CN114285758A - Communication network optimization simulation system, method and device based on OPNET - Google Patents
Communication network optimization simulation system, method and device based on OPNET Download PDFInfo
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Abstract
The application relates to a communication network optimization simulation system, method, device, computer equipment, storage medium and computer program product based on OPNET, comprising: the topological structure construction module acquires parameter information of communication nodes of various types in the communication network, determines the connection relation among the communication nodes of various types and constructs the topological structure network; the communication link sensing module transmits the data detection packet to a target communication node through a topological structure network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node; the optimal path determining module constructs an optimal path selection formula and then obtains an optimal path selection result by using a particle swarm algorithm; and the network optimization simulation module verifies the optimal path selection result to obtain a network optimization simulation result. The method and the device achieve the optimization goal of reducing data packet loss and end-to-end delay, and improve network optimization efficiency.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to an OPNET-based communication network optimization simulation system, method, apparatus, computer device, storage medium, and computer program product.
Background
With the geometric increase of information quantity, the information communication network is under greater and greater pressure, and the requirement on the processing capacity of information communication services is continuously increased.
At present, the transmission of information is mainly accomplished through wide area communication network, and when one end needs to send information resource to the other end, if the inhomogeneous of resource distribution, some wide area communication network link just can not in time forward, transmit, and a large amount of information resources will block up at the channel mouth, and the queuing is waited for and is forwarded, causes the network and blocks up the problem promptly. Meanwhile, links with less resource distribution are idle, and network communication bandwidth resources are wasted, so that the problem of network congestion is solved, and the method has important practical significance for optimizing wide area communication network resources.
Therefore, a communication network optimization simulation mode is needed to achieve reasonable scheduling of communication network resources and improve network optimization efficiency.
Disclosure of Invention
In view of the above, it is necessary to provide a communication network optimization simulation system, method, apparatus, computer device, computer readable storage medium and computer program product based on OPNET for solving the above technical problems.
In a first aspect, the application provides an OPNET-based communication network optimization simulation system. The system comprises:
the system comprises a topological structure construction module, a communication link perception module, an optimal path determination module and a network optimization simulation module; the topological structure building module, the communication link sensing module, the optimal path determining module and the network optimization simulation module are in communication connection;
the topological structure constructing module is used for acquiring parameter information of each type of communication node in the communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
the communication link perception module is used for transmitting a data detection packet to a target communication node through the topological structure network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
the optimal path determining module is used for constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating the optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
the network optimization simulation module is used for verifying the optimal path selection result according to preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
In one embodiment, the communication nodes include at least a switch, a host router, and a label node;
the topology structure building module is further configured to obtain a data link layer protocol of the switch, and obtain an address forwarding table of the switch according to the data link layer protocol; adding the switch closest to the mark node into a preset queue according to the address forwarding table; and traversing each switch in the preset queue, and connecting the switch with the downstream port being the leaf port with the host router.
In one embodiment, the communication link awareness module is further configured to determine a starting switch in the topology network; sending the data probe packet to the target communication node through the originating switch; the target communication node is a communication node connected with the starting switch; calculating the residual capacity of a communication channel corresponding to a communication link according to the number of the data detection packets received by the target communication node; and determining the communication link state of the communication channel according to the residual capacity.
In one embodiment, the obtaining the remaining capacity of the communication channel comprises:
wherein, C is the residual capacity of the communication channel; a is a channel broadband; s is that the target communication node receives the number of the simulation detection packets; and N is the total number of the sent out simulation detection packets.
In one embodiment, the particle swarm algorithm is obtained by:
wherein V represents a set of all said switches in the communication network; r represents the set of all said communication links in the communication network; (s, D, B) represents the communication transmission process from the originating switch s to the final destination switch D, where D represents the maximum delay threshold; b is the communication link bandwidth.
In a second aspect, the application further provides a communication network optimization simulation method based on the OPNET. The method comprises the following steps:
acquiring parameter information of communication nodes of various types in a communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
transmitting a data probe packet to a target communication node through the topology network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating the optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
verifying the optimal path selection result according to a preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
In a third aspect, the application further provides a communication network optimization simulation device based on the OPNET. The device comprises:
the parameter acquisition module is used for acquiring parameter information of communication nodes of various types in a communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
the node detection module is used for transmitting a data detection packet to a target communication node through the topological structure network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
the path selection module is used for constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating the optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
the path verification module is used for verifying the optimal path selection result according to preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
In a fourth aspect, the present application further provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program:
acquiring parameter information of communication nodes of various types in a communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
transmitting a data probe packet to a target communication node through the topology network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating the optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
verifying the optimal path selection result according to a preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
In a fifth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
acquiring parameter information of communication nodes of various types in a communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
transmitting a data probe packet to a target communication node through the topology network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating the optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
verifying the optimal path selection result according to a preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
In a sixth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:
acquiring parameter information of communication nodes of various types in a communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
transmitting a data probe packet to a target communication node through the topology network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating the optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
verifying the optimal path selection result according to a preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
The communication network optimization simulation system, method, device, computer equipment, storage medium and computer program product based on the OPNET comprise: the system comprises a topological structure construction module, a communication link perception module, an optimal path determination module and a network optimization simulation module; the topological structure building module, the communication link sensing module, the optimal path determining module and the network optimization simulation module are in communication connection; the topological structure constructing module is used for acquiring parameter information of communication nodes of various types in a communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation; the communication link sensing module is used for transmitting the data detection packet to a target communication node through a topological structure network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node; the optimal path determining module is used for constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating an optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result; the network optimization simulation module is used for verifying the optimal path selection result according to preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result. By combining with an OPNET network simulation tool, the load balance of a communication network link is realized through reasonable scheduling of communication network resources, so that a wide area communication network is optimized, the bandwidth resources of the communication link can be fully utilized, information resources are reasonably distributed, the optimization target of reducing data packet loss and end-to-end delay is finally achieved, and the network optimization efficiency is improved.
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FIG. 1 is a schematic diagram of a load balancing principle of a communication network according to an embodiment;
fig. 2 is a diagram illustrating the results of the communication network optimization simulation system based on OPNET in one embodiment;
FIG. 3 is a schematic flow chart of a basic flow of a particle swarm algorithm in one embodiment;
FIG. 4 is a schematic flow diagram of a simulation for network optimization in one embodiment;
FIG. 5 is a block diagram of a wide area communication network topology in one embodiment;
fig. 6 is a schematic flow chart of an OPNET-based communication network optimization simulation method in an embodiment;
fig. 7 is a block diagram of an OPNET-based communication network optimization simulation apparatus according to an embodiment;
FIG. 8 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The wide area communication network optimization method based on the OPNET can be realized through the communication network optimization simulation system based on the OPNET:
if there is a large number of message flows in the network, congestion may occur due to the limited forwarding capability of the nodes. Network congestion can be described by the following equation:
sigma task transmission requirement > available resources of communication network link; (1)
once congestion occurs in a communication network link, the transmission performance of the communication network link is reduced straightly, and even a large amount of data packet loss problem occurs, so that the data integrity is insufficient. Therefore, in order to optimize the data transmission performance of the wide area communication network, the communication network optimization simulation system based on the OPNET of the present disclosure can implement the optimized scheduling of the network, and the principle is as shown in fig. 1, that is, the load or the work task is reasonably distributed to other communication links, so that a large number of tasks are prevented from being concentrated on one link node, thereby reducing the occurrence of congestion and improving the task transmission efficiency of the communication network.
The embodiment of the present application provides an OPNET-based communication network optimization simulation system, a structure of which is shown in fig. 2, and includes: the system comprises a topological structure construction module 11, a communication link perception module 12, an optimal path determination module 13 and a network optimization simulation module 14; the topological structure constructing module 11, the communication link perceiving module 12, the optimal path determining module 13 and the network optimization simulation module 14 are in communication connection; the topology structure building module 11 is configured to obtain parameter information of each type of communication node in the communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation; the communication link sensing module 12 is configured to transmit the data detection packet to a target communication node through a topology network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node; an optimal path determining module 13, configured to construct an optimal path selection formula according to communication nodes and communication link states of the topology network; calculating an optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result; the network optimization simulation module 14 is configured to verify the optimal path selection result according to a preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result. The embodiment combines an OPNET network simulation tool, reasonably schedules communication network resources, and realizes communication network link load balancing, so that a wide area communication network is optimized, communication link bandwidth resources can be fully utilized, information resources are reasonably distributed, an optimization target of reducing data packet loss and end-to-end delay is finally achieved, and network optimization efficiency is improved.
In one embodiment, the communication nodes include at least a switch, a host router, and a label node; the topological structure constructing module is also used for acquiring a data link layer protocol of the switch and acquiring an address forwarding table of the switch according to the data link layer protocol; adding the switch closest to the mark node into a preset queue according to the address forwarding table; and traversing each switch in the preset queue, and connecting the switch with the downstream port being the leaf port with the host router.
With the continuous deepening of information interaction and sharing, the scale and structure of the communication network are continuously upgraded, which makes the communication network planning more and more difficult while improving the communication performance. In order to realize wide area communication network optimization through load balancing scheduling, the network topology needs to be firstly determined. The huge scale and the structural complexity of the wide area communication network make the topology construction difficult, so the embodiment automatically generates the communication network topology through a discovery algorithm.
Specifically, the network topology discovery refers to automatically discovering a node set N existing in a communication network and a connection relationship between the node set N and the node set N, and is specifically realized by the following steps: step 1: defining all routers, switches, hosts and mark nodes in a communication network; step 2: reading the data link layer protocol of each switch, and acquiring an address forwarding table of the switch: and step 3: searching the switch closest to the mark node as a root node of the topology tree, adding the switch into the queue T to be found, and then searching the switch closest to the address of the switch of the root node until all switches are added into the queue T to be found; and 4, step 4: selecting a first switch node T1 in the queue to be found; and 5: determining the connection relation of a T1 downlink port; if the downlink port is a leaf port, the downlink port is connected with the dummy equipment and the host router, otherwise, the downlink port is not connected. Step 6: and (5) repeating the steps 4 to 5, and judging the connection relation of the second switch node in the discovery queue until all the switches in the queue to be discovered of all the switches are traversed, so that a large-wide area communication network topology structure is formed.
In the embodiment, the topological structure is constructed and obtained by obtaining each communication node according to the incidence relation between the communication nodes and the data processing step, so that the network optimization efficiency is improved.
In one embodiment, the communication link awareness module is further configured to determine an originating switch in the topology network; sending a data detection packet to a target communication node through an initial switch; the target communication node is a communication node connected with the starting switch; calculating the residual capacity of a communication channel corresponding to a communication link according to the number of the data detection packets received by the target communication node; the communication link status of the communication channel is determined based on the remaining capacity.
In the embodiment, the state of the communication link is sensed by means of OPNET network simulation software, and the current capacity of the communication channel is judged to be remained and whether congestion occurs or not. The OPNET can accurately analyze the performance and the behavior of a complex network, can be arbitrarily inserted into a standard or user-specified probe, collects data information, and then obtains a result to prepare for selecting an optimal communication path for subsequent loads, and is specifically realized by the following steps: step 1: inputting the wide area communication network topological structure into OPNETOPNET network simulation software; step 2: determining an originating switch of a wide area communication network; and step 3: generating a simulation detection packet by the OPNET; and 4, step 4: sending out a detection packet to each communication node connected with the starting switch by the starting switch; and 5: the target communication node receives the simulation detection packets and counts the receiving quantity; step 6: the remaining capacity of the communication channel is calculated by the following formula:
wherein, C is the residual capacity of the communication channel; a is a channel broadband; s is that the target communication node receives the number of the simulation detection packets; and N is the total number of the sent out simulation detection packets.
And 7: it is judged whether or not the remaining capacity is 0 or more. If the residual capacity is greater than or equal to 0, the communication channel is not blocked; otherwise, the communication is congested, and the communication channel cannot complete the resource forwarding work in real time.
In this embodiment, a data probe packet is sent to a target communication node through an originating switch; calculating the residual capacity of a communication channel corresponding to a communication link according to the number of the data detection packets received by the target communication node; the communication link state of the communication channel is determined according to the residual capacity, and the determination efficiency of the communication link state is improved.
In one embodiment, the optimal path determining module is configured to construct an optimal path selection formula according to communication nodes and communication link states of the topology network; and operating the optimal path selection formula according to the particle swarm algorithm to obtain an optimal path selection result.
In the embodiment, based on the communication link state determined by the communication link sensing module, an intelligent algorithm is used to dynamically select an optimal path capable of quickly realizing communication so as to achieve the communication network optimization target, and a basic flow of a particle swarm algorithm is shown in fig. 3.
Specifically, the particle swarm algorithm is used to describe the problem to be studied in this section, and the expression formula is as follows:
wherein V represents the set of all switches in the communication network; r represents the set of all communication links in the communication network; (s, D, B) represents the communication transmission process from the originating switch s to the final destination switch D, where D represents the maximum delay threshold; b is the communication link bandwidth.
Let L (s, d) be the path of possible choice from the originating switch s to the final destination switch d. It describes the formula as follows:
L(s,d)＝(s,s1,...,i,j,...,d1,d)；
thus, all the conditions of the network link included in L (s, d) are described in detail:
wherein, BandsdBandwidth Delay that indicates the path L (s, d) can usesdRepresenting the delay value of the path L (s, d). p is a radical ofijIs the state of the link; delayijRepresenting the delay of the link; bandijRepresenting the available bandwidth of the link.
The formula for determining whether a selected path is the optimal communication path is as follows:
fitness＝(w0×Re(L(s,d))+w1×C)-1；
wherein, the fitness is an adaptation function; w is a0And w1Is the weight; re (L (s, d)) represents a communication bandwidth consumption function; c represents the residual capacity of the communication channel; b represents the required value of the bandwidth when the communication task is transmitted in the network; h (L (s, d)) represents the sum of the weights of the paths L (s, d).
An optimal path selection formula is constructed in the following mode, and the optimal path can be obtained by utilizing a particle swarm optimization to carry out optimization solution:
wherein minRe (L (s, d)) is an objective function; band (R)sdNot less than B and DelaysdD is less than or equal to the constraint condition of the objective function.
The optimal path selection formula can be expressed as: on the premise of realizing the maximum value of the adaptation function, the path L (s, d) distributes the communication load on the link with less bandwidth consumption (the largest channel capacity) as much as possible, thereby avoiding the possibility that tasks are concentrated on one link and solving the problem of communication congestion.
In the embodiment, the optimal path selection formula is operated through the particle swarm algorithm, so that the efficiency of obtaining the optimal path selection result is improved.
In one embodiment, the network optimization simulation module is configured to verify the optimal path selection result according to a preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
Specifically, the network optimization simulation module performs network optimization simulation through the steps shown in fig. 4; firstly, generating a communication task in a power communication network; generating a corresponding network topology according to the communication task, and establishing a network model; after corresponding communication task quantity parameters are imported into the network model, an OPNET simulation tool is operated to obtain a simulation result; if the simulation does not reach the preset condition, the communication task can be reset and executed until a simulation result meeting the condition is obtained; and determining the performance of the communication network by counting the simulation result.
In the embodiment, the optimal path selection result is verified through the network optimization simulation module, so that the reliability of the verification result is ensured.
In one embodiment, the power communication network carries the transmission work of information services such as power system scheduling, management, network state, user data and the like, and is an important component of the power system, so that the communication network of a certain household electrical appliance enterprise is selected as an object, and a network topology structure is constructed by utilizing a researched automatic discovery algorithm.
Therefore, the communication network optimization simulation system based on OPNET of the present disclosure can be applied to the wide area communication network topology structure shown in fig. 5, and the composition situation in the power communication network is shown in table 1:
table 1 composition table in power communication network
The optimal path is solved by utilizing the particle swarm algorithm, and when the transmission performance of the communication network is optimized, the set related parameters are shown in the table 2:
TABLE 2 particle swarm optimization-related parameters
Determining the optimization effect of the transmission performance of the communication network by the following evaluation criteria of the performance of the communication network, including:
(1) link load rate
The link load rate is the ratio between the workload bandwidth which can be actually processed by the communication link and the total bandwidth of the link, and the calculation formula is as follows:
wherein, the LLR is the link load rate, and once the value exceeds 60%, the link falls into heavy load and has congestion problem; a1 represents the workload bandwidth that the link can actually handle; and a is the total bandwidth of the link.
(2) Degree of load balancing
The load balance degree refers to the balance of the load borne by each link. The calculation formula is as follows:
wherein, L is the load balance degree; b is the average utilization rate of the link bandwidth; bmaxMaximum bandwidth utilization for the link; m is the number of links.
(3) Ratio of failed services
The failure service ratio is the ratio of the links with packet loss in task transmission in the communication links to the number of all links.
Wherein, F (t) is the ratio of failed services in t time; and f (t) represents the number of links in which packet loss occurs in task transmission within the time t.
After the above processing procedure, it is assumed that the server sends 12556 data packets to the power communication network, and forwards the data packets to the client through the power communication network, and then performs optimized scheduling by using the method of this embodiment, and counts the maximum link load rate, load balancing degree, and failure traffic ratio, according to the method 1: high-speed railway wireless communication network optimization scheme based on MEC (li bin. high-speed railway wireless communication network optimization scheme based on MEC [ J ] telecommunication science, 2019,035(011) 88-95), method 2: communication scheduling methods for communication rearrangement and message merging (patau, yang chapter, liuqingka, etc.. study [ J ] in conjunction with communication scheduling methods for communication rearrangement and message merging [ J ]. computer engineering and science, 2020,42(2):191-196) and method 3: the communication network performance statistical results are obtained by comparing the researches of the hybrid-based network congestion control routing algorithm [ J ] in the LLN, computer science, 2019,046(006): 107-:
table 3 statistical results of communication network performance
As can be seen from table 3, after the communication network transmission task is uniformly scheduled by using the communication network optimization simulation system based on OPNET of the present disclosure, the maximum link load rate is only 24.55%, the load balance degree reaches above 0.9, and the failure service ratio is 0.25%, which makes a great progress compared with the methods proposed by methods 1 to 3, and shows that the studied method realizes the optimization of the communication network transmission performance by uniformly scheduling the communication network transmission task.
In one embodiment, as shown in fig. 6, there is provided an OPNET-based communication network optimization simulation method, including the following steps:
In the communication network optimization simulation method based on the OPNET, parameter information of each type of communication nodes in the communication network is obtained; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation; transmitting the data detection packet to a target communication node through a topological structure network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node; constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating an optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result; verifying the optimal path selection result according to a preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result. By combining with an OPNET network simulation tool, the load balance of a communication network link is realized through reasonable scheduling of communication network resources, so that a wide area communication network is optimized, the bandwidth resources of the communication link can be fully utilized, information resources are reasonably distributed, the optimization target of reducing data packet loss and end-to-end delay is finally achieved, and the network optimization efficiency is improved.
It should be understood that, although the steps in the flowcharts related to the embodiments are shown in sequence as indicated by the arrows, the steps are not necessarily executed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the above embodiments may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.
Based on the same inventive concept, the embodiment of the application also provides an OPNET-based communication network optimization simulation device for realizing the OPNET-based communication network optimization simulation method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the method, so that specific limitations in one or more embodiments of the communication network optimization simulation device based on OPNET provided below can be referred to the limitations of the communication network optimization simulation method based on OPNET, and are not described herein again.
In one embodiment, as shown in fig. 7, there is provided an OPNET-based communication network optimization simulation apparatus, including: a parameter obtaining module 702, a node detecting module 704, a path selecting module 706 and a path verifying module 708, wherein:
a parameter obtaining module 702, configured to obtain parameter information of each type of communication node in a communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
a node probing module 704, configured to transmit the data probing packet to a target communication node through a topology network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
a path selection module 706, configured to construct an optimal path selection formula according to states of communication nodes and communication links of the topology network; calculating an optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
a path verification module 708, configured to verify the optimal path selection result according to a preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
In one embodiment, the communication nodes include at least a switch, a host router, and a label node; the parameter obtaining module 702 is further configured to obtain a data link layer protocol of the switch, and obtain an address forwarding table of the switch according to the data link layer protocol; adding the switch closest to the mark node into a preset queue according to the address forwarding table; and traversing each switch in the preset queue, and connecting the switch with the downstream port being the leaf port with the host router.
In one embodiment, the node probing module 704 is further configured to determine an originating switch in the topology network; sending a data detection packet to a target communication node through an initial switch; the target communication node is a communication node connected with the starting switch; calculating the residual capacity of a communication channel corresponding to a communication link according to the number of the data detection packets received by the target communication node; the communication link status of the communication channel is determined based on the remaining capacity.
The various modules in the communication network optimization simulation device based on OPNET can be realized in whole or in part by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 8. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing OPNET-based communication network optimization simulation data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement an OPNET-based communication network optimization simulation method.
Those skilled in the art will appreciate that the architecture shown in fig. 8 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring parameter information of communication nodes of various types in a communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
transmitting the data detection packet to a target communication node through a topological structure network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating an optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
verifying the optimal path selection result according to a preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
In one embodiment, the processor, when executing the computer program, further performs the steps of: acquiring a data link layer protocol of a switch, and acquiring an address forwarding table of the switch according to the data link layer protocol; adding the switch closest to the mark node into a preset queue according to the address forwarding table; and traversing each switch in the preset queue, and connecting the switch with the downstream port being the leaf port with the host router.
In one embodiment, the processor, when executing the computer program, further performs the steps of: determining a starting switch in the topological structure network; sending a data detection packet to a target communication node through an initial switch; the target communication node is a communication node connected with the starting switch; calculating the residual capacity of a communication channel corresponding to a communication link according to the number of the data detection packets received by the target communication node; the communication link status of the communication channel is determined based on the remaining capacity.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring parameter information of communication nodes of various types in a communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
transmitting the data detection packet to a target communication node through a topological structure network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating an optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
verifying the optimal path selection result according to a preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring a data link layer protocol of a switch, and acquiring an address forwarding table of the switch according to the data link layer protocol; adding the switch closest to the mark node into a preset queue according to the address forwarding table; and traversing each switch in the preset queue, and connecting the switch with the downstream port being the leaf port with the host router.
In one embodiment, the computer program when executed by the processor further performs the steps of: determining a starting switch in the topological structure network; sending a data detection packet to a target communication node through an initial switch; the target communication node is a communication node connected with the starting switch; calculating the residual capacity of a communication channel corresponding to a communication link according to the number of the data detection packets received by the target communication node; the communication link status of the communication channel is determined based on the remaining capacity.
In one embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, performs the steps of:
acquiring parameter information of communication nodes of various types in a communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
transmitting the data detection packet to a target communication node through a topological structure network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating an optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
verifying the optimal path selection result according to a preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring a data link layer protocol of a switch, and acquiring an address forwarding table of the switch according to the data link layer protocol; adding the switch closest to the mark node into a preset queue according to the address forwarding table; and traversing each switch in the preset queue, and connecting the switch with the downstream port being the leaf port with the host router.
In one embodiment, the computer program when executed by the processor further performs the steps of: determining a starting switch in the topological structure network; sending a data detection packet to a target communication node through an initial switch; the target communication node is a communication node connected with the starting switch; calculating the residual capacity of a communication channel corresponding to a communication link according to the number of the data detection packets received by the target communication node; the communication link status of the communication channel is determined based on the remaining capacity.
It should be noted that, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.
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 hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), Magnetic Random Access Memory (MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above examples only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.
Claims (10)
1. An OPNET-based communication network optimization simulation system is characterized by comprising: the system comprises a topological structure construction module, a communication link perception module, an optimal path determination module and a network optimization simulation module; the topological structure building module, the communication link sensing module, the optimal path determining module and the network optimization simulation module are in communication connection;
the topological structure constructing module is used for acquiring parameter information of each type of communication node in the communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
the communication link perception module is used for transmitting a data detection packet to a target communication node through the topological structure network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
the optimal path determining module is used for constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating the optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
the network optimization simulation module is used for verifying the optimal path selection result according to preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
2. The method of claim 1, wherein the communication nodes comprise at least a switch, a host router, and a label node;
the topology structure building module is further configured to obtain a data link layer protocol of the switch, and obtain an address forwarding table of the switch according to the data link layer protocol; adding the switch closest to the mark node into a preset queue according to the address forwarding table; and traversing each switch in the preset queue, and connecting the switch with the downstream port being the leaf port with the host router.
3. The method of claim 1, wherein the communication link awareness module is further configured to determine a starting switch in the topology network; sending the data probe packet to the target communication node through the originating switch; the target communication node is a communication node connected with the starting switch; calculating the residual capacity of a communication channel corresponding to a communication link according to the number of the data detection packets received by the target communication node; and determining the communication link state of the communication channel according to the residual capacity.
4. The method of claim 3, wherein obtaining the remaining capacity of the communication channel comprises:
wherein, C is the residual capacity of the communication channel; a is a channel broadband; s is that the target communication node receives the number of the simulation detection packets; and N is the total number of the sent out simulation detection packets.
5. The method of claim 1, wherein the particle swarm algorithm is obtained by:
wherein V represents a set of all said switches in the communication network; r represents the set of all said communication links in the communication network; (s, D, B) represents the communication transmission process from the originating switch s to the final destination switch D, where D represents the maximum delay threshold; b is the communication link bandwidth.
6. A communication network optimization simulation method based on OPNET is characterized by comprising the following steps:
acquiring parameter information of communication nodes of various types in a communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
transmitting a data probe packet to a target communication node through the topology network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating the optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
verifying the optimal path selection result according to a preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
7. An OPNET-based communication network optimization simulation device, characterized in that the device comprises:
the parameter acquisition module is used for acquiring parameter information of communication nodes of various types in a communication network; determining the connection relation between communication nodes of various types according to the parameter information of the communication nodes; constructing a topological structure network according to the connection relation;
the node detection module is used for transmitting a data detection packet to a target communication node through the topological structure network; determining the communication link state of the corresponding communication link according to the number of the data detection packets received by the target communication node;
the path selection module is used for constructing an optimal path selection formula according to the communication nodes and the communication link states of the topological structure network; calculating the optimal path selection formula according to a particle swarm algorithm to obtain an optimal path selection result;
the path verification module is used for verifying the optimal path selection result according to preset network optimization simulation logic to obtain a verification result; and generating a network optimization simulation result according to the verification result.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of claim 6.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method as claimed in claim 6.
10. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of claim 6 when executed by a processor.
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