CN117978711A - Method for distributing power grid business paths - Google Patents

Abstract

The application provides a method and computing equipment for distributing power grid service paths, which are applied to power grid service. The method for distributing the power grid business paths comprises the following steps: receiving a power grid service request; based on the grouping wavelength allocation strategy, carrying out service path planning by utilizing an improved ant colony algorithm; establishing path connection according to the planned optimal path; the improved ant colony algorithm adds constraint information of link idle rate in the ant routing process, and the link idle rate is constrained by the grouping wavelength allocation strategy. The method of the application can reduce the network blocking rate of the high-priority power grid service and realize the performance of different power grid services in the network.

Description

Method for distributing power grid business paths

Technical Field

The invention relates to the technical field of path planning of multi-stage power grid service, in particular to a method for distributing power grid service paths.

Background

With the rapid development of smart power grids, each link of power service is more informationized and intelligent, a large number of new service scenes are introduced, the future power grids are subjected to the condition of rapid increase of different levels of service volume, and high requirements are put on the effectiveness and reliability of network transmission.

The current mainstream network transmission technology is an optical transport network (Optical Transport Network, OTN), and although the OTN can better promote the reliability of the power grid operation, the network resources are limited, and the intelligent power grid is faced with increasingly high traffic, and cannot be reasonably planned according to the service priority.

Routing and wavelength assignment (Routing AND WAVELENGTH ASSIGNMENT, RWA) is one of the key technologies for OTN networking. RWA specifically refers to selecting an appropriate route for a grid service connection request in the OTN and allocating an appropriate wavelength to the request. The core problem of RWA is how to select the optimal route to minimize the resource occupation and reduce the traffic congestion under the constraint conditions of given wavelength number, connection request and the like. Because of the highly differentiated user quality of service (Quality of Service, qoS) requirements of the grid service, the RWA policy not only needs to have dynamic allocation capability, but also needs to implement differentiated treatment according to service characteristics. In order to meet the differentiated power grid service demands, the wavelength utilization and blocking rate of the network are considered, and the RWA algorithm is improved according to the dynamic characteristics of the power grid service.

Therefore, the method has great significance on how to reasonably and effectively plan for different services in the face of various power grid services.

Disclosure of Invention

The application aims to provide a method for distributing power grid business paths, which aims to solve the problem of limited power grid network resources in the face of increasing business volume of a smart power grid.

According to an aspect of the present application, there is provided a method for grid traffic path allocation, comprising:

Receiving a power grid service request;

based on the grouping wavelength allocation strategy, carrying out service path planning by utilizing an improved ant colony algorithm;

establishing path connection according to the planned optimal path;

the improved ant colony algorithm adds constraint information of link idle rate in the ant routing process, and the link idle rate is constrained by the grouping wavelength allocation strategy.

According to some embodiments, the packet wavelength allocation policy comprises: and multiplexing and distributing the idle wavelength according to the service priority.

According to some embodiments, multiplexing and assigning idle wavelengths according to traffic priority comprises:

and after the power grid service arrives, searching idle wavelengths from wavelength packets with the priority and lower priority according to different service grades and priority orders.

According to some embodiments, the method further comprises: and determining the traffic proportion of the services with different priorities through simulation.

According to some embodiments, the improved ant colony algorithm calculates the transition probability by:

Wherein,

Representing the transition probability of ant x from node i to j at time t for a grid service connection request with priority k;

information amount indicating wavelength w on path (i, j) at time t;

alpha represents a heuristic factor of the pheromone;

a heuristic function representing a link (i, j) is the Euclidean distance of node i to node j;

beta is the influence factor of the heuristic function, representing the relative importance of visibility;

allowed _k represents all nodes selectable for ant x of grid service connection request node i with priority k;

is the link idle rate where the packet is k on the grid service connection request (i, j) with priority k at time t.

According to some embodiments, the link idle rate is calculated by the following formula:

Is the total wavelength number of k in the grouping on the power grid service connection request (i, j) with the priority of k; /(I) Is the number of wavelengths used for the service connection request (i, j) with priority k at time t.

According to another aspect of the present application, there is provided a computing device comprising:

A processor; and

And a memory storing a computer program which, when executed by the processor, causes the processor to perform any of the methods described above.

According to the embodiment of the application, the power grid business path planning algorithm based on grouping wavelength distribution can be widely applied to the field of business scheduling of intelligent power grids, and has strong compatibility and expansion type. On one hand, the algorithm adopts a grouping wavelength distribution strategy aiming at differentiated power grid services, so that the network performance of high-quality service can be effectively improved; on the other hand, the grouping wavelength link idle rate corresponding to the differentiated power grid service is introduced into the ant colony algorithm, the improved ant colony algorithm is combined with the G-RWA strategy, and the average blocking rate of the network is reduced.

According to some embodiments, after the grid traffic arrives, idle wavelengths are searched sequentially from the lower priority wavelength packets according to the traffic in order of priority, and if there is eventually no idle wavelength, the grid traffic will be rejected. The method can support differentiated treatment of different levels of power grid services, preferentially ensures wavelength resources of high-priority power grid services, and meets the performance requirement of lower blocking rate of the high-priority power grid services.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the description of the embodiments will be briefly described below.

Fig. 1 shows a schematic diagram of G-RWA packet-based wavelength allocation according to an example embodiment.

Fig. 2 shows a flow chart of G-RWA packet-based wavelength allocation according to an example embodiment.

Fig. 3 shows a flow chart of an improved ant colony algorithm +g-RWA based method according to an example embodiment.

Fig. 4 illustrates a network topology according to an example embodiment.

Fig. 5A illustrates a network topology low-priority traffic blocking rate according to an example embodiment.

Fig. 5B illustrates a preferred traffic blocking rate in a network topology according to an example embodiment.

Fig. 5C illustrates a network topology high-priority traffic blocking rate according to an example embodiment.

Fig. 5D illustrates a network topology average blocking rate according to an example embodiment.

Fig. 5E illustrates network topology channel utilization in accordance with an example embodiment.

FIG. 6 illustrates a block diagram of a computing device according to an example embodiment of the application.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted.

Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the application may be practiced without one or more of the specific details, or with other methods, components, devices, steps, etc. In other instances, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the application.

The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.

The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the order of actual execution may be changed according to actual situations.

It will be understood that, although the terms first, second, third, etc. may be used herein to describe various components, these components should not be limited by these terms. These terms are used to distinguish one element from another element. Accordingly, a first component discussed below could be termed a second component without departing from the teachings of the present inventive concept. As used herein, the term "and/or" includes any one of the associated listed items and all combinations of one or more.

The user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or fully authorized by each party, and the collection, use and processing of related data is required to comply with the relevant laws and regulations and standards of the relevant country and region, and is provided with corresponding operation entries for the user to select authorization or rejection.

Those skilled in the art will appreciate that the drawings are schematic representations of example embodiments and that the modules or flows in the drawings are not necessarily required to practice the application and therefore should not be taken to limit the scope of the application.

Aiming at various power grid services and differentiated power grid service requirements, a reasonable and efficient algorithm is explored, the overall blocking rate of the power grid services is improved, and the utilization rate of the power grid wavelength can be greatly improved. Therefore, the application provides a method for distributing the power grid service paths, which improves the overall blocking rate of the power grid service.

According to the method and the device for distributing the routing wavelength, the service class division is carried out on the requirements of the intelligent power grid service, the different classes of service are divided into different priorities, and a grouping wavelength distribution strategy is provided for differentiated service.

Before describing embodiments of the present application, some terms or concepts related to the embodiments of the present application are explained.

OTN (Optical Transport Network): an optical transport network, one type of network, refers to a transport network that implements transport, multiplexing, routing, monitoring of traffic signals within an optical domain, and ensures its performance metrics and survivability.

RWA (Routing AND WAVELENGTH ASSIGNMENT): the routing and wavelength allocation algorithm, a network algorithm, refers to that after connection requests among nodes are given in a network, routes are first found for the connection requests in the network, and then wavelengths are allocated to the routes. The algorithm that implements routing and wavelength assignment is referred to as the routing and wavelength assignment algorithm. The main task of RWA is to find a suitable optical path and to allocate wavelengths reasonably for it, making full use of limited resources to provide as much communication capacity as possible.

G-RWA (Group-based RWA): based on packet wavelength allocation.

Ant colony algorithm: is a probabilistic algorithm for finding an optimized path.

Exemplary embodiments of the present application are described below with reference to the accompanying drawings.

Fig. 1 shows a schematic diagram of packet-based wavelength allocation according to an example embodiment.

In an actual power network, the same wavelength can be multiplexed, since a single wavelength is not occupied by a certain grid service for a long time. In order to improve multiplexing efficiency, the traffic with the same and similar priority can be multiplexed to the same wavelength, and the performance of the low-priority traffic needs to be improved when the high-priority traffic is ensured, and the policy is based on packet routing wavelength allocation (G-RWA).

Referring to fig. 1, the packet wavelength allocation scheme includes a first service class QoS ₁, a second service class QoS ₂, a third service class QoS ₃, different wavelengths corresponding to different service classes, available wavelength numbers corresponding to different service classes, and different wavelengths in the power network. Wherein the first service class QoS ₁ corresponds to the packet wavelength G ₁, and the available wavelength number of the first service class QoS ₁ is (λ ₁₁、λ₁₂、…λ_1a); the second service class QoS ₂ corresponds to the packet wavelength G ₂, and the number of available wavelengths of the second service class QoS ₂ is (λ ₂₁、λ₂₂、…λ_2b); the third traffic class QoS ₃ corresponds to the packet wavelength G ₃, and the number of available wavelengths of the third traffic class QoS ₃ is (λ ₃₁、λ₃₂、…λ_3c), the wavelengths being divided into a first wavelength, a second wavelength, and a second wavelength according to different paths.

According to an example embodiment, assume that the total number of fibers of the power network is n and the total number of wavelengths multiplexed by a single fiber is W. Overall flow based on packet wavelength allocation: after the power grid service arrives, according to different service grades, searching idle wavelengths from wavelength groups with the priority and lower priority according to the priority sequence, and if the idle wavelengths are not available finally, rejecting the power grid service.

For further explanation, define:

Wherein,

Ζ _i is whether grid traffic of class i contains available wavelengths;

Delta _i is the grid business request blocking rate of level i;

gi represents the ith group of wavelength packets;

lambada _ij represents the j-th wavelength of the i-th group of wavelength packets.

According to some embodiments, the formula assumes that the requested blocking rate is inversely proportional to the number of available wavelengthsCan be further developed as:

by comparing the formulas (①)、(②) and (③), it can be derived that:

δ₁≤δ₂≤δ₃ (④)

from the analysis of the equation (④), it can be seen that the third traffic class is higher than the second traffic class, which is higher than the first traffic class.

The grouping wavelength allocation strategy can support differentiated treatment of different levels of power grid services, preferentially guarantees wavelength resources of high-priority power grid services, and meets the performance requirement of lower blocking rate of the high-priority power grid services.

Fig. 2 shows a flow chart of packet-based wavelength allocation according to an example embodiment.

At S101, a flow based on packet wavelength allocation is started.

A search for power network wavelengths is initiated.

At S103, the network initializes the set initial number of wavelengths.

According to an example embodiment, the network initialization sets an initial number of wavelengths of the power grid, and divides the power grid service into three levels of QoS ₁、QoS₂、QoS₃, wherein the grouping wavelength of each level is G ₁、G₂、G₃, and the available number of wavelengths of each level is (λ₁₁、λ₁₂、…λ_1a)、(λ₂₁、λ₂₂、…λ_2b)、(λ₃₁、λ₃₂、…λ_3c).

At S105, a service request arrives.

According to an example embodiment, after a service request arrives at the grid, the grid searches for idle wavelengths in the grid service class according to the priority order of the service.

At S106, it is determined whether the service level is QoS ₁.

According to an example embodiment, it is determined whether the requested service level is the first service level QoS ₁, and if the service request is the first service level QoS ₁, S107 is performed. If the service request is not the first service class QoS ₁, then S108 is performed.

In S107, it is determined whether G ₁ has an idle wavelength.

In the previous step S106, if the service request is the first service class QoS ₁, it is determined whether the packet wavelength G ₁ corresponding to the first service class QoS ₁ has an idle wavelength, and if the packet wavelength G ₁ has an idle wavelength, it is determined S115 to allocate a wavelength to the service. If the packet wavelength G ₁ has no idle wavelength, S109 is performed.

At S108, it is determined whether the service level is QoS ₂.

In the previous step S106, if the service request is not the first service class QoS ₁, a determination is made as to whether the service class is QoS ₂. If the service request is the second service class QoS ₂, S109 is performed. If the service request is not the second service class QoS ₂, then S110 is performed.

At S109, it is determined whether G ₂ has an idle wavelength.

In the previous step S108, if the service request is the second service class QoS ₂, it is determined whether the packet wavelength G ₂ corresponding to the second service class QoS ₂ has an idle wavelength, and if the packet wavelength G ₂ has an idle wavelength, it is determined S115 to allocate a wavelength to the service. If the packet wavelength G ₂ has no idle wavelength, S110 is performed.

At S110, it is determined whether G ₃ has an idle wavelength.

According to an example embodiment, as previously described, if the packet wavelength G ₁ corresponding to the first traffic class QoS ₁ has no idle wavelength and the packet wavelength G ₂ corresponding to the second traffic class QoS ₂ has no idle wavelength, a determination is made as to whether the packet wavelength G ₃ corresponding to the third traffic class QoS ₃ has an idle wavelength. If the packet wavelength G ₃ has an idle wavelength, S115 is performed to allocate a wavelength for the service. If the packet wavelength G ₃ has no idle wavelength, S113 is performed.

At S113, the request is denied.

According to an example embodiment, after determining the priority order of the service requests, if no idle wavelength is searched for the idle wavelength in each packet wavelength of the power grid service level, the service requests are refused, and S119 is performed, so as to end the flow of packet wavelength allocation.

At S115, according to an exemplary embodiment, after determining the priority order of the service requests, any idle wavelength is searched for in each packet wavelength of the power grid service level.

At S117, the occupied wavelength is released.

In the previous step S115, the wavelength is allocated to the service, and then the occupied wavelength is released, and S119 is performed, so that the entire wavelength packet allocation flow is terminated.

The grouping wavelength allocation strategy can support differentiated treatment of different-level power grid services, and after service requests arrive, the idle condition of low service level is firstly inquired, wavelength resources of high-priority power grid services are preferentially ensured, and the performance requirement of lower blocking rate of the high-priority power grid services is realized.

According to the routing and wavelength allocation algorithm RWA, the above embodiments seek a method based on packet wavelength allocation, and the following proposes an improved ant colony algorithm based on the routing allocation.

In the traditional ant colony algorithm, ant routing has certain randomness and blindness, and a large amount of pheromones are likely to be accumulated on certain network links (overload), but the pheromones of other paths are less (relatively idle). Therefore, the traditional ant colony algorithm has the problems of high traffic blocking rate and unbalanced load.

Aiming at the defects of the traditional ant colony algorithm and combining with the G-RwA strategy, the improved ant colony algorithm is provided, the key idea is to add constraint information of the link idle rate in the ant routing process, and to the connection request of each power grid service, the link with large link idle rate is preferentially selected, so that the problems of high blocking rate and unbalanced load are solved.

According to an example embodiment, the link idle rate formula is:

Wherein, The link idle rate of k is grouped on a power grid service connection request (i, j) with k priority at the moment t; /(I)Is the total wavelength number of k in the grouping on the power grid service connection request (i, j) with the priority of k; /(I)Is the number of wavelengths used for the service connection request (i, j) with priority k at time t.

According to an example embodiment, the improved transition probabilities are:

Wherein,

Representing the transition probability of ant x from node i to j at time t for a grid service connection request with priority k;

information amount indicating wavelength w on path (i, j) at time t;

alpha represents a heuristic factor of the pheromone;

a heuristic function representing a link (i, j) is the Euclidean distance of node i to node j;

beta is the influence factor of the heuristic function, representing the relative importance of visibility;

allowed _k represents all nodes selectable for ant x of grid service connection request node i with priority k.

Found through mathematical derivation, when the link is idleWhen the load of the service link is smaller than a certain value, the transfer probability of the improved ant colony algorithm is smaller than that of the traditional ant colony algorithm; when the link is idle rate/>When the traffic link load is higher than a certain value, the transition probability of the improved ant colony algorithm is higher than that of the traditional ant colony algorithm. Therefore, the improved ant colony algorithm can promote ants to select links with large idle rate with larger probability, so that the performance of blocking rate reduction and load balancing is realized.

Fig. 3 shows a flow chart of a G-RWA method based on an improved ant colony algorithm according to an example embodiment.

Based on the improved ant colony algorithm and the G-RWA grouping wavelength distribution method, the method combines the improved ant colony algorithm and the G-RWA grouping wavelength distribution method to be applied to power grid service distribution, so that the wavelength resource of power grid service can be fully utilized, and the problems of high service blocking rate and unbalanced load can be solved.

In S201, a path allocation procedure of G-RWA based on the improved ant colony algorithm is started.

At S203, the parameters are initialized.

Firstly, initializing parameters, which mainly comprises the initialization of ant number, maximum circulation times, network topology, traffic and multiplexing wavelength number among nodes.

At S205, it is determined whether or not the service arrives.

If the service request does not arrive, carrying out service detection again; if the service request has arrived, the process goes to S207 to perform path allocation.

In S207, traffic path planning is performed using the improved ant colony algorithm based on the packet wavelength allocation policy.

According to the link idle rate formula, constraint information of the link idle rate is added in the ant routing process, and a link with high link idle rate is preferentially selected according to the connection request of each power grid service, so that the problems of high blocking rate and unbalanced load are solved from the aspect of route distribution.

In accordance with the foregoing discussion, the link idle rate is constrained by the packet wavelength allocation policy.

According to some embodiments, when path planning is performed using the ant colony algorithm, if the wavelength allocation is successful, a global update may be applied.

According to some embodiments, after finding the optimal path, if the termination condition is not satisfied, the ant colony optimization may be continued. The termination condition may include the number of loops or the time that the ant colony algorithm has arrived.

At S209, it is determined whether or not the path is the optimal path.

If the ant selects the path according to the link idle rate and the grouping wavelength is successfully allocated, the ant judges whether the path is a feasible optimal path after global updating is applied to the result of selecting the path +G-RWA according to the link idle rate.

If the path allocation of the improved ant colony algorithm +G-RWA is the optimal path, S211 is performed, a path is established, and power grid service allocation is performed by the optimal path. Otherwise, continue waiting for other services.

According to some embodiments, the optimal path may incorporate traffic load, network blocking rate, etc. criteria.

According to some embodiments, after the path allocation method of the improved ant colony algorithm +g-RWA is determined, the power grid service may directly call the path allocation result of the improved ant colony algorithm +g-RWA when the path allocation that the subsequent service request arrives.

According to the path distribution method of the improved ant colony algorithm +G-RWA applied to the power grid service, in order to verify that the method can truly improve the performance indexes such as the power grid network resource utilization rate, the blocking rate and the like, the simulation result and the performance analysis are carried out aiming at the network service path planning algorithm based on the grouping wavelength distribution.

According to an example embodiment, the system simulation performed by the application mainly focuses on performance indexes such as network resource utilization rate, blocking rate and the like of different levels of power grid services, the simulation language is object-oriented C++, the development environment is visual studio code, and finally, the output result is analyzed, and parameters related to the simulation process are shown in table 1.

TABLE 1 simulation output parameters

And carrying out numerical simulation on the G-RWA algorithm on the 14-node 21 link NSFNET (National Science Foundation Network) network topology, comparing the service blocking rate performances of different levels of power grids, and comparing the average blocking rate of the improved ant colony + G-RWA algorithm with the non-differentiated service class RWA algorithm to verify the network performance of the G-RWA supporting differentiated services. The NSFNET network topology is shown in fig. 4, for which, for the sake of simulation, it is assumed that the nodes are connected by 4 optical fibers, and the number of multiplexing wavelengths in each optical fiber is 9 (i.e., each group of wavelengths contains 3 wavelengths).

To meet the wavelength consistency principle, all nodes in the defined network have no wavelength converter. It is assumed that in the initial state, when some grid traffic is generated in the network, some wavelength of some optical fibers is not available. The simulation result is an average result by repeating 100 operations because of the randomness of the source node, the target node, and the randomness of the ant colony algorithm.

According to an example embodiment, it is assumed that the service request numbers of the third level service, the second level service and the first level service are x, y and z, respectively, and the available wavelength numbers in the wavelength packets corresponding to the third level service, the second level service and the first level service are a, b and c. The third level service is higher than the second level service, the second level service is higher than the first level service, the simulation link follows the principle that the high level service volume is not greater than the low level service volume, and six service volume ratios of 1:1:7,1:2:6,1:3:5,2:2:5,2:3:4 and 1:1:1 are selected for simulation, so that a result is obtained. In the following figures, fig. 5A, fig. 5B, fig. 5C, fig. 5D, and fig. 5E respectively show the comparison of the traffic blocking rate, the average blocking rate, and the channel utilization rate of each level when a: B: c=x: y: z in the case that the NSFNET network topology adopts the improved ant colony+g-RWA algorithm, where the network traffic load in the network is normalized.

According to an example embodiment, as shown in fig. 5A, 5B, 5C, 5D and 5E, for the NSFNET network, in the case of using the modified ant colony+g-RWA algorithm, when a: B: c=x: y: z, as the traffic load increases, the traffic blocking rates of three levels all tend to increase. When the service load is low, both the high-priority service and the medium-priority service have the performance of low blocking rate, and the blocking rate of the low-priority service is high; when the service load is larger, the blocking rate of the low-priority service is closer to that of the medium-priority service. For the same level of traffic blocking rate, the blocking rate is different when the proportion of the traffic arriving is different. For example, for the low optimal traffic blocking rate, the blocking rate is minimal when the traffic ratio is 1:1:7, and is reduced by 15% at maximum relative to 1:1:1, but the high optimal traffic blocking rate is maximal.

From this, when x: y: z=1:1:7, better performance of low-priority service is obtained, and performance of high-priority service is sacrificed, which is contrary to the original purpose of low blocking rate of high-priority service. When the ratio of each traffic is comprehensively compared, the high-priority traffic blocking rate and the medium-priority traffic blocking rate are the lowest, and the low-priority traffic blocking rate is lower when x: y: z=1:3:5. As for the average blocking rate, at low traffic load, the blocking rate difference is large; at high traffic loads, the blocking rates for different wavelength packet ratios are nearly uniform. The channel utilization is similar regardless of the traffic load. Therefore, 1:3:5 is the optimal traffic ratio.

In summary, the ant colony+G-RWA algorithm is improved to enable the network blocking rate performances of different levels of power grid services to be different, the high-priority service blocking rate is relatively low, the low-priority service blocking rate is relatively high, and different performance performances of different levels of services in the network are realized. When the traffic proportion is different, the ratio of the packet wavelength number is the same as the traffic proportion, and the network performance is better. In summary, when the number of the third level service, the second level service and the first level service requests is 1:3:5, the NSFNET network has the best performance.

Aiming at the use allocation situation of the power grid service, the method for allocating the power grid service paths can preferentially ensure the wavelength resources of the power grid service with high priority by adopting a grouping wavelength allocation strategy through the power grid service with differentiated level, reduce the network blocking rate of the power grid service with high priority, add the link idle rate of wavelength grouping on the basis of traditional ant colony routing, combine ant routing with G-RWA strategy, and realize the performance of load balance and blocking rate reduction. Through simulation, the performance of different levels of power grid services in a network can be realized by verifying the improved ant colony +G-RWA algorithm.

FIG. 6 illustrates a block diagram of a computing device according to an example embodiment of the application.

As shown in fig. 6, computing device 30 includes processor 12 and memory 14. Computing device 30 may also include a bus 22, a network interface 16, and an I/O interface 18. The processor 12, memory 14, network interface 16, and I/O interface 18 may communicate with each other via a bus 22.

The processor 12 may include one or more general purpose CPUs (Central Processing Unit, processors), microprocessors, or application specific integrated circuits, etc. for executing associated program instructions.

Memory 14 may include machine-system-readable media in the form of volatile memory, such as Random Access Memory (RAM), read Only Memory (ROM), and/or cache memory. Memory 14 is used to store one or more programs including instructions as well as data. The processor 12 may read instructions stored in the memory 14 to perform the methods according to embodiments of the application described above.

Computing device 30 may also communicate with one or more networks through network interface 16. The network interface 16 may be a wireless network interface.

Bus 22 may be a bus including an address bus, a data bus, a control bus, etc. Bus 22 provides a path for exchanging information between the components.

It should be noted that, in the implementation, the computing device 30 may further include other components necessary to achieve normal operation. Furthermore, it will be understood by those skilled in the art that the above-described apparatus may include only the components necessary to implement the embodiments of the present description, and not all the components shown in the drawings.

The present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the above method. The computer readable storage medium may include, but is not limited to, any type of disk including floppy disks, optical disks, DVDs, CD-ROMs, micro-drives, and magneto-optical disks, ROM, RAM, EPROM, EEPROM, DRAM, VRAM, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), network storage devices, cloud storage devices, or any type of media or device suitable for storing instructions and/or data.

Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform part or all of the steps of any one of the methods described in the method embodiments above.

It will be clear to a person skilled in the art that the solution according to the application can be implemented by means of software and/or hardware. "Unit" and "module" in this specification refer to software and/or hardware capable of performing a specific function, either alone or in combination with other components, where the hardware may be, for example, a field programmable gate array, an integrated circuit, or the like.

It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in whole or in part in the form of a software product stored in a memory, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present application.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.

The exemplary embodiments of the present application have been particularly shown and described above. It is to be understood that this application is not limited to the precise arrangements, instrumentalities and instrumentalities described herein; on the contrary, the application is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

It will be clear to a person skilled in the art that the solution according to the application can be implemented by means of software and/or hardware. "Unit" and "module" in this specification refer to software and/or hardware capable of performing a specific function, either alone or in combination with other components, where the hardware may be, for example, a field programmable gate array, an integrated circuit, or the like.

It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in whole or in part in the form of a software product stored in a memory, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present application.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.

The exemplary embodiments of the present application have been particularly shown and described above. It is to be understood that this application is not limited to the precise arrangements, instrumentalities and instrumentalities described herein; on the contrary, the application is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims (7)

1. A method for grid traffic path allocation, comprising:

Receiving a power grid service request;

based on the grouping wavelength allocation strategy, carrying out service path planning by utilizing an improved ant colony algorithm;

establishing path connection according to the planned optimal path;

the improved ant colony algorithm adds constraint information of link idle rate in the ant routing process, and the link idle rate is constrained by the grouping wavelength allocation strategy.

2. The method of claim 1, wherein the packet wavelength allocation policy comprises:

And multiplexing and distributing the idle wavelength according to the service priority.

3. The method of claim 2, wherein multiplexing and assigning idle wavelengths according to traffic priority comprises:

and after the power grid service arrives, searching idle wavelengths from wavelength packets with the priority and lower priority according to different service grades and priority orders.

4. The method according to claim 2, wherein the method further comprises:

and determining the traffic proportion of the services with different priorities through simulation.

5. The method of claim 1, wherein the modified ant colony algorithm calculates the transition probability by:

Wherein,

Representing the transition probability of ant x from node i to j at time t for a grid service connection request with priority k;

information amount indicating wavelength w on path (i, j) at time t;

alpha represents a heuristic factor of the pheromone;

a heuristic function representing a link (i, j) is the Euclidean distance of node i to node j;

beta is the influence factor of the heuristic function, representing the relative importance of visibility;

allowed _k represents all nodes selectable for ant x of grid service connection request node i with priority k;

is the link idle rate where the packet is k on the grid service connection request (i, j) with priority k at time t.

6. The method of claim 5, wherein the link idle rate is calculated by the formula:

Is the total wavelength number of k in the grouping on the power grid service connection request (i, j) with the priority of k; /(I) Is the number of wavelengths used for the service connection request (i, j) with priority k at time t.

7. A computing device, comprising:

A processor; and

A memory storing a computer program which, when executed by the processor, causes the processor to perform the method of any one of claims 1-6.