CN109510764B - Power multi-service transmission optimization method and device - Google Patents
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Abstract
The invention discloses a method and a device for optimizing power multi-service transmission, wherein the method comprises the following steps: determining at least two transmission paths between a source node and a destination node of power service to be transmitted; respectively calculating the performance integration degree of the at least two transmission paths, wherein the performance integration degree is the integrated value of the multi-aspect performance parameters of the transmission paths; determining a transmission path with optimal performance integration degree; and transmitting the power service to be transmitted through the transmission path with the optimal performance comprehensiveness. The invention can plan the path according to the performance of comprehensively considering reliability, risk, real-time performance and the like, so that the transmission performance of the power communication network is generally optimized.
Description
Technical Field
The invention relates to the technical field of power communication, in particular to a power multi-service transmission optimization method and device.
Background
Nowadays, electric power communication services and electric power communication networks are continuously developed, and the connection between the electric power communication services and the electric power communication networks and the electric power grids is more and more. Compared with the services carried by the public network, most services of the power communication network are used for guaranteeing the normal operation and production of the power system, and the reliable operation of the power communication network plays an important role in the management of the operation management, the production scheduling and the enterprise informatization management of a power grid company.
The existing power multi-service transmission optimization method usually selects a path with the shortest distance from a source node to a destination node for transmission. However, there are disadvantages such as low reliability and poor real-time performance when transmitting power services over the shortest distance.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for optimizing power multi-service transmission, so as to solve the problems of low reliability and poor real-time performance when power services are transmitted over a shortest distance.
According to a first aspect, an embodiment of the present invention provides a power multi-service transmission optimization method, including: determining at least two transmission paths between a source node and a destination node of power service to be transmitted; respectively calculating the performance integration degree of the at least two transmission paths, wherein the performance integration degree is the integrated value of the multi-aspect performance parameters of the transmission paths; determining a transmission path with optimal performance integration degree; and transmitting the power service to be transmitted through the transmission path with the optimal performance comprehensiveness.
Optionally, the performance integration degree is calculated by the following formula:
wherein t represents that the service type of the power service to be transmitted belongs to is the t-th service, X is the number of the t-th service on the path L, EtLxClass x performance parameter, a, on path L for class t traffictxThe parameter is a weight coefficient of the xth performance parameter of the tth service, and | a | represents the normalization processing of the variable a.
Optionally, the performance parameter includes at least one of traffic latency, traffic risk, and traffic load balancing.
Optionally, the performance integration degree is calculated by the following formula:
Fobj＝||at1·EtL1||+||at2·EtL2||+||at3·EtL3where t denotes that the service type to which the power service to be transmitted belongs is the t-th service, EtL1A service delay performance parameter for the t-th service on the path Lt1A weight coefficient of the service delay performance parameter of the t-type service; etL2For the traffic risk performance parameter of class t traffic on path L, at2A weight coefficient of the service risk performance parameter of the t-type service; etL3Balancing performance parameters for the traffic load of class t traffic on path L, at3And balancing the weight coefficient of the performance parameter for the service load of the t-th service.
Optionally, the weight coefficient is calculated by the following formula:
wherein D istFor real-time weighting of class t traffic, RtFor risk weight of class t traffic, PtAs in class tLoad balancing weight of traffic.
Optionally, the service delay performance parameter of the t-th class service on the path L is calculated by the following formula: etL1＝Dt·DtL1And is and
wherein D istL1The delay of the t-th service on the path L; w is the directional side on the path L, W is the set of sides W on the path L, DelaytwThe time delay of the t-th class service on the edge w; n is a node on the path L, N is a set of nodes on the path L, DelaytnThe time delay of the t-th service at the node n is obtained; and/or calculating the service risk performance parameter of the t-th class service on the path L by the following formula: etL2＝Rt·RtL2And is and
wherein R istL1Risk on path L for type t traffic; w is the edge with direction on the path L, W is the set of edges W on the path L, LoiwProbability of failure of edge w, RiwThe risk of edge w; n is a node on path L, N is a set of nodes on path L, LoinIs the failure probability of node n, RinIs the risk of node n; and/or calculating the service load balancing performance parameter of the t-th class service on the path L by the following formula: etL3＝Pt·PiL3And is and
wherein, PiL3Load balance degree of the t-th class service on a path L; b iswTotal bandwidth of edge w, BjW is the set of edges W on the path L for the traffic bandwidth on the path before traffic i.
According to a second aspect, an embodiment of the present invention provides an electric power multi-service transmission optimization apparatus, including: the system comprises a first determining unit, a second determining unit and a control unit, wherein the first determining unit is used for determining at least two transmission paths between a source node and a destination node of the power service to be transmitted; the calculating unit is used for respectively calculating the performance integration degree of the at least two transmission paths, wherein the performance integration degree is a comprehensive value of multi-aspect performance parameters of the transmission paths; the second determining unit is used for determining the transmission path with the optimal performance integration degree; and the transmission unit is used for transmitting the transmission path of the power service to be transmitted through the transmission path with the optimal performance comprehensiveness.
Optionally, the performance integration degree is calculated by the following formula:
wherein t represents that the service type of the power service to be transmitted belongs to is the t-th service, X is the number of the t-th service on the path L, EtLxClass x performance parameter, a, on path L for class t traffictxThe parameter is a weight coefficient of the xth performance parameter of the tth service, and | a | represents the normalization processing of the variable a.
According to a third aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores computer instructions for causing a computer to execute the power multiservice transmission optimization method described in the first aspect or any one implementation manner of the first aspect.
According to the method and the device for optimizing the power multi-service transmission, provided by the embodiment of the invention, after at least two transmission paths of the power service to be transmitted from the source node to the destination node are determined, the performance integration degree of the transmission paths is respectively calculated, the power service to be transmitted is transmitted by adopting the transmission path with the optimal performance integration degree, and path planning can be carried out according to the performance of the power service to be transmitted in all aspects of comprehensive consideration of reliability, risk, instantaneity and the like, so that the transmission performance of a power communication network is generally optimized.
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The features and advantages of the present invention will be more clearly understood by reference to the accompanying drawings, which are illustrative and not to be construed as limiting the invention in any way, and in which:
fig. 1 shows a flow chart of a power multi-service transmission optimization method according to an embodiment of the invention;
fig. 2 shows a schematic block diagram of an electric power multi-service transmission optimizing device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 shows a flowchart of a power multi-service transmission optimization method according to an embodiment of the present invention. As shown in fig. 1, the method comprises the steps of:
s101: at least one transmission path between the power service to be transmitted from the source node to the destination node is determined.
The source node is the position of the power service to be transmitted in the power communication network, and the destination node is the position to which the power service needs to be transmitted. A plurality of transmission paths from a source node to a destination node often exist in a power communication network.
Step S101 may be to obtain all transmission paths from the source node to the destination node, or may be to obtain k shortest paths according to Dijkstra algorithm, where k is a search range of Dijkstra algorithm.
S102: and respectively calculating the performance integration degree of at least one transmission path, wherein the performance integration degree is the integrated value of the multi-aspect performance parameters of the transmission path.
S103: and determining the transmission path with the optimal performance integration degree.
The "optimum" here may be a minimum value or a maximum value, depending on the specific calculation method of the performance integration degree.
S104: and transmitting the power service to be transmitted through the determined transmission path.
According to the power multi-service transmission optimization method, after at least two transmission paths between the power service to be transmitted from the source node to the destination node are determined, the performance integration degrees of the transmission paths are respectively calculated, the transmission path with the optimal performance integration degree is adopted to transmit the power service to be transmitted, path planning can be carried out according to the performance of the power service to be transmitted in all aspects of comprehensive consideration of reliability, risk, instantaneity and the like, and the transmission performance of the power communication network is enabled to be overall optimized.
Before the above steps are performed, network information (including a network topology, device information of each node in the network, etc.) is initialized, and is denoted by G (N, W, L). Wherein, n (n) represents a node set in the network, w (w) represents a set of edges in the network, w represents a directional edge, l (l) represents a path set of the traffic, l represents the ith path of the traffic, and the path l is composed of the edge w. In addition, in the present application, i (i) represents a set of services, and Bw represents an available bandwidth size of an edge w.
Before the power service I to be transmitted is transmitted, identifying the type of the power service to be transmitted, a source node, a destination node and the bandwidth required by service transmission to be I (t, s, d, B)i) Indicating that t is the service class to which the service i belongs, s is the source node of the service request, d is the destination node of the service request, BiBandwidth required for the transmission of service i.
As an alternative to this embodiment, the performance integration
Wherein t represents that the service type of the power service to be transmitted belongs to is the t-th service, X is the number of the t-th service on the path L, EtLxClass x performance parameter, a, on path L for class t traffictxThe parameter is a weight coefficient of the xth performance parameter of the tth service, and | a | represents the normalization processing of the variable a. That is, after the x-th class performance parameter of the t-th class service on the path L is multiplied by the weight value, the product result is normalized, and then the values after normalization are summed. The performance integration degree is simple in calculation mode, the calculated amount is small, and the larger the value of the performance integration degree is, the better the value is.
Wherein, the normalization processing method converts each performance parameter EtL1、EtL2、EtL3… …, carrying out non-dimensionalization treatment, and the calculation formula is as follows:
wherein z is E before treatmenttL1、EtL2Or EtL3… …, z' is E after processing corresponding to ztL1、EtL2Or EtL3… …, max is pre-treatment EtL1、EtL2、EtL3… …, min is pre-treatment EtL1、EtL2、EtL3… …. The normalization processing enables the weighted value of each performance parameter to be in a value range of 0-1, prevents a certain performance parameter from being larger in value after being weighted and enabling the value of the certain performance parameter and the value of the other performance parameter after being weighted not to be in the same value range, and reduces complexity of weight determination.
Of course, other ways of calculating the performance integration may be used, such as, for example,
the larger the value of the performance integration degree is, the better the performance integration degree is; fobj＝||at1·EtL1||·||at2·EtL2||……||atx·EtLxAnd | l, the smaller the value of the performance integration degree is, the better the performance integration degree is.
The following describes a calculation method of the performance integration degree by taking performance parameters including service delay, service risk, and service load balance as examples.
Performance integration degree Fobj＝||at1·EtL1||+||at2·EtL2||+||at3·EtL3Where t denotes that the service type to which the power service to be transmitted belongs is the t-th service, EtL1A service delay performance parameter for the t-th service on the path Lt1A weight coefficient of the service delay performance parameter of the t-type service; etL2For the traffic risk performance parameter of class t traffic on path L, at2For class t servicesWeighting coefficients of business risk performance parameters; etL3Balancing performance parameters for the traffic load of class t traffic on path L, at3And balancing the weight coefficient of the performance parameter for the service load of the t-th service.
Wherein the weight coefficient
DtFor real-time weighting of class t traffic, RtFor risk weight of class t traffic, PtAnd the load balance weight of the t-th class service is obtained.
Weighting by real-time nature of business according to analytic hierarchy process DtRisk weight RtAnd a traffic load balancing weight PtRespectively calculating D for scheme layer and service type as criterion layert、RtAnd PtWeight values for different services. The specific method comprises the following steps:
constructing a discrimination matrix according to an analytic hierarchy process, wherein CiRepresenting services i, CijIndicating the result of comparing the importance of the service ij.
The properties are as follows: (1) cij>0；(2)Cij＝1/Cji；(3)Cii＝1。
CijThe assignment method comprises the following steps:
wherein i and j represent two service types, and the two service types are compared pairwise according to the method. And obtaining a discrimination matrix A. And (4) carrying out consistency check on the matrix A for the situation that pairwise contradiction occurs when two kinds of service assignment do not occur. Calculating the maximum eigenvalue lambda of the judgment matrix AmaxAnd the characteristic vector W can be solved by adopting a recursive method.
Normalizing the characteristic vector W to obtain eachWeight vector W of pair-wise decision matrix1。
And (3) carrying out consistency check on the judgment matrix, wherein R.I. is an average random consistency index of the same order, C.R. is a consistency ratio, and C.I. is a consistency index of the judgment matrix, and usually C.R. <0.1, which indicates that the consistency of the judgment matrix is acceptable. The specific calculation method comprises the following steps:
get the maximum characteristic root λmaxThe corresponding eigenvector is the value of D (i), and R (i) and P (i) can be obtained in the same way.
Calculating the service delay performance parameter of the t-th class service on the path L by the following formula: etL1＝Dt·DtL1And is and
wherein D istL1The delay of the t-th service on the path L; w is the directional side on the path L, W is the set of sides W on the path L, DelaytwThe time delay of the t-th class service on the edge w; n is a node on the path L, N is a set of nodes on the path L, DelaytnThe delay at node n for class t traffic.
Calculating the service risk performance parameter of the t-th class service on the path L by the following formula: etL2＝Rt·RtL2And is and
wherein R istL1Risk on path L for type t traffic; w is the edge with direction on the path L, W is the set of edges W on the path L, LoiwProbability of failure of edge w, RiwThe risk of edge w; n is a node on path L, N is a set of nodes on path L, LoinIs the failure probability of node n, RinIs the risk of node n.
Calculating the service load balancing performance parameter of the t-th service on the path L by the following formula：EtL3＝Pt·PiL3And is and
that is to say
Wherein, PiL3Load balance degree of the t-th class service on a path L; b ism(w)The used bandwidth of edge w, BwTotal bandwidth of edge w, BjW is the set of edges W on the path L for the traffic bandwidth on the path before traffic i.
With the continuous improvement of the requirements of the power system on automation, informatization and intellectualization, the power grid service carried by the power communication network has the trend of "broadband, networking, IP and diversification", and the traditional multilayer network architecture of Packet Transport Network (PTN) + Optical Transport Network (OTN) "can provide bandwidth, but has various problems. A packet enhanced optical network (POTN) which has been developed in recent years is a good solution, and the POTN refers to a network which has processing capabilities such as optical channel data unit (ODUk) crossing, packet switching, Virtual Container (VC) crossing, and Optical Channel (OCH) crossing, and can realize unified transmission of services such as electrical switching services and packets. Meanwhile, the system has the capability of wavelength division/OTN/SDH/PTN, and can simplify the network layer, reduce the equipment stacking and reduce the occupied area.
In the past, network service routing algorithms generally plan service paths according to shortest paths between services, and implemented networks are usually from PTNs, OTNs, and the like, which is less than the service routing planning methods of the POTN networks. Especially, for a network carrying power services, in the face of complex situations of multiple types and multiple granularities of power services, a traditional service routing algorithm cannot necessarily meet special requirements of power multi-service transmission optimization. Because the POTN has the capability of carrying both packet service and circuit service, a general routing algorithm usually only considers the planning of a service transmission path, but ignores the service adaptation problems of mapping multiplexing and the like of the service in the POTN network, and usually needs to add an adaptation process when planning the service route in practical application, thereby completing the service routing process.
For the situation that the POTN carries the power service, before step S101, the service needs to be adapted by mapping and multiplexing according to the type and bandwidth of the power service to be transmitted, so as to establish a transmission path from the source node to the destination node.
Determining a traffic real-time threshold D before adaptationp(i) Traffic particle threshold BpiAnd the algorithm search range k represents the number of routing paths for performing shortest path algorithm selection on the service.
The specific adaptation method is as follows. For general circuit-switched services, the traffic bandwidth is relatively small, when D (i)>Dp(i) The adaptation mode adopted is that the service is multiplexed to STM-N (Synchronous Transport Module level N, Chinese: Synchronous transmission Module N level), and then mapped to ODUk (Optical channel data unit, Chinese: Optical channel data unit). D (i)<Dp(i) And adopting a circuit simulation method to map the service into the pseudo wire PW. For packet switched and power over ethernet traffic, in order to make full use of network resources. And mapping the service into the PW, and selecting an adaptive path according to the service real-time weight D (i) and the service bandwidth Bi. The specific adaptation method comprises the following steps: when the real-time weight D (i) of the service is larger than the real-time weight threshold value Dp(i) And encapsulating the service into a PW, mapping the PW into an LSP (Label Switched Path, Chinese) and then encapsulating the LSP into an ODUk. Selecting a service according to its grain size, the service grain size B, when the service real-time weight D (i) is less than the service real-time weight thresholdiGreater than the particle size threshold BpiMeanwhile, after the service is encapsulated into the PW, the service is mapped into the LSP and encapsulated into the ODUk. Service particle size BiLess than the particle size threshold BpiWhen the service is in use, the PWs of multiple services are mapped into one LSP, and then the LSP is encapsulated to enter an ODUk, and a specific adaptation mode is shown in formula (1).
Fig. 2 shows a schematic block diagram of an electrical multi-service transmission optimization apparatus according to an embodiment of the present invention, which can be used to execute the method shown in fig. 1. As shown in fig. 2, the apparatus includes a first determining unit 10, a calculating unit 20, a second determining unit 30, and a transmitting unit 40.
The first determination unit 10 is configured to determine at least two transmission paths between the source node and the destination node of the current power traffic. The calculating unit 20 is configured to calculate performance integration degrees of at least two transmission paths, where the performance integration degrees are integrated values of multiple performance parameters of the transmission paths. The second determination unit 30 is used to determine the transmission path with the best performance integration. The transmission unit 40 is configured to transmit the transmission path of the current power service through the transmission path with the optimal performance integration.
An embodiment of the present invention also provides a computer-readable storage medium storing computer instructions (for example, the first determining unit 10, the calculating unit 20, the second determining unit 30, and the transmitting unit 40 shown in fig. 2) for causing a computer to execute the power multi-service transmission optimization method shown in fig. 1.
The computer-readable storage medium may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by a computer, and the like. Further, the computer-readable storage medium may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the computer-readable storage medium optionally includes memory located remotely from the computer, which may be connected to the computer through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.
Claims (3)
1. A power multi-service transmission optimization method is characterized by comprising the following steps:
determining at least two transmission paths between a source node and a destination node of power service to be transmitted;
respectively calculating the performance integration degree of the at least two transmission paths, wherein the performance integration degree is the integrated value of the multi-aspect performance parameters of the transmission paths;
determining a transmission path with optimal performance integration degree;
transmitting the power service to be transmitted through the transmission path with the optimal performance comprehensiveness;
the performance integration degree is calculated by the following formula:
Fobj＝||at1·EtL1||+||at2·EtL2||+||at3·EtL3the parameter is a variable A, t represents that the service type of the electric power service to be transmitted is the t-th service, EtL1A service delay performance parameter for the t-th service on the path Lt1A weight coefficient of the service delay performance parameter of the t-type service; etL2For the traffic risk performance parameter of class t traffic on path L, at2Is as followsthe weight coefficient of the service risk performance parameter of the t-type service; etL3Balancing performance parameters for the traffic load of class t traffic on path L, at3A weight coefficient of the service load balancing performance parameter of the t-type service;
calculating the service delay performance parameter of the t-th class service on the path L by the following formula: etL1＝Dt·DtL1And is and
wherein D istL1The delay of the t-th service on the path L; w is the directional side on the path L, W is the set of sides W on the path L, DelaytwThe time delay of the t-th class service on the edge w; n is a node on the path L, N is a set of nodes on the path L, DelaytnThe time delay of the t-th service at the node n is obtained; and/or the presence of a gas in the gas,
calculating the service risk performance parameter of the t-th class service on the path L by the following formula: etL2＝Rt·RtL2And is and
wherein R istL2Risk on path L for type t traffic; w is the edge with direction on the path L, W is the set of edges W on the path L, LoiwProbability of failure of edge w, RiwThe risk of edge w; n is a node on path L, N is a set of nodes on path L, LoinIs the failure probability of node n, RinIs the risk of node n; and/or the presence of a gas in the gas,
calculating the service load balancing performance parameter of the t-th class service on the path L by the following formula: etL3＝Pt·PiL3And is and
wherein, PiL3Load balance degree of the t-th class service on a path L; b iswTotal bandwidth of edge w, BjFor the traffic bandwidth on the path before traffic i, W is the set of edges W on path L；
The weight coefficient is calculated by the following formula:
2. An apparatus for optimizing power multi-service transmission, comprising:
the system comprises a first determining unit, a second determining unit and a control unit, wherein the first determining unit is used for determining at least two transmission paths between a source node and a destination node of the power service to be transmitted;
the calculating unit is used for respectively calculating the performance integration degree of the at least two transmission paths, wherein the performance integration degree is a comprehensive value of multi-aspect performance parameters of the transmission paths;
the second determining unit is used for determining the transmission path with the optimal performance integration degree;
the transmission unit is used for transmitting the transmission path of the power service to be transmitted through the transmission path with the optimal performance comprehensiveness;
the performance integration degree is calculated by the following formula:
Fobj＝||at1·EtL1||+||at2·EtL2||+||at3·EtL3the parameter is a variable A, t represents that the service type of the electric power service to be transmitted is the t-th service, EtL1A service delay performance parameter for the t-th service on the path Lt1A weight coefficient of the service delay performance parameter of the t-type service; etL2For the traffic risk performance parameter of class t traffic on path L, at2A weight coefficient of the service risk performance parameter of the t-type service; etL3Balancing performance parameters for the traffic load of class t traffic on path L, at3A weight coefficient of the service load balancing performance parameter of the t-type service;
calculating the service delay performance parameter of the t-th class service on the path L by the following formula: etL1＝Dt·DtL1And is and
wherein D istL1The delay of the t-th service on the path L; w is the directional side on the path L, W is the set of sides W on the path L, DelaytwThe time delay of the t-th class service on the edge w; n is a node on the path L, N is a set of nodes on the path L, DelaytnThe time delay of the t-th service at the node n is obtained; and/or the presence of a gas in the gas,
calculating the service risk performance parameter of the t-th class service on the path L by the following formula: etL2＝Rt·RtL2And is and
wherein R istL2Risk on path L for type t traffic; w is the edge with direction on the path L, W is the set of edges W on the path L, LoiwProbability of failure of edge w, RiwThe risk of edge w; n is a node on path L, N is a set of nodes on path L, LoinIs the failure probability of node n, RinIs the risk of node n; and/or the presence of a gas in the gas,
calculating the service load balancing performance parameter of the t-th class service on the path L by the following formula: etL3＝Pt·PiL3And is and
wherein, PiL3Load balance degree of the t-th class service on a path L; b iswTotal bandwidth of edge w, BjW is the set of edges W on the path L for the traffic bandwidth on the path before the traffic i;
the weight coefficient is calculated by the following formula:
3. A computer-readable storage medium storing computer instructions for causing a computer to perform the power multiservice transmission optimization method of claim 1.
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