating algorithm, thereby determining a fault link set FF in the network.
6. The system of claim 4, wherein: the rerouting mechanism is configured with an LSP from the first node A to the node K through the node D and the node G, the fiber between the node D and the node G is broken, and the rerouting process is as follows:
after the FIU or OTU of the node D detects the alarm, the master GMPLS module is reported;
the node D is used for checking the affected intelligent service and sending a Notify message to the first node A by a GMPLS module;
after receiving the Notify message, the GMPLS module of the first node A calculates an end-to-end recovery PATH, then sends PATH message to the end node K direction through the intermediate node along the calculated PATH, and establishes reverse cross connection at each node along the PATH;
after receiving the PATH message, the GMPLS module of the end node K sends an RESV message to the first node A through the intermediate node, and positive cross connection is established at each node along the way;
after receiving RESV information from the end node, the first node A opens alarm monitoring, and then sends PATH information for opening alarm to the downstream node, after receiving the information, the downstream node opens alarm monitoring to the new service PATH, and after the alarm monitoring of the whole LSP is opened, if the LSP is unreleasable service, the old PATH is deleted.
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