A flow pressure load balancing routing method and system based on incomplete information

Abstract

The present invention relates to the field of communication technology, and specifically discloses a flow pressure load balancing routing method and system based on incomplete information, wherein the method comprises: before each round of service is transmitted from a starting node to a convergence node, a reasonable next hop is selected for each routing node based on delay redundancy to construct a static network topology; according to the static network topology, a bandwidth resource allocation benefit function is established for each routing node; according to the bandwidth resource allocation benefit function, a linear programming problem for maximizing node benefits is established; based on the KKT condition, the linear programming problem is solved to obtain an optimal solution for bandwidth resource allocation; and the change in the number of real-time transmission services of each routing node is monitored, and when the number of real-time transmission services of any node changes, a bandwidth allocation plan is immediately updated.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a flow pressure load balancing routing method and system based on incomplete information. Background Art

[0002] With the rapid progress of contemporary communication technology and the rapid development of information processing technology, people's demand for equipment monitoring, environmental monitoring and other technologies is becoming increasingly urgent. Therefore, wireless sensor networks were born. It is composed of a certain number of sensor nodes, each of which has the ability to transmit communication and perception and judgment. The nodes are interconnected in a self-organizing mode, with the characteristics of large-scale, unmanned monitoring, and low power consumption. Rechargeable wireless sensor networks are composed of a large number of rechargeable wireless sensors and are widely used in large-scale environmental monitoring systems such as smart grids.

[0003] Traffic pressure load balancing is a key issue in wireless sensor networks, especially when node density is uneven or some nodes fail. Traditional load balancing methods are usually based on the assumption of complete information, that is, each node has global network status information. However, in actual situations, nodes may only have partial or incomplete information, which makes traditional methods face challenges in dealing with load balancing problems under incomplete information.

[0004] Routing optimization is one of the main means to achieve load balancing in rechargeable wireless sensor networks. Reasonable routing strategies can reduce the pressure on high-load nodes and achieve network load balancing. There are massive concurrent services in the nodes, and different services have different latency requirements, which brings huge pressure to the network and also causes imbalance in network load. Therefore, a new solution is urgently needed. Summary of the invention

[0005] In order to break the limitation of a single routing mode, the present application provides a traffic pressure load balancing routing method based on incomplete information, including:

[0006] Step S1: Before each round of service transmission from the starting node to the aggregation node, a reasonable next hop is selected for each routing node based on delay redundancy to build a static network topology;

[0007] Step S2: establishing a bandwidth resource allocation benefit function for each routing node according to the static network topology;

[0008] Step S3: Establishing a linear programming problem for maximizing node benefits according to the bandwidth resource allocation benefit function;

[0009] Step S4: Solving the linear programming problem based on the KKT condition to obtain an optimal solution for bandwidth resource allocation;

[0010] Step S5: monitor the change of the number of real-time transmission services of each routing node. When the number of real-time transmission services of any node changes, repeat steps S3 and S4 to update the bandwidth allocation plan.

[0011] In some specific embodiments, in step S1, the static network topology is determined according to the following formula:

[0012]

[0013] Among them, τ j is the delay redundancy of node j, θ i is the state collection range of node i, which contains the state information of nodes in the forward range. Its information includes the delay redundancy point of the last service to be sent by the node to the aggregation node. The delay redundancy calculation method is as follows:

[0014]

[0015] Among them, k last The last service relayed by the node to the sink node. is the transmission delay requirement of the last service sent from node j to the sink node, It is the time taken for the service to be transmitted to the aggregation node. The calculation formula is:

[0016]

[0017] Where k represents the kth service that node j needs to transmit in a specified working round, B j is the bandwidth of node j, Ψ j represents the set of services to be transmitted by node j, k is the data volume of service k.

[0018] In some specific embodiments, the state collection range construction method of node i is as follows:

[0019]

[0020] Among them, d i,j represents the distance between nodes i and j, V represents the numbered set of nodes, where d i,s and d j,s Respectively represent the upload distance of node i and node j, n h Specifies the maximum number of upload hops.

[0021] In some specific embodiments, in step S2, according to the static network topology, for each node, the bandwidth allocation ratio is dynamically adjusted to respond to the delay change and maximize the node's benefit. To ensure that the service with lower delay redundancy obtains a higher bandwidth allocation ratio, a node bandwidth resource allocation benefit function is established:

[0022]

[0023] Among them, Θ i is the bandwidth resource allocation benefit function of node i, Ψ i represents the set of services to be transmitted by node i, γ i,k is the bandwidth B of node i for service k i Allocation ratio, τ i,k It represents the delay redundancy of the service k, specifically the delay redundancy of the last unit data. Its calculation method is:

[0024] τ i,k =ζ i,k -Γ i,k

[0025] Among them, i,k is the transmission delay requirement of service k in node i, Γ i,k It is the time taken for the last unit data of the service data packet to be generated and sent to node i.

[0026] In some specific embodiments, in step S3, by utilizing reasonable allocation of bandwidth resources to meet the service transmission delay requirement, a linear programming problem is constructed, and the maximum bandwidth resource allocation benefit is determined according to the following formula:

[0027]

[0028] Among them, i represents the set of services to be transmitted by node i, γ i,k is the bandwidth B of node i for service k i Allocation ratio.

[0029] To achieve the same invention purpose, the present application also provides a traffic pressure load balancing routing system based on incomplete information, including:

[0030] Network topology building module: used to select a reasonable next hop for each routing node based on delay redundancy before each round of business is transmitted from the starting node to the aggregation node, and to build a static network topology;

[0031] A revenue function establishment module: used to establish a bandwidth resource allocation revenue function for each routing node according to the network topology;

[0032] Linear programming calculation module: used to reasonably allocate bandwidth resources according to the network topology and node bandwidth resource allocation benefit function, with the goal of meeting the service transmission delay requirement, and establish a linear programming problem for maximizing node benefits according to the bandwidth resource allocation benefit function;

[0033] Resource allocation module: used to solve the linear programming based on KKT conditions to obtain the optimal solution for bandwidth resource allocation, and monitor the changes in the number of real-time transmission services of each routing node. When the number of real-time transmission services of any node changes, the bandwidth allocation plan is updated.

[0034] In some specific embodiments, in the network topology building module, the static network topology is determined according to the following formula:

[0035]

[0036] Among them, τ j is the delay redundancy of node j, θ i is the state collection range of node i, which contains the state information of nodes in the forward range. Its information includes the delay redundancy point of the last service to be sent by the node to the aggregation node. The delay redundancy calculation method is as follows:

[0037]

[0038] Among them, k last The last service relayed by the node to the sink node. is the transmission delay requirement of the last service sent from node j to the sink node, It is the time taken for the service to be transmitted to the aggregation node. The calculation formula is:

[0039]

[0040] Where k represents the kth service that node j needs to transmit in a specified working round, B j is the bandwidth of node j, Ψ j represents the set of services to be transmitted by node j, k is the data volume of service k.

[0041] In some specific embodiments, the state collection range construction method of node i is as follows:

[0042]

[0043] Among them, d i,j represents the distance between nodes i and j, V represents the numbered set of nodes, where d i,s and d j,sRespectively represent the upload distance of node i and node j, n h Specifies the maximum number of upload hops.

[0044] In some specific embodiments, in the revenue function establishment module, according to the static network topology, for each node, the bandwidth allocation ratio is dynamically adjusted to respond to the delay change and maximize the node's revenue. To ensure that the service with lower delay redundancy obtains a higher bandwidth allocation ratio, a node bandwidth resource allocation revenue function is established:

[0045]

[0046] Among them, Θ i is the bandwidth resource allocation benefit function of node i, Ψ i represents the set of services to be transmitted by node i, γ i,k is the bandwidth B of node i for service k i Allocation ratio, τ i,k It represents the delay redundancy of the service k, specifically the delay redundancy of the last unit data. Its calculation method is:

[0047] τ i,k =ζ i,k -Γ i,k

[0048] Among them, i,k is the transmission delay requirement of service k in node i, Γ i,k It is the time taken for the last unit data of the service data packet to be generated and sent to node i.

[0049] In some specific embodiments, in the linear programming calculation module, by utilizing reasonable allocation of bandwidth resources to meet the service transmission delay requirement, a linear programming problem is constructed, and the maximum bandwidth resource allocation benefit is determined according to the following formula:

[0050]

[0051] Among them, i represents the set of services to be transmitted by node i, γ i,k is the bandwidth B of node i for service k i Allocation ratio.

[0052] Beneficial effects of the above technical solution:

[0053] The traffic pressure load balancing routing method based on incomplete information described in the present application comprehensively considers the limitation that nodes can usually only collect status information of local networks within a limited range, and dynamically allocates bandwidth based on the KKT (Karush-Kuhn-Tucker) condition. Once the number of node services changes, bandwidth resources are reallocated. Compared with the fixed average allocation method, nodes can flexibly allocate bandwidth resources according to the requirements of different services, meet the latency requirements of differentiated services, avoid inefficient use of bandwidth, and intelligently achieve network workload balance. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0055] Figure 1 A flow chart of a flow pressure load balancing routing method based on incomplete information provided by an embodiment of the present invention;

[0056] Figure 2 A schematic diagram of the structure of a traffic pressure load balancing routing system based on incomplete information provided by an embodiment of the present invention;

[0057] Figure 3 A delay comparison diagram of a traffic pressure load balancing routing method based on incomplete information and a bandwidth resource average allocation method provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0059] Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar symbols throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0060] Embodiment 1

[0061] An embodiment of the present invention provides a flow pressure load balancing routing method based on incomplete information, referring to Figure 1 As shown, including:

[0062] Step S1: Before each round starts, a reasonable next hop is selected for each routing node based on delay redundancy to build a static network topology.

[0063] In a specific embodiment of the present invention, in step S1, the static network topology is determined according to the following formula:

[0064]

[0065] Among them, τ j is the delay redundancy of node j, θ i is the state collection range of node i, which contains the state information of nodes in the forward range. Its information includes the delay redundancy of the last service to be sent by the node to the aggregation node. The node delay redundancy calculation method is as follows:

[0066]

[0067] Among them, k last The last service relayed by the node to the sink node. is the transmission delay requirement of the last service sent from node j to the sink node, It is the time taken for the service to be transmitted to the aggregation node. The calculation formula is:

[0068]

[0069] Where k represents the kth service that node j needs to transmit in a specified working round. j is the bandwidth of node j, Ψ j represents the set of services to be transmitted by node j, k is the data volume of service k.

[0070] The state collection range construction method of node i is as follows:

[0071]

[0072] Among them, d i,j represents the distance between nodes i and j, V represents the node set, which records the numbers of all nodes, where d i,s and d j,s denotes the upload distance of node i and node j respectively, which means the distance between the node and the sink node, n h Specifies the maximum number of upload hops.

[0073] Step S2: According to the generated network topology, a bandwidth resource allocation benefit function is established for each routing node.

[0074] In a specific embodiment of the present invention, in step S2, based on the network topology constructed in step 1, for each node, the bandwidth allocation ratio is dynamically adjusted to respond to the delay change and maximize the node's benefit. To ensure that the service with lower delay redundancy obtains a higher bandwidth allocation ratio, a node bandwidth resource allocation benefit function is established:

[0075]

[0076] Among them, Θ i is the bandwidth resource allocation benefit function of node i, Ψ i represents the set of services to be transmitted by node i, γ i,k is the bandwidth B of node i for service k i Allocation ratio, τ i,k It represents the delay redundancy of the service k, specifically the delay redundancy of the last unit data, which is calculated as follows:

[0077] τ i,k =ζ i,k -Γ i,k

[0078] Among them, i,k is the transmission delay requirement of service k in node i, Γ i,k It is the time taken for the last unit data of the service data packet to be generated and sent to node i.

[0079] Step S3: Establish a linear programming problem for maximizing node benefits according to the above steps.

[0080] In a specific embodiment of the present invention, in step S3, based on the above steps, the optimization target is defined as the benefit function in step S2, and a linear programming problem is constructed by reasonably allocating bandwidth resources to meet the service transmission delay requirement. Therefore, the optimization target is to maximize the bandwidth resource allocation benefit, which is expressed as follows:

[0081]

[0082] Among them, i represents the set of services to be transmitted by node i, γ i,k is the bandwidth B of node i for service k i Allocation ratio.

[0083] Step S4: Solve it based on the KKT (Karush-Kuhn-Tucker) condition to obtain the optimal solution for bandwidth resource allocation.

[0084] Step S5: monitor the change of the number of real-time transmission services of each routing node. When the number of real-time transmission services of any node changes, immediately repeat steps S3 and S4 to update the bandwidth allocation plan.

[0085] Reference Figure 3 As shown, in order to test the performance of the routing method proposed in the embodiment of the present invention, the routing method in this embodiment is simulated and compared with other existing methods, such as the bandwidth resource average allocation method, under the same network environment. The simulation environment is a square two-dimensional plane with a side length of 300m. The location of the aggregation node is in the center of the simulation square. The specific simulation process is as follows:

[0086] First, an initial service is assigned to all nodes, and the forward state collection range is determined. The next hop is selected from the nodes in the range to generate a static network topology.

[0087] Secondly, the method is aimed at routing optimization. Bandwidth resources are allocated to services within the node, and the delay redundancy after each service completes the transmission is calculated, so that the energy efficiency of the method can be clearly compared.

[0088] Finally, PYTHON is used as the simulation tool, and the system simulation environment parameters are set as follows:

[0089] 1) The number of nodes is 10;

[0090] 2) The bandwidth of each node is,B=75kbps;

[0091] 3) Determine the latency requirements for three types of services, which are 145 milliseconds, 320 milliseconds, and 40 milliseconds respectively;

[0092] 4) Determine the data volume of three types of services, which are 3500 bits, 7000 bits, and 1500 bits respectively;

[0093] 5) The maximum number of upload hops is set to 6, i.e. n h =6;

[0094] 6) Determine the maximum communication range of the node to be 100m;

[0095] It should be noted that the above parameters are not constant. Some parameters can be changed as needed for different simulation contents. The above parameters are only parameter values ​​in one embodiment. In other embodiments, they can also be other parameter values. The present invention is not limited to the above parameter values.

[0096] According to the above simulation process, the simulation results are as follows: Figure 3 shown.

[0097] Figure 3The transmission delay comparison results of this routing method and the average bandwidth resource allocation method in the same network environment.

[0098] It can be seen that the average bandwidth resource allocation method often exceeds the service delay requirement, and the service transmission delay of the routing method proposed in the present invention is obviously closer to the service transmission delay requirement than the average bandwidth resource allocation method.

[0099] Therefore, it can be seen from the above simulation results that the routing method in the present invention optimizes system performance, effectively improves resource utilization efficiency without increasing the difficulty of nodes collecting status information, and enhances the stability and sustainability of the network.

[0100] The traffic pressure load balancing routing method based on incomplete information described in the present application comprehensively considers the limitation that nodes can usually only collect status information of local networks within a limited range, and dynamically allocates bandwidth based on the KKT (Karush-Kuhn-Tucker) condition. Once the number of node services changes, bandwidth resources are reallocated. Compared with the fixed average allocation method, nodes can flexibly allocate bandwidth resources according to the requirements of different services, meet the latency requirements of differentiated services, avoid inefficient use of bandwidth, and intelligently achieve network workload balance.

[0101] Embodiment 2

[0102] An embodiment of the present invention provides a traffic pressure load balancing routing system based on incomplete information, referring to Figure 2 As shown, including:

[0103] Network topology building module 10: used to select a reasonable next hop for each routing node based on delay redundancy before each round of service is transmitted from the starting node to the aggregation node, and to build a static network topology;

[0104] The benefit function establishment module 20 is used to establish a bandwidth resource allocation benefit function for each routing node according to the network topology;

[0105] Linear programming calculation module 30: used to reasonably allocate bandwidth resources according to the network topology and node bandwidth resource allocation benefit function, with the goal of meeting the service transmission delay requirement, and establish a linear programming problem for maximizing node benefits according to the bandwidth resource allocation benefit function;

[0106] Resource allocation module 40: used to solve the linear programming based on KKT conditions to obtain the optimal solution for bandwidth resource allocation, and monitor the changes in the number of real-time transmission services of each routing node. When the number of real-time transmission services of any node changes, the bandwidth allocation plan is updated.

[0107] In a specific embodiment of the present invention, in the network topology building module 10, the static network topology is determined according to the following formula:

[0108]

[0109] Among them, τ j is the delay redundancy of node j, θ i is the state collection range of node i, which contains the state information of nodes in the forward range. Its information includes the delay redundancy point of the last service to be sent by the node to the aggregation node. The delay redundancy calculation method is as follows:

[0110]

[0111] Among them, k last The last service relayed by the node to the sink node. is the transmission delay requirement of the last service sent from node j to the sink node, It is the time taken for the service to be transmitted to the aggregation node. The calculation formula is:

[0112]

[0113] Where k represents the kth service that node j needs to transmit in a specified working round, B j is the bandwidth of node j, Ψ j represents the set of services to be transmitted by node j, k is the data volume of service k.

[0114] In a specific embodiment of the present invention, the method for constructing the state collection range of node i is as follows:

[0115]

[0116] Among them, d i,j represents the distance between nodes i and j, V represents the numbered set of nodes, where d i,s and d j,s Respectively represent the upload distance of node i and node j, n h Specifies the maximum number of upload hops.

[0117] In a specific embodiment of the present invention, in the benefit function establishment module 20, according to the static network topology, for each node, the bandwidth allocation ratio is dynamically adjusted to respond to the delay change and maximize the node's benefit. To ensure that the service with lower delay redundancy obtains a higher bandwidth allocation ratio, a node bandwidth resource allocation benefit function is established:

[0118]

[0119] Among them, Θ i is the bandwidth resource allocation benefit function of node i, Ψ i represents the set of services to be transmitted by node i, γ i,k is the bandwidth B of node i for service k i Allocation ratio, τ i,k It represents the delay redundancy of the service k, specifically the delay redundancy of the last unit data. Its calculation method is:

[0120] τ i,k =ζ i,k -Γ i,k

[0121] Among them, i,k is the transmission delay requirement of service k in node i, Γ i,k It is the time taken for the last unit data of the service data packet to be generated and sent to node i.

[0122] In a specific embodiment of the present invention, in the linear programming calculation module 30, by utilizing reasonable allocation of bandwidth resources to meet the service transmission delay requirement, a linear programming problem is constructed, and the maximum bandwidth resource allocation benefit is determined according to the following formula:

[0123]

[0124] Among them, i represents the set of services to be transmitted by node i, γ i,k is the bandwidth B of node i for service k i Allocation ratio.

[0125] The traffic pressure load balancing routing method based on incomplete information described in the present application comprehensively considers the limitation that nodes can usually only collect status information of local networks within a limited range, and dynamically allocates bandwidth based on the KKT (Karush-Kuhn-Tucker) condition. Once the number of node services changes, bandwidth resources are reallocated. Compared with the fixed average allocation method, nodes can flexibly allocate bandwidth resources according to the requirements of different services, meet the latency requirements of differentiated services, avoid inefficient use of bandwidth, and intelligently achieve network workload balance.

[0126] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

[0127] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referenced to each other. The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the functions in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing terminal device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable terminal device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1The steps of the functions specified in one or more boxes. Although the preferred embodiments of the embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they know the basic creative concept. Therefore, the attached claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention. Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or terminal device including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0128] The method and device provided by the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principle and implementation mode of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation mode and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

[0129] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", "one specific embodiment" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0130] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A traffic pressure load balancing routing method based on incomplete information, characterized in that: include: Step S1: Before each round of service transmission from the starting node to the aggregation node, a reasonable next hop is selected for each routing node based on delay redundancy to build a static network topology; Step S2: establishing a bandwidth resource allocation benefit function for each routing node according to the static network topology; Step S3: Establishing a linear programming problem for maximizing node benefits according to the bandwidth resource allocation benefit function; Step S4: Solving the linear programming problem based on the KKT condition to obtain an optimal solution for bandwidth resource allocation; Step S5: monitor the change of the number of real-time transmission services of each routing node. When the number of real-time transmission services of any node changes, repeat steps S3 and S4 to update the bandwidth allocation plan; In step S1, the static network topology is determined according to the following formula: in, For Node Delay redundancy, Is a node The state collection range includes the state information of the nodes in the forward range, including the delay redundancy point of the last service to be sent by the node to the aggregation node. The delay redundancy calculation method is as follows: in, The last service relayed by the node to the sink node. For Node The transmission delay requirement of the last service sent to the aggregation node in It is the time taken for the service to be transmitted to the aggregation node. The calculation formula is: in, Representation Node The first Business, For Node bandwidth, Representation Node The set of services to be transmitted, For Business The amount of data; In step S2, according to the static network topology, for each node, the bandwidth allocation ratio is dynamically adjusted to respond to the delay change and maximize the node's benefit. To ensure that the service with lower delay redundancy obtains a higher bandwidth allocation ratio, a node bandwidth resource allocation benefit function is established: in, Is a node The bandwidth resource allocation benefit function is Representation Node The set of services to be transmitted, Is a node Business-oriented Bandwidth Distribution ratio, Indicates that the business The delay redundancy is specifically the delay redundancy of the last unit data; its calculation method is: in, For Node Medium Business The transmission delay requirement is The last unit data of the service data packet is generated and sent to the node Time taken.

2. The traffic pressure load balancing routing method based on incomplete information according to claim 1 is characterized in that: node The state collection scope build method looks like this: in, Representation Node and The distance between A set of numbers representing nodes, where and Respectively represent nodes and nodes Upload distance, Specifies the maximum number of upload hops.

3. The traffic pressure load balancing routing method based on incomplete information according to claim 1 is characterized in that: In step S3, by utilizing reasonable allocation of bandwidth resources to meet the service transmission delay requirements, a linear programming problem is constructed, and the maximum bandwidth resource allocation benefit is determined according to the following formula: in, Representation Node The set of services to be transmitted, Is a node Business-oriented Bandwidth Allocation ratio.

4. A traffic pressure load balancing routing system based on incomplete information, characterized in that: include: Network topology building module: used to select a reasonable next hop for each routing node based on delay redundancy before each round of business is transmitted from the starting node to the aggregation node, and to build a static network topology; A revenue function establishment module: used to establish a bandwidth resource allocation revenue function for each routing node according to the network topology; Linear programming calculation module: used to reasonably allocate bandwidth resources according to the network topology and node bandwidth resource allocation benefit function, with the goal of meeting the service transmission delay requirement, and establish a linear programming problem for maximizing node benefits according to the bandwidth resource allocation benefit function; Resource allocation module: used to solve the linear programming based on KKT conditions to obtain the optimal solution for bandwidth resource allocation, and monitor the changes in the number of real-time transmission services of each routing node. When the number of real-time transmission services of any node changes, the bandwidth allocation plan is updated; In the network topology building module, the static network topology is determined according to the following formula: in, For Node Delay redundancy, Is a node The state collection range includes the state information of the nodes in the forward range, including the delay redundancy point of the last service to be sent by the node to the aggregation node. The delay redundancy calculation method is as follows: in, The last service relayed by the node to the sink node. For Node The transmission delay requirement of the last service sent to the aggregation node in It is the time taken for the service to be transmitted to the aggregation node. The calculation formula is: in, Representation Node The first Business, For Node bandwidth, Representation Node The set of services to be transmitted, For Business The amount of data; In the revenue function establishment module, according to the static network topology, for each node, the bandwidth allocation ratio is dynamically adjusted to respond to the delay change and maximize the node's revenue. To ensure that the service with lower delay redundancy obtains a higher bandwidth allocation ratio, the node's bandwidth resource allocation revenue function is established: in, Is a node The bandwidth resource allocation benefit function is Representation Node The set of services to be transmitted, Is a node Business-oriented Bandwidth Distribution ratio, Indicates that the business The delay redundancy is specifically the delay redundancy of the last unit data; its calculation method is: in, For Node Medium Business The transmission delay requirement is The last unit data of the service data packet is generated and sent to the node Time taken.

5. The flow pressure load balancing routing system based on incomplete information according to claim 4 is characterized in that: node The state collection scope build method looks like this: in, Representation Node and The distance between A set of numbers representing nodes, where and Respectively represent nodes and nodes Upload distance, Specifies the maximum number of upload hops.

6. The flow pressure load balancing routing system based on incomplete information according to claim 4 is characterized in that: In the linear programming calculation module, by utilizing reasonable allocation of bandwidth resources to meet the service transmission delay requirements, a linear programming problem is constructed, and the maximum bandwidth resource allocation benefit is determined according to the following formula: in, Representation Node The set of services to be transmitted, Is a node Business-oriented Bandwidth Allocation ratio.

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