Data transmission method and device for ocean sensing data and electronic equipment

Abstract

The invention provides a data transmission method and device for ocean perception data and electronic equipment, and relates to the technical field of communication networks. In the application, through the at least one sensing node, the intermediate node and the computing node included in the node set corresponding to the target sea area, a multi-source target ocean sensing network can be constructed, higher requirements of ocean meteorological prediction on data transmission and processing are met, and a future intelligent ocean meteorological prediction scene is enabled. Moreover, at least one data transmission link meeting the preset data transmission link condition is selected from the target ocean sensing network, so that the optimization of link resources in the target ocean sensing network is realized, the link configuration in the target ocean sensing network is dynamically adjusted, the transmission delay of the ocean sensing data is reduced, and the transmission efficiency of the ocean sensing network is improved. Therefore, the overall transmission efficiency of the target ocean sensing network is improved. The rationality and timeliness of ocean sensing data transmission can be improved, and the performance and real-time forecasting capability of an ocean sensing network are further improved.

Description

Technical Field

[0001] The present application relates to the field of communication network technology, and in particular to a method, device and electronic equipment for transmitting ocean perception data. Background Art

[0002] With the growing demand for artificial intelligence (AI)-based marine meteorological forecasts (e.g., storms, ocean currents, and waves), efficient ocean sensing data transmission has become crucial for accurate marine meteorological forecasts.

[0003] In traditional ocean sensing networks, a single type of sensing device is often used for marine meteorological perception due to its high stability. However, as marine meteorological forecasting gradually develops towards digitalization, diversification and intelligence, the limitations of a single type of sensing device are becoming increasingly prominent, and the coordinated perception of multiple sensing devices has become an inevitable trend.

[0004] Therefore, an ocean sensing network including a variety of sensing devices has been built to realize the collection, transmission and processing of large-scale ocean sensing data and adapt to the complex and changing ocean environment. However, when transmitting ocean sensing data, the current ocean sensing network may have problems such as unreasonable data transmission links or high latency, and may not be able to report the collected ocean sensing data to the network side in a timely manner or even fail to do so, thus failing to predict ocean weather in real time.

[0005] In view of this, how to improve the rationality and timeliness of ocean perception data transmission in order to enhance the performance and real-time forecasting (or prediction) capabilities of the ocean perception network is an issue that needs to be addressed urgently. Summary of the invention

[0006] The embodiments of the present application provide a method, device and electronic device for transmitting ocean perception data, so as to improve the rationality and timeliness of ocean perception data transmission, thereby improving the performance and real-time forecasting capability of the ocean perception network.

[0007] In a first aspect, an embodiment of the present application provides a method for transmitting ocean perception data, the method comprising:

[0008] Obtaining node information of a node set corresponding to the target sea area; the node information represents data transmission performance corresponding to a plurality of nodes included in the node set, wherein the plurality of nodes include: at least one sensing node, an intermediate node and a computing node, each intermediate node being used to transmit ocean sensing data of the target sea area sensed by the corresponding sensing node to the corresponding computing node, so that the computing node predicts the ocean weather of the target sea area according to the ocean sensing data;

[0009] Based on the node information, a node subset that meets the preset data transmission performance conditions is selected from the node set, and a target ocean perception network of the target sea area is constructed based on the node subset;

[0010] Selecting at least one data transmission link that meets a preset data transmission link condition from the target ocean sensing network;

[0011] Based on at least one data transmission link, ocean sensing data sensed by at least one sensing node included in the transmission node subset.

[0012] In an optional embodiment, the node information includes any one or combination of node association numbers, node transmission delays, and stability metrics corresponding to the multiple nodes, and the data transmission performance condition includes any one or combination of the following:

[0013] The node association number of the node is less than the node association number threshold set for the node's environment;

[0014] The node transmission delay of the node is less than the node transmission delay threshold set for the environment in which the node is located;

[0015] The stability metric value of the node is less than the stability metric threshold set for the node's environment.

[0016] In an optional embodiment, constructing a target ocean sensing network of a target sea area based on a node subset includes:

[0017] Based on a set number of nodes in the node subset and a preset node connection relationship, an initial ocean perception network of the target sea area is constructed;

[0018] Based on the set ocean data perception range and at least one node in the node subset other than the set number of nodes, the initial ocean perception network is expanded to obtain a target ocean perception network.

[0019] In an optional embodiment, based on the set ocean data perception range and at least one node in the node subset other than the set number of nodes, the initial ocean perception network is expanded to obtain a target ocean perception network, including:

[0020] According to the set network expansion speed, the initial ocean perception network is expanded multiple times until the perception range of the expanded ocean perception network reaches the ocean data perception range;

[0021] The expanded ocean sensing network is used as the target ocean sensing network;

[0022] In an optional embodiment, the initial ocean sensing network is expanded multiple times according to a set network expansion speed, including:

[0023] During an expansion of the initial ocean sensing network, the following operations are performed:

[0024] Determine the expanded sensing range based on the network expansion speed and the sensing range of the current ocean sensing network;

[0025] Based on the node association numbers corresponding to at least one newly added node within the expanded perception range, the current ocean perception network is expanded.

[0026] In an optional embodiment, selecting at least one data transmission link that meets a preset data transmission link condition from the target ocean sensing network includes:

[0027] For at least one sensing node in the target ocean sensing network, perform the following operations:

[0028] Selecting at least one data transmission link from the target ocean sensing network with a sensing node as a source node and any computing node in the target ocean sensing network as a destination node;

[0029] A first data transmission link in at least one data transmission link whose link transmission delay is less than a link transmission delay threshold set for a sensing node is used as a data transmission link that satisfies the data transmission link condition and corresponds to a sensing node.

[0030] In an optional embodiment, after selecting at least one data transmission link with a sensing node as a source node and any computing node in the target ocean sensing network as a destination node from the target ocean sensing network, the method further includes:

[0031] If the first data transmission link does not exist in the at least one data transmission link, determining a link transmission performance metric value corresponding to each of the at least one data transmission links based on the total remaining bandwidth and the link transmission delay corresponding to each of the at least one data transmission link;

[0032] The second data transmission link with the largest link transmission performance metric value among the at least one data transmission link is used as a data transmission link that meets the data transmission link condition and corresponds to a sensing node.

[0033] In an optional embodiment, determining a link transmission performance metric value corresponding to at least one data transmission link based on the total remaining bandwidth and link transmission delay corresponding to at least one data transmission link respectively includes:

[0034] For at least one data transmission link, perform the following operations:

[0035] Obtain a first metric value based on a first ratio obtained by the total amount of remaining bandwidth and the total bandwidth of a data transmission link, and a first weight factor set for the first ratio;

[0036] Obtaining a second metric value based on a second ratio obtained between the link transmission delay and a link transmission delay threshold corresponding to a data transmission link, and a second weight factor set for the second ratio;

[0037] A link transmission performance metric is determined based on the first metric and the second metric.

[0038] In a second aspect, an embodiment of the present application further provides a data transmission device for ocean sensing data, the device comprising:

[0039] An information acquisition module is used to acquire node information of a node set corresponding to a target sea area; the node information represents the data transmission performance corresponding to a plurality of nodes included in the node set, and the plurality of nodes include: at least one sensing node, an intermediate node and a computing node, and each intermediate node is used to transmit the ocean sensing data of the target sea area sensed by the corresponding sensing node to the corresponding computing node, so that the computing node predicts the ocean weather of the target sea area according to the ocean sensing data;

[0040] A network construction module is used to select a node subset that meets a preset data transmission performance condition from a node set based on the node information, and to construct a target ocean perception network in the target sea area based on the node subset;

[0041] A link selection module, used to select at least one data transmission link that meets a preset data transmission link condition from the target ocean sensing network;

[0042] The data transmission module is used to transmit ocean sensing data sensed by at least one sensing node included in the node subset based on at least one data transmission link.

[0043] In an optional embodiment, when constructing a target ocean perception network of a target sea area based on a node subset, the network construction module is specifically used to:

[0044] Based on a set number of nodes in the node subset and a preset node connection relationship, an initial ocean perception network of the target sea area is constructed;

[0045] Based on the set ocean data perception range and at least one node in the node subset other than the set number of nodes, the initial ocean perception network is expanded to obtain a target ocean perception network.

[0046] In an optional embodiment, when the initial ocean sensing network is expanded based on the set ocean data sensing range and at least one node in the node subset other than the set number of nodes to obtain the target ocean sensing network, the network construction module is specifically used to:

[0047] According to the set network expansion speed, the initial ocean perception network is expanded multiple times until the perception range of the expanded ocean perception network reaches the ocean data perception range;

[0048] The expanded ocean sensing network is used as the target ocean sensing network;

[0049] In an optional embodiment, when the initial ocean sensing network is expanded multiple times according to a set network expansion speed, the network construction module is specifically used to:

[0050] During an expansion of the initial ocean sensing network, the following operations are performed:

[0051] Determine the expanded sensing range based on the network expansion speed and the sensing range of the current ocean sensing network;

[0052] Based on the node association numbers corresponding to at least one newly added node within the expanded perception range, the current ocean perception network is expanded.

[0053] In an optional embodiment, when selecting at least one data transmission link that meets a preset data transmission link condition from the target ocean sensing network, the link selection module is specifically used to:

[0054] For at least one sensing node in the target ocean sensing network, perform the following operations:

[0055] Selecting at least one data transmission link from the target ocean sensing network with a sensing node as a source node and any computing node in the target ocean sensing network as a destination node;

[0056] A first data transmission link in at least one data transmission link whose link transmission delay is less than a link transmission delay threshold set for a sensing node is used as a data transmission link that satisfies the data transmission link condition and corresponds to a sensing node.

[0057] In an optional embodiment, after selecting at least one data transmission link with a sensing node as a source node and any computing node in the target ocean sensing network as a destination node from the target ocean sensing network, the link selection module is further used to:

[0058] If the first data transmission link does not exist in the at least one data transmission link, determining a link transmission performance metric value corresponding to each of the at least one data transmission links based on the total remaining bandwidth and the link transmission delay corresponding to each of the at least one data transmission link;

[0059] The second data transmission link with the largest link transmission performance metric value among the at least one data transmission link is used as a data transmission link that meets the data transmission link condition and corresponds to a sensing node.

[0060] In an optional embodiment, when determining the link transmission performance metric value corresponding to at least one data transmission link based on the total remaining bandwidth and link transmission delay corresponding to at least one data transmission link, the link selection module is specifically used to:

[0061] For at least one data transmission link, perform the following operations:

[0062] Obtain a first metric value based on a first ratio obtained by the total amount of remaining bandwidth and the total bandwidth of a data transmission link, and a first weight factor set for the first ratio;

[0063] Obtaining a second metric value based on a second ratio obtained between the link transmission delay and a link transmission delay threshold corresponding to a data transmission link, and a second weight factor set for the second ratio;

[0064] A link transmission performance metric is determined based on the first metric and the second metric.

[0065] In a third aspect, an embodiment of the present application further provides an electronic device, including:

[0066] Processor; and

[0067] Memory for storing programs,

[0068] The program includes instructions, which, when executed by a processor, cause the processor to execute the method for transmitting ocean perception data as described in the first aspect.

[0069] In a fourth aspect, an embodiment of the present application further provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the data transmission method for ocean perception data as described in the first aspect.

[0070] In a fifth aspect, the present application provides a computer program product, which, when called by a computer, enables the computer to execute the steps of the method for transmitting ocean perception data as described in the first aspect.

[0071] The beneficial effects of this application are as follows:

[0072] In the data transmission method of ocean perception data provided in the embodiment of the present application, a multi-source target ocean perception network can be constructed by at least one perception node, intermediate node and computing node included in the node set corresponding to the target sea area, which meets the high requirements of marine meteorological forecasting for data transmission and processing, and empowers future intelligent marine meteorological forecasting scenarios. In addition, by selecting at least one data transmission link that meets the preset data transmission link conditions from the target ocean perception network, the link resources in the target ocean perception network are optimized, that is, the link configuration in the target ocean perception network can be dynamically adjusted according to the data transmission requirements and link status to reduce the transmission delay of the ocean perception data, thereby improving the overall transmission efficiency of the target ocean perception network. That is, the rationality and timeliness of ocean perception data transmission can be improved, thereby improving the performance and real-time forecasting capabilities of the ocean perception network.

[0073] In addition, other features and advantages of the present application will be described in the subsequent description, and partly become apparent from the description, or be understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described here are used to provide a further understanding of the present application, constitute a part of the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0075] Figure 1 A schematic diagram of a network architecture of an ocean sensing network applicable to an embodiment of the present application;

[0076] Figure 2 A schematic diagram of an implementation flow of a method for transmitting ocean sensing data provided in an embodiment of the present application;

[0077] Figure 3 A schematic diagram of the composition structure of an initial ocean sensing network provided in an embodiment of the present application;

[0078] Figure 4 A schematic diagram of a specific application scenario for screening data transmission links provided in an embodiment of the present application;

[0079] Figure 5 A schematic diagram of the structure of a data transmission device for ocean sensing data provided in an embodiment of the present application;

[0080] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0081] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be construed as being limited to the embodiments described herein. Instead, these embodiments are provided to provide a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are only for exemplary purposes and are not intended to limit the scope of protection of the present application.

[0082] It should be understood that the various steps described in the method implementation of the present application can be performed in different orders and / or performed in parallel. In addition, the method implementation may include additional steps and / or omit the steps shown. The scope of the present application is not limited in this respect.

[0083] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this application are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0084] It should be noted that the modifications of "one" and "plurality" mentioned in the present application are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0085] The names of the messages or information exchanged between multiple devices in the embodiments of the present application are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0086] First, the design concept of the embodiment of the present application is briefly introduced below:

[0087] With the growing demand for AI-based marine weather (e.g., storms, ocean currents, and waves) forecasts, efficient ocean sensing data transmission has become critical for accurate marine weather forecasts. Therefore, efforts have been made to improve existing marine environment models or marine sensing networks to more accurately predict marine weather. As marine weather forecast systems rapidly develop towards precision and heterogeneity, more and more marine sensing networks have emerged, collecting marine data in real time through various large-scale sensing devices (e.g., sensors), such as seawater temperature, wave height, wind speed, and ocean current direction.

[0088] In order to make full use of the performance of emerging technologies and realize intelligent and accurate forecasting of marine meteorology, higher requirements are put forward for the ocean perception network, such as high-precision perception, collaborative transmission, distributed computing and rapid forecasting. It can be seen that the future ocean perception network is a new collaborative system based on information-physical fusion, which requires the ocean perception network to not only have multi-dimensional and distributed perception detection, but also real-time and stable communication transmission, and more importantly, powerful and intensive computing services.

[0089] In traditional ocean sensing networks, a single type of sensing device is often used for marine meteorological perception due to its high stability. However, as marine meteorological forecasting gradually develops towards digitalization, diversification and intelligence, the limitations of a single type of sensing device are becoming increasingly prominent, and coordinated perception of multiple sensing devices has become an inevitable trend. The ocean sensing network covers a vast area including air, land, water and underwater. The special geographical and climatic conditions make the construction and maintenance of network facilities extremely complex and costly. Although a variety of network systems have been deployed in the ocean space, the coordinated perception of multiple heterogeneous devices is poor due to the diverse deployment forms, inconsistent communication formats and standards.

[0090] Therefore, it is urgent to build a unified ocean perception network architecture to achieve efficient collection, transmission and processing of large-scale ocean (environmental) data and adapt to complex and changing environmental requirements. In the architecture of the ocean perception network, efficient allocation of link resources is one of the key elements to ensure the quality of ocean perception data transmission. Unreasonable link resource allocation may cause data congestion during ocean perception data transmission, significantly increase transmission delay, and affect the real-time performance of marine meteorological forecasts. In addition, unoptimized link resources will reduce the anti-destruction capability of the ocean perception network, causing the ocean perception network to perform poorly in the face of burst traffic or failures, and reduce robustness and reliability.

[0091] From the perspective of the system level, the optimization of link resources is closely related to scheduling resources, and the rationality of scheduling resources directly depends on the allocation of link resources. If scheduling resources are not optimized on the basis of link resource optimization, it may lead to suboptimal or failed link resource selection, causing overload or imbalance of data transmission links, further aggravating the congestion problem of the ocean perception network, and thus significantly increasing the transmission delay. This will not only affect the overall stability of the network, but may even cause local network collapse or communication interruption. Therefore, the optimization of link resources and scheduling resources is crucial. The two must complement each other in the architectural design of the ocean perception network and work together for the efficient operation of the ocean perception network. The ocean perception network that has not been collaboratively optimized not only faces the risk of unbalanced resource allocation and unreasonable transmission paths, but may also lead to low utilization of the ocean perception network and inability to adapt to complex dynamic changes.

[0092] In view of this, in order to solve or improve the above problems, by optimizing the links and scheduling resources, it is possible to ensure the rationality and timeliness of the data transmission path, maintain the continuity and stability of the network operation, and further improve the performance and real-time forecasting capabilities of the wave sensing network. Therefore, the embodiment of the present application proposes a data transmission of ocean sensing data, which may specifically include: obtaining the node information of the node set corresponding to the target sea area; the node information characterizes the data transmission performance corresponding to the multiple nodes included in the node set, and the multiple nodes include: at least one sensing node, an intermediate node and a computing node, each intermediate node is used to transmit the ocean sensing data of the target sea area perceived by the corresponding sensing node to the corresponding computing node, so that the computing node predicts the marine meteorology of the target sea area based on the ocean sensing data; then, based on the obtained node information, a node subset that meets the preset data transmission performance conditions is selected from the node set, and a target ocean sensing network of the target sea area is constructed based on the node subset; further, from the target ocean sensing network, at least one data transmission link that meets the preset data transmission link conditions is selected; finally, based on at least one data transmission link, the ocean sensing data perceived by at least one sensing node included in the transmission node subset is transmitted.

[0093] In this way, a multi-source target ocean perception network can be constructed through at least one perception node, intermediate node and computing node included in the node set, which meets the high requirements of marine meteorological forecasting for data transmission and processing, and empowers future intelligent marine meteorological forecasting scenarios. In addition, by selecting at least one data transmission link that meets the preset data transmission link conditions from the target ocean perception network, the link resources in the target ocean perception network are optimized, that is, the link configuration in the target ocean perception network can be dynamically adjusted according to the data transmission requirements and link status to reduce the transmission delay of ocean perception data, thereby improving the overall transmission efficiency of the target ocean perception network. For example, the responsiveness and data processing capabilities of the target ocean perception network are improved.

[0094] In particular, the preferred embodiments of the present application are described below in conjunction with the drawings in the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application, and the embodiments of the present application and the features in the embodiments may be combined with each other if there is no conflict.

[0095] See also Figure 1 As shown, it is a schematic diagram of the network architecture of an ocean perception network applicable to an embodiment of the present application, and the ocean perception network is composed of a perception layer 101, an edge layer 102, and a computing layer 103. Among them, the nodes between the three layers of the perception layer 101, the edge layer 102, and the computing layer 103 can exchange information through a communication network, and the communication mode adopted by the aforementioned communication network may include: a wireless communication mode and a wired communication mode.

[0096] Exemplarily, the nodes in the edge layer 102 (e.g., intermediate nodes, or edge nodes) can access the network through cellular mobile communication technology, and communicate with the nodes in the perception layer 101 (e.g., perception nodes) and the nodes in the computing layer 103 (e.g., computing nodes), respectively. The cellular mobile communication technology, for example, includes the fifth generation mobile communication (5th generation mobile networks, 5G) technology or the next generation mobile communication technology.

[0097] Optionally, the nodes in the edge layer 102 may also access the network through short-range wireless communication, and communicate with the nodes in the perception layer 101 and the nodes in the computing layer 103. The short-range wireless communication method, for example, includes wireless fidelity (Wi-Fi) technology.

[0098] The embodiment of the present application does not impose any restrictions on the number of nodes involved in each network layer in the above network architecture. For example, the above perception layer 101 may include more perception nodes, or may include fewer perception nodes, or may also include other network devices. Optionally, the embodiment of the present application does not limit the number of network layers in the above network architecture. For example, more network layers may be included. Figure 1 As shown, only the perception layer 101, the edge layer 102 and the computing layer 103 are described as examples, and the above network layers and their respective functions are briefly introduced below.

[0099] The perception layer 101 is located at the bottom layer of the network architecture and is composed of various sensing devices such as satellites, drones, buoys and submersibles distributed in space, sky, land and ocean. It is responsible for the perception of wave data and communication with upper-level nodes.

[0100] The various sensing devices mentioned above can all be referred to as sensing nodes, that is, different sensing nodes correspond to different types of sensing devices. Of course, the various sensing devices mentioned above can also have other names, which are not limited in the embodiments of the present application.

[0101] The edge layer 102 is located in the middle layer of the architecture and acts as a data transfer station and processing node, such as an intermediate router or switch. This layer consists of edge servers and sensor devices with computing capabilities, responsible for real-time data collection, and performing preliminary data processing and filtering.

[0102] Since the edge computing nodes in the edge layer 102 are closer to the data source (ie, the perception nodes in the perception layer 101), they can process tasks faster, thereby sharing the computing pressure of the computing layer 103 (or the cloud computing center layer).

[0103] The computing layer 103 is located at the top of the network architecture and can be composed of supercomputers or server clusters. These devices have powerful computing and storage capabilities. The tasks of this layer include data processing, AI model training, and prediction result analysis. This layer realizes the centralized management, backup, storage, and analysis of ocean perception data, ensuring the integrity and availability of the data.

[0104] Optionally, the sensing nodes in the sensing layer 101 may be connected to the computing nodes in the computing layer 103 through the intermediate nodes in the edge layer 102, or some sensing nodes may be directly connected to the computing nodes in the computing layer 103 to improve the stability and robustness of the ocean sensing network. In addition, the sensing nodes in the sensing layer 101 may be connected only to the intermediate nodes in the edge layer 102 to improve the response speed of the ocean sensing network and reduce the computing load of the computing layer 103.

[0105] In order to achieve accurate and timely marine weather forecasts (such as wave conditions), a large amount of multi-source data is required as input, and in order to ensure that the sensing devices that obtain these input data can work together. Therefore, based on the structural design of the above-mentioned marine sensing network, the marine sensing data sensed by each sensing node in the sensing layer 101 can be acquired and processed in real time and comprehensively, so as to more accurately predict the marine weather.

[0106] The structural design of the above-mentioned ocean perception network not only optimizes the data flow and processing flow, but also realizes efficient and real-time processing of data. Among them, the wide distribution of perception nodes in the perception layer 101 improves the quality of ocean perception data and the system adaptability of the ocean perception network; the edge layer 102 reduces the data transmission delay and the computing load of the computing layer 103 by fast processing near the data source, thereby improving the response speed of the ocean perception network; the high-performance computing resources in the computing layer 103 ensure the accuracy of marine meteorological forecasts and decision-making support capabilities. It can be seen that the ocean perception network provided by the embodiment of the present application realizes the real-time collection and processing of ocean data, improves the management efficiency of ocean perception data, and thereby improves the performance of the ocean perception network and the real-time forecasting capability of marine meteorology.

[0107] It is worth mentioning that the ocean perception network provided in the embodiment of the present application can be constructed based on the node information of the node set corresponding to the target sea area. Exemplarily, it can specifically include: obtaining the node information of the node set corresponding to the target sea area; the node information characterizes the data transmission performance corresponding to the multiple nodes included in the node set, and the multiple nodes include: at least one perception node, an intermediate node and a computing node, so as to filter out a node subset that meets the preset data transmission performance conditions from the node set based on the node information, and construct a target ocean perception network of the target sea area based on the node subset.

[0108] The following describes the data transmission method of ocean perception data provided by the exemplary embodiment of the present application in combination with the above-mentioned network architecture and with reference to the accompanying drawings. It should be noted that the above-mentioned system architecture is only shown to facilitate the understanding of the spirit and principles of the present application, and the implementation of the present application is not limited in this regard.

[0109] See also Figure 2 As shown, it is a schematic diagram of the implementation process of a method for transmitting ocean perception data provided by an embodiment of the present application. The execution subject takes a server for building an ocean perception network as an example. The specific implementation process of the method is as follows:

[0110] S201: Obtain node information of a node set corresponding to a target sea area.

[0111] The above-mentioned node information represents the data transmission performances corresponding to the multiple nodes included in the node set, and the aforementioned multiple nodes may include: at least one sensing node, at least one intermediate node and at least one computing node.

[0112] Among them, each sensing node can be used to sense the target sea area to obtain corresponding ocean sensing data, each intermediate node can be used to transmit the ocean sensing data sensed by the corresponding sensing node to the corresponding computing node, and each computing node can be used to predict the ocean weather of the target sea area based on the ocean sensing data of the target sea area. Optionally, the above intermediate nodes can also predict the ocean weather of the target sea area based on the ocean sensing data uploaded by the sensing nodes.

[0113] The above-mentioned ocean sensing data may include, but are not limited to: ocean data such as sea temperature (ie, sea water temperature), sea surface height, sea surface wind speed, and sea water flow direction. The above-mentioned ocean weather may include the state of waves, whether a storm is generated, and the like.

[0114] Exemplarily, when executing step S201, the server may obtain a node set for performing marine meteorological forecasting on the target sea area. The aforementioned node set may include: a number of sensing nodes (i.e., sensing devices for marine data) located in the ocean (e.g., the seabed, in the sea, on the sea surface), land, sky, and space, for example, there are 100 sensors in the ocean space, and the spacing between each sensor in the ocean space is 200 meters; an intermediate node cluster including 100 intermediate nodes is deployed on the ground; and a computing node cluster including 50 computing nodes is deployed on the ground.

[0115] In an optional implementation, the node information may include any one or combination of the node association number, node transmission delay and stability measurement value corresponding to the multiple nodes in the node set. The node association number refers to the number of edges associated with the node. For an undirected graph, the degree of a node is the number of edges connected to it; for a directed graph, the in-degree of a node refers to the number of edges pointing to the node from other nodes, and the out-degree refers to the number of edges starting from the node. Therefore, the node association number is the sum of the in-degree and the out-degree. Node transmission delay refers to the data transmission delay between two nodes, that is, the end-to-end delay. The stability measurement value is also the stability factor, which is used to measure the data transmission quality of the node in the environment in which it is located. If the stability measurement value is smaller, it indicates that the corresponding node is more unstable and the data transmission quality is worse; conversely, if the stability measurement value is larger, it indicates that the corresponding node is more stable and the data transmission quality is better.

[0116] In the embodiment of the present application, the undirected graph corresponding to the above node set is used as an example for description. For example, the above undirected graph can be represented as G(V, E), where V represents the node set and E represents the edge set. Assuming that there are N nodes in the above node set V, then the node set V = {v n |n=1,...,N}. Optional, node v n The node association number can be expressed as a(v n ), node v n The node transmission delay can be expressed as μ(v n ), node v n The stability measure of can be expressed as η(v n ).

[0117] The ocean sensing data to be transmitted (i.e., data stream) f n For example, s n represents f n The source node (i.e., the sensing node), d n represents f n The destination node (i.e., the intermediate node or computing node with computing capabilities), size n represents f n Size, upd n represents f n The upper bound of the link transmission delay (i.e. the corresponding set link transmission delay threshold).

[0118] S202: Based on the node information, a node subset that meets the preset data transmission performance conditions is screened out from the node set, and a target ocean perception network of the target sea area is constructed based on the node subset.

[0119] Since the node information includes any one or combination of the node association number, node transmission delay and stability measurement value corresponding to multiple nodes in the above node set, then the above preset data transmission performance conditions may include any one or combination of the following: the node association number of the node is less than the node association number threshold value set for the node's environment; the node transmission delay of the node is less than the node transmission delay threshold value set for the node's environment; the node stability measurement value is less than the stability measurement threshold value set for the node's environment.

[0120] Exemplarily, the node subset obtained from the above node set V can be expressed as V i , and the node set V except the node subset V i The node subset outside can be represented as V0. Correspondingly, in the edge set E corresponding to the node set V, the node subset V i The corresponding edge set can be expressed as E i , the edge set corresponding to the node subset V0 can be expressed as E0.

[0121] The node subset V above i It can also be understood as a node subset obtained by optimizing the node association number, node transmission delay and stability metric value. i The target ocean perception network of the target sea area is constructed, that is, the ocean perception network after link resource optimization. According to the characteristics of the ocean perception network, different parameter thresholds (such as node association number threshold, node transmission delay threshold and stability measurement threshold) of nodes (such as perception nodes) in the space, sky, ground and sea (i.e., space, sky, ground and sea) are used. i Node v in i The node association number is defined as a(v i ) as an example, if node v i The node association number threshold of the node in space is expressed as γ. Then, the node association number threshold of the node in space can be expressed as γ f , the node association number threshold of the node in the sky can be expressed as γ s , the node association number threshold of the node on the ground can be expressed as γ g , the node association number threshold of the node in the ocean can be expressed as Y b Then the node association number constraint that the node association number of the above node is less than the node association number threshold set for the node's environment can be expressed as:

[0122]

[0123] Based on the above representation of node association number constraints, the node association number constraints at different nodes in different environments of air, land, and sea can be expressed as:

[0124]

[0125]

[0126]

[0127]

[0128] Among them, a f (v i ) represents the node v in space i The number of node associations, a s (v i ) represents the node v in the sky i The number of node associations, a g (v i ) represents the node v on the ground i The number of node associations, a b (v i ) indicates that the ocean is at node vi The number of node associations.

[0129] Different nodes in different environments in the sky, land and sea also have different node transmission delay thresholds. i Node v in i The node transmission delay is μ(v i ) as an example, if node v i The node transmission delay threshold of the node in space is expressed as δ. Then, the node transmission delay threshold of the node in space can be expressed as δ f , the node transmission delay threshold of the node in the sky can be expressed as δ s , the node transmission delay threshold of the node on the ground can be expressed as δ g , the node transmission delay threshold of the node in the ocean can be expressed as δ b Then the node transmission delay of the above node is less than the node transmission delay threshold set for the node's environment. This node transmission delay constraint can be expressed as:

[0130]

[0131] Based on the above representation of node transmission delay constraints, the node transmission delay constraints at different nodes in different environments of air, land, and sea can be expressed as:

[0132]

[0133]

[0134]

[0135]

[0136] Among them, μ f (v i ) represents the node v in space i The node transmission delay, μ s (v i ) represents the node v in the sky i The node transmission delay, μ g (v i ) represents the node v on the ground i The node transmission delay, μ b (v i ) indicates that the ocean is at node v i The node transmission delay.

[0137] There are also differences in the stability metric thresholds for nodes in different environments in the sky, land and sea. For example, nodes in space (such as satellites) are located in the earth's orbit and are not affected by ground weather, but may be disturbed by the space environment (such as head-on storms) and have mobility factors. Nodes in the sky (such as drones) are limited by weather conditions and battery life, and stability problems may occur during flight. The flight environment changes greatly and is easily disturbed. Nodes on the ground (such as weather stations) are usually fixed in specific locations, are less affected by the environment, and have relatively stable connections and operations. Nodes on the sea surface (such as buoys) move with the waves on the sea surface. They are designed to work normally in bad weather, but may still be affected by natural factors such as wind and waves. Nodes under the sea surface (such as underwater submersibles) work in underwater environments and may encounter complex water currents and other obstacles, resulting in unstable connections.

[0138] Still with node subset V i Node v in i The stability measure is η(v i ) as an example, if node v i The stability measurement threshold is denoted as λ. Then, the node transmission delay threshold of the node in space can be expressed as λ f , the node transmission delay threshold of the node in the sky can be expressed as λ s , the node transmission delay threshold of the node on the ground can be expressed as λ g , the node transmission delay threshold of the node in the ocean can be expressed as λ b Then the stability metric value constraint that the stability metric value of the above node is less than the stability metric threshold set for the node's environment can be expressed as:

[0139]

[0140] Based on the above representation of stability metric constraints, the stability metric constraints at different nodes in different environments of air, land, and sea can be expressed as:

[0141]

[0142]

[0143]

[0144]

[0145] Among them, η f (v i ) represents the node v in space i The stability measure, η s (v i) represents the node v in the sky i The stability measure, η g (v i ) represents the node v on the ground i The stability measure, η b (v i ) indicates that the ocean is at node v i The stability measure of .

[0146] In this way, the server can filter out multiple nodes with higher data transmission quality from the above-mentioned node set, thereby avoiding the problem that some nodes in the node set may fail or have poor node performance due to the relatively harsh environment or failure of the nodes, thereby ensuring the reliability and security of the subsequently constructed ocean perception network.

[0147] In an optional implementation, after the server selects the node subset based on the above method, it can construct an initial ocean perception network of the target sea area based on a set number of nodes (e.g., m0 nodes) in the node subset and a preset node connection relationship; then, based on the set ocean data perception range and at least one node in the node subset other than the set number of nodes, the initial ocean perception network is expanded to obtain a target ocean perception network. The aforementioned preset node connection relationship may include the number of edges in the constructed initial ocean perception network (e.g., e0 edges).

[0148] For example, see Figure 3 As shown, the above initial ocean sensing network may include 6 nodes (i.e., node S, node 2, node 1, node D, node 4, and node 5), and 6 edges (i.e., node S→node 2, node 2→node 1, node 1→node D, node 1→node 5, node D→node 4, node 5→node 4).

[0149] Optionally, when the server expands the initial ocean perception network based on the above-set ocean data perception range and at least one node in the node subset other than the set number of nodes to obtain the target ocean perception network, the server can expand the initial ocean perception network multiple times according to the set network expansion speed until the perception range of the expanded ocean perception network is the ocean data perception range, thereby using the expanded ocean perception network as the target ocean perception network. In addition, during one expansion of the initial ocean perception network, the following operations can be performed: determine the expanded perception range based on the network expansion speed and the perception range of the current ocean perception network; expand the current ocean perception network based on the node association number corresponding to at least one newly added node in the expanded perception range. It can be seen that the link resource optimization of the wave perception network can change at any time as the network perception range changes.

[0150] Assume that in the above process of expanding or extending the initial ocean perception network, the initial ocean perception network is defined to have m0 nodes and e0 edges, and the initial radius of expansion (i.e., the coverage radius of the initial ocean perception network) is set to R l , the global radius (i.e. the coverage radius of the target ocean sensing network is R g ), the center of the initial ocean sensing network is selected as the center of the circle. The coverage radius of the initial ocean sensing network is from R l It starts to grow at a speed of c (i.e., the network expansion speed). When a new node is added to the already constructed ocean sensing network, it will be connected to m existing nodes (i.e., the m nodes in the already constructed ocean sensing network), where m≤m0, until it grows to the initial radius R. l =R g That is, the initial ocean sensing network is expanded to the target ocean sensing network.

[0151] Therefore, in the above node set V, according to the range covered by the circle radius, the above node subset V can be defined i is the node set within the expansion radius, and the node subset V0 is the node set outside the expansion radius, while the node subset V i The corresponding edge set E i That is, the edge set within the expansion radius. The edge set E0 corresponding to the above node subset V0 is the edge set outside the expansion radius. During the initial expansion or expansion of the ocean sensing network, the nodes in the node subset V0 will gradually join the node subset V i In the process, the nodes in node subset V0 are added to node subset V i Then, n node subsets V will be selected i At this time, when selecting n nodes to connect, it is necessary to connect them according to the link resource optimization design.

[0152] According to the link resource optimization rules, assuming that v i is the node subset V i The nodes that already exist in v j Prepare a new node subset V for node subset V0 i To add a link between two nodes, the added link must satisfy the constraints of node association number, node transmission delay and stability metric value before it can be added at node v i and node v j If the link is successfully added, the node v j Add node subset V i In the middle, and the edge [v i , v j ]Add edge set Ei In, that is, v j ∈V i , while [v i , v j ]∈E i If the constraints of node association number, node transmission delay and stability metric value (i.e., the threshold requirements of node association number, node transmission delay and stability metric value) are not met, the node v will not be i and node v j Add links between them.

[0153] In the wave sensing network, if the data transmission time is too long and cannot be analyzed in real time, it will be impossible to accurately grasp the true situation of the ocean meteorology. At the same time, the longer the transmission time, the greater the probability of being affected by noise and interference, and the accuracy of the predicted ocean meteorology will also be affected. In addition, the environment in which the sensing equipment in the air or under the sea is relatively harsh, and there may be unexpected situations such as external attacks or energy exhaustion, which will cause the node to fail. Therefore, it is very important to ensure the real-time and stability of the data. By optimizing the link resources of the multi-source ocean sensing network nodes in the above way, the link resources can be reasonably and efficiently allocated to adapt to the changing ocean environment, thereby reducing network latency. At the same time, a robust link structure can enhance the stability of the entire system. That is, not only the data transmission efficiency is significantly improved, but also the robustness of the network is enhanced.

[0154] S203: Select at least one data transmission link that meets a preset data transmission link condition from the target ocean sensing network.

[0155] In an optional implementation, when executing step S203, the server can perform the following operations respectively for at least one perception node in the target ocean perception network: select at least one data transmission link with a perception node as the source node and any computing node in the target ocean perception network as the destination node from the target ocean perception network; and use the first data transmission link in the at least one data transmission link whose link transmission delay is less than the link transmission delay threshold set for a perception node as a data transmission link corresponding to a perception node and meeting the data transmission link conditions.

[0156] In order to ensure that there are enough computing resources for marine meteorological forecasts in the future, the server can select computing nodes with more remaining computing resources as destination nodes according to certain rules. For example, multiple computing nodes in the computing layer can be sorted according to the remaining amount of computing resources, so as to select computing nodes according to the order of remaining computing resources.

[0157] Taking sensing node A as an example, if the link transmission delay D of the data transmission link corresponding to sensing node A is nLess than the link transmission delay threshold upd set for sensing node A n , that is, D n <upd n , the data transmission link can be used as the data transmission link corresponding to the sensing node A that meets the data transmission link conditions. If the link transmission delay D of the data transmission link corresponding to the sensing node A is n Greater than or equal to the above link transmission delay threshold upd n , that is, D n ≥ upd n , it is necessary to optimize the data transmission link corresponding to the sensing node A according to the target ocean sensing network (or schedule link resource optimization) to ensure that the data transmission delay requirements of the ocean sensing data are met, thereby improving the data transmission efficiency.

[0158] In a multi-source ocean perception network, it is crucial to implement a scheduling resource optimization strategy, which can ensure that data is efficiently transmitted through the best data transmission link, reduce transmission delays, avoid data congestion, and improve the load balance of the ocean perception network. In addition, a good scheduling resource optimization strategy can enhance the robustness of the ocean perception network, enabling it to adapt to the complex and changing ocean environment. Therefore, the scheduling optimization of the data transmission link not only improves the response speed and accuracy of data processing, but also enhances the adaptability and stability of the ocean perception network in the face of environmental challenges.

[0159] Among them, in a multi-source ocean perception network, perception nodes usually require low-latency and high-bandwidth transmission paths or data transmission links. In other words, in response to the multi-source ocean perception network's demand for low latency and high bandwidth, the scheduling resource optimization strategy comprehensively considers the two key factors of link transmission latency and bandwidth.

[0160] Therefore, in an optional implementation method, if the first data transmission link does not exist in the at least one data transmission link, the link transmission performance measurement values ​​corresponding to the at least one data transmission link can be determined based on the total remaining bandwidth and link transmission delay corresponding to the at least one data transmission link, so that the second data transmission link with the largest link transmission performance measurement value among the at least one data transmission link is used as the data transmission link that meets the data transmission link conditions corresponding to the one perception node.

[0161] Obviously, based on the above method, the scheduling resource optimization strategy proposed in this application can perform weighted optimization on the link transmission delay and bandwidth, and jointly determine the link transmission performance metric value of the data transmission link.

[0162] First, the remaining bandwidth of the data transmission link is one of the important resources that can be scheduled. Selecting a path with a larger remaining bandwidth can effectively avoid the congestion of ocean sensing data on a data transmission link, thereby achieving load balancing of the entire ocean sensing network. For example, assuming that the ocean sensing data f of a sensing node n From the source node v s To the destination node v d M data transmission links are searched. Represents ocean perception data f n The mth data transmission link in the ocean sensing network, where The aforementioned data transmission link can also be The data transmission direction is expressed as: s →v1→...→v i →v i+1 →...→v j →v n Therefore, the server can use Represents ocean perception data f n The link transmission delay of the mth data transmission link in the ocean sensing network and the Represents ocean perception data f n The total remaining bandwidth of the mth data transmission link in the ocean sensing network.

[0163] Optionally, the calculation formula for the total remaining bandwidth of the mth data transmission link may be specifically expressed as follows:

[0164]

[0165] in, represents the total bandwidth of the mth data transmission link above, Indicates the bandwidth used by the mth data transmission link. If there are multiple ocean sensing data occupying bandwidth on the mth data transmission link, and it is assumed that the bandwidths occupied by the multiple ocean sensing data are B1, B2, ..., B n , then the bandwidth used by the mth data transmission link is It is the sum of the bandwidths occupied by the aforementioned multiple ocean sensing data.

[0166] In other words, the bandwidth used by the mth data transmission link is It can be specifically expressed as follows:

[0167]

[0168] Therefore, the total remaining bandwidth of the mth data transmission link is The calculation formula can be further expressed as follows:

[0169]

[0170] Secondly, in the process of transmitting ocean sensing data, the link transmission delay of ocean sensing data from the sensing end (i.e., sensing node) to the computing end (i.e., computing node) can be mainly composed of four parts: sending delay, propagation delay, processing delay, and queuing delay. For example, the aforementioned processing delay d h It can represent the time required for nodes in the target ocean sensing network to process ocean sensing data (such as routing or link selection, data parsing, etc.), which is usually relatively short. Optionally, it can be defined that the node v in the target ocean sensing network i The processing delay is

[0171] The above queuing delay d q It can characterize the time that the ocean sensing data waits for transmission at the nodes in the target ocean sensing network. This part of the delay is usually uncertain and depends on the load and congestion status of the nodes in the target ocean sensing network. Optionally, the queuing delay of the nodes in the target ocean sensing network can be defined as

[0172] The above transmission delay d t It can characterize the time required for ocean sensing data to be sent to the data transmission link, which is mainly related to the size of the ocean sensing data and the bandwidth of the data transmission link. Optionally, the transmission delay of the node in the target ocean sensing network can be defined as The aforementioned transmission delay d t The calculation formula can be specifically expressed as follows:

[0173]

[0174] Among them, L represents the size of ocean sensing data, and B represents the bandwidth of the data transmission link.

[0175] The propagation delay d p It can characterize the time required for ocean sensing data to propagate on the data transmission link, which mainly depends on the link length of the data transmission link and the propagation speed of the ocean sensing data. Optionally, it can be defined in the data transmission link (v i , v j ) is the propagation delay The aforementioned propagation delay d p The calculation formula can be specifically expressed as follows:

[0176]

[0177] Where d represents the link length of the data transmission link, and v represents the propagation speed of the data transmission link. Since the multi-source sensing nodes are in different environments of air, land, and sea, the propagation delay d generated by different transmission media p There is a difference, so the propagation delay d p It can be expressed as follows:

[0178] d p ∈{d pf , d ps , d pg , d pb}

[0179] Among them, dp f represents the propagation delay of the data transmission link in space, dps represents the propagation delay of the data transmission link in the sky, d pg represents the propagation delay of the data transmission link on the ground, d pb Represents the propagation delay of the data transmission link in the ocean.

[0180] Since the above scheduling resource optimization needs to consider whether the target ocean sensing network is congested during the transmission process, a congestion flag ω can be designed. Specifically, if there is no congestion in the scheduled data transmission link, ω = 0, and the total delay (i.e., link transmission delay) is the transmission delay d t , propagation delay dp and processing delay d h If congestion occurs in the scheduled data transmission link, ω = 1, and the total delay is the transmission delay d t , propagation delay d p , processing delay and queuing delay d q Therefore, the total delay through n nodes (i.e. ) is calculated as follows:

[0181]

[0182] In an optional implementation, after the server obtains the total remaining bandwidth and link transmission delay corresponding to the at least one data transmission link, the server can perform weighted optimization on the total remaining bandwidth and link transmission delay to jointly determine how to schedule link resources. Therefore, for the at least one data transmission link, the following operations can be performed: a first metric value is obtained based on a first ratio obtained based on the total remaining bandwidth and the total bandwidth of a data transmission link, and a first weight factor set for the first ratio; then, a second metric value is obtained based on a second ratio obtained based on the link transmission delay and a link transmission delay threshold corresponding to a data transmission link, and a second weight factor set for the second ratio; finally, a link transmission performance metric value is determined based on the first metric value and the second metric value.

[0183] It should be noted that the first weight factor and the second weight factor may be the relative influence of the remaining total bandwidth and the link transmission delay on the link transmission performance determined according to a plurality of experimental data.

[0184] Exemplarily, assuming that the link transmission performance metric value of the scheduling optimization target (i.e., the above-mentioned data transmission link, such as the mth data transmission link) is ρ, the weighted optimization formula of the total remaining bandwidth and the link transmission delay is expressed as follows:

[0185]

[0186] Among them, α represents the first weight factor mentioned above, represents the first ratio mentioned above, Indicates the total remaining bandwidth of the above data transmission link, represents the total bandwidth of the above data transmission link, β represents the above second weight factor, represents the second ratio mentioned above, Indicates the link transmission delay of the above data transmission link, upd n Indicates the link transmission delay threshold set corresponding to the above data transmission link.

[0187] Since the first ratio can be used to measure the bandwidth utilization of the current data transmission link, and the second ratio can be used to measure the delay performance of the current data transmission link, the scheduling resource optimization strategy can make decisions based on the size of ρ corresponding to the optimization target. When ρ is larger, it means that the remaining bandwidth of the data transmission link is more abundant and the data transmission delay is smaller, so the data transmission link with a larger ρ is preferentially selected for resource scheduling.

[0188] In another optional implementation, the server can also determine the link transmission performance metric value corresponding to at least one data transmission link according to the total remaining bandwidth and the total link transmission delay corresponding to the at least one data transmission link, so as to use the data transmission link with the largest link transmission performance metric value among the at least one data transmission link as the data transmission link corresponding to the sensing node that meets the data transmission link conditions. In this way, it can be ensured to the greatest extent that the stability, reliability and data transmission efficiency of the selected data transmission link can meet the data transmission requirements.

[0189] For example, see Figure 4 As shown, assuming that the source node is node S and the destination node is node D, the server can Figure 4 In the target ocean sensing network shown in FIG. , data transmission links that meet the above data transmission link conditions are selected. Figure 4As shown, the aforementioned data transmission link is: node S→node 2→node 1→node D.

[0190] It should be noted that, given that the sensing nodes in the target ocean sensing network are usually in a harsh environment and are prone to abnormal situations such as communication interruption or device disconnection, the scheduling resource (or link) optimization strategy can introduce mechanisms such as disjoint paths and multi-path routing, that is, at least one of the above data transmission links does not have the same nodes except for the source node and the destination node, thereby improving the reliability and fault resistance of the target ocean sensing network. This design can achieve continuous transmission of ocean sensing data through the backup path when the main path fails, ensuring fault tolerance in complex environments.

[0191] In other words, the target ocean perception network is usually deployed in a complex and harsh marine environment, using a variety of sensor equipment such as satellites, buoys, and unmanned ships to monitor the ocean status in real time. Due to the uncertainty of the marine environment, sensor equipment may frequently lose connection or fail, so the reliability and transmission efficiency of the target ocean perception network are crucial. To meet these challenges, multi-path routing and non-intersecting path rules can also be used in scheduling resource optimization strategies. First, non-intersecting paths ensure that ocean perception data can be transmitted through backup data transmission links when data transmission links or nodes fail, thereby enhancing the fault tolerance of the target ocean perception network. Secondly, multi-path routing can disperse traffic, achieve load balancing and bandwidth optimization, and reduce the overall transmission delay by selecting data transmission links with low data transmission delay to meet real-time needs.

[0192] For example, in the design of multipath routing and disjoint paths, assuming that the topology of the target ocean sensing network is a graph G'(V', E'), given a source node s and a destination node t, find multiple data transmission links P1, P2, ..., P from the source node s to the destination node t. k , these paths are used for data transmission. Define each path P i P i ∈E', E' represents the path P i The selection of multipath routing can be represented as a path set {P1, P2, ..., P k}, where P i ∈p(s, t). That is, the set of all possible paths from the source node s to the destination node t: p(s, t) = {P|P i ∈E',s→t}.

[0193] The above disjoint paths or routes refer to multiple data transmission links from the source node to the destination node that do not share links or nodes. Assume that the paths P1, P2, ..., P k The link sets passed are E'(P1), E'(P2), ..., E'(Pk ), then the condition that links or paths do not intersect can be expressed as:

[0194]

[0195] In summary, the scheduling resource optimization strategy of the multi-source target ocean sensing network can improve network efficiency and reliability, ensure that ocean sensing data can be transmitted through the optimal path, and reduce latency and congestion. This optimization can meet the needs of real-time monitoring, enhance the fault tolerance of the network, and ensure the stability and accuracy of sensing data in complex ocean environments.

[0196] S204: Based on at least one data transmission link, transmit the ocean sensing data sensed by at least one sensing node included in the node subset.

[0197] The at least one sensing node included in the transmission node subset is also the sensing node corresponding to the at least one data transmission link. For example, assuming that five data transmission links that meet the preset data transmission link conditions are selected from the target ocean sensing network, the server can transmit the ocean sensing data sensed by the sensing nodes corresponding to the five data transmission links according to the five data transmission links.

[0198] In summary, in the data transmission method of ocean perception data provided in the embodiment of the present application, a multi-source target ocean perception network can be constructed through at least one perception node, intermediate node and computing node included in the node set corresponding to the target sea area, which meets the high requirements of marine meteorological forecasting for data transmission and processing, and empowers future intelligent marine meteorological forecasting scenarios. In addition, by selecting at least one data transmission link that meets the preset data transmission link conditions from the target ocean perception network, the link resources in the target ocean perception network are optimized, that is, the link configuration in the target ocean perception network can be dynamically adjusted according to the data transmission requirements and link status to reduce the transmission delay of the ocean perception data, thereby improving the overall transmission efficiency of the target ocean perception network. That is, the rationality and timeliness of ocean perception data transmission can be improved, thereby improving the performance and real-time forecasting capabilities of the ocean perception network.

[0199] Further, based on the same technical concept, the embodiment of the present application provides a data transmission device for ocean sensing data, and the data transmission device for ocean sensing data is used to implement the above method flow of the embodiment of the present application. Figure 5 As shown, the data transmission device 500 for ocean sensing data may include: an information acquisition module 501, a network construction module 502, a link selection module 503 and a data transmission module 504, wherein:

[0200] The information acquisition module 501 is used to acquire node information of a node set corresponding to the target sea area; the node information represents the data transmission performance corresponding to the multiple nodes included in the node set, and the multiple nodes include: at least one sensing node, an intermediate node and a computing node, and each intermediate node is used to transmit the ocean sensing data of the target sea area sensed by the corresponding sensing node to the corresponding computing node, so that the computing node predicts the marine weather of the target sea area according to the ocean sensing data;

[0201] The network construction module 502 is used to select a node subset that meets a preset data transmission performance condition from the node set based on the node information, and construct a target ocean perception network of the target sea area based on the node subset;

[0202] The link selection module 503 is used to select at least one data transmission link that meets the preset data transmission link conditions from the target ocean sensing network;

[0203] The data transmission module 504 is configured to transmit ocean sensing data sensed by at least one sensing node included in the node subset based on at least one data transmission link.

[0204] In an optional embodiment, when constructing the target ocean sensing network of the target sea area based on the node subset, the network construction module 502 is specifically used to:

[0205] Based on a set number of nodes in the node subset and a preset node connection relationship, an initial ocean perception network of the target sea area is constructed;

[0206] Based on the set ocean data perception range and at least one node in the node subset other than the set number of nodes, the initial ocean perception network is expanded to obtain a target ocean perception network.

[0207] In an optional embodiment, when the initial ocean sensing network is expanded based on the set ocean data sensing range and at least one node in the node subset other than the set number of nodes to obtain the target ocean sensing network, the network construction module 502 is specifically used to:

[0208] According to the set network expansion speed, the initial ocean perception network is expanded multiple times until the perception range of the expanded ocean perception network reaches the ocean data perception range;

[0209] The expanded ocean sensing network is used as the target ocean sensing network;

[0210] In an optional embodiment, when the initial ocean sensing network is expanded multiple times according to a set network expansion speed, the network construction module 502 is specifically used to:

[0211] During an expansion of the initial ocean sensing network, the following operations are performed:

[0212] Determine the expanded sensing range based on the network expansion speed and the sensing range of the current ocean sensing network;

[0213] Based on the node association numbers corresponding to at least one newly added node within the expanded perception range, the current ocean perception network is expanded.

[0214] In an optional embodiment, when selecting at least one data transmission link that meets a preset data transmission link condition from the target ocean sensing network, the link selection module 503 is specifically used to:

[0215] For at least one sensing node in the target ocean sensing network, perform the following operations:

[0216] Selecting at least one data transmission link from the target ocean sensing network with a sensing node as a source node and any computing node in the target ocean sensing network as a destination node;

[0217] A first data transmission link in at least one data transmission link whose link transmission delay is less than a link transmission delay threshold set for a sensing node is used as a data transmission link that satisfies the data transmission link condition and corresponds to a sensing node.

[0218] In an optional embodiment, after selecting at least one data transmission link with a sensing node as a source node and any computing node in the target ocean sensing network as a destination node from the target ocean sensing network, the link selection module 503 is further used to:

[0219] If the first data transmission link does not exist in the at least one data transmission link, determining a link transmission performance metric value corresponding to each of the at least one data transmission links based on the total remaining bandwidth and the link transmission delay corresponding to each of the at least one data transmission link;

[0220] The second data transmission link with the largest link transmission performance metric value among the at least one data transmission link is used as a data transmission link that meets the data transmission link condition and corresponds to a sensing node.

[0221] In an optional embodiment, when determining the link transmission performance metric value corresponding to at least one data transmission link based on the total remaining bandwidth and link transmission delay corresponding to at least one data transmission link, the link selection module 503 is specifically used to:

[0222] For at least one data transmission link, perform the following operations:

[0223] Obtain a first metric value based on a first ratio obtained by the total amount of remaining bandwidth and the total bandwidth of a data transmission link, and a first weight factor set for the first ratio;

[0224] Obtaining a second metric value based on a second ratio obtained between the link transmission delay and a link transmission delay threshold corresponding to a data transmission link, and a second weight factor set for the second ratio;

[0225] A link transmission performance metric is determined based on the first metric and the second metric.

[0226] Based on the description of the above method embodiment and device embodiment, the exemplary embodiment of the present invention further provides an electronic device, including: at least one processor; and a memory connected to the at least one processor in communication. The memory stores a computer program that can be executed by the at least one processor, and the computer program is used to enable the electronic device to perform the method according to the embodiment of the present invention when executed by the at least one processor.

[0227] An embodiment of the present application also provides a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to execute a method according to an embodiment of the present application.

[0228] An embodiment of the present application also provides a computer program product, including a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to execute a method according to an embodiment of the present application.

[0229] See also Figure 6 As shown, the structured block diagram of the electronic device 600 that can be used as the server or client of the present application will now be described, which is an example of the hardware device that can be applied to various aspects of the present application. The electronic device is intended to represent the computer device of various forms of digital electronics, such as, laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital processing, cellular phones, smart phones, wearable devices and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only used as examples, and are not intended to limit the implementation of the present application described herein and / or required.

[0230] like Figure 6As shown, the electronic device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 to a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 can also be stored. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0231] A plurality of components in the electronic device 600 are connected to the I / O interface 605, including: an input unit 606, an output unit 607, a storage unit 608, and a communication unit 609. The input unit 606 may be any type of device capable of inputting information to the electronic device 600, and the input unit 606 may receive input digital or character information, and generate key signal inputs related to user settings and / or function control of the electronic device. The output unit 607 may be any type of device capable of presenting information, and may include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 608 may include but is not limited to a disk, an optical disk. The communication unit 609 allows the electronic device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and may include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth device, a WiFi device, a worldwide interoperability for microwave access (WiMax) device, a cellular communication device, and / or the like.

[0232] The computing unit 601 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various AI computing chips, various computing units running machine learning model algorithms, digital signal processors (DSP), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 601 performs the various methods and processes described above. For example, in some embodiments, the data transmission method of the above-mentioned ocean perception data may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 600 via the ROM 602 and / or the communication unit 609.

[0233] In some embodiments, the computing unit 601 may be configured to execute the above-mentioned ocean sensing data transmission method by any other appropriate means (for example, by means of firmware).

[0234] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0235] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an erasable programmable read-only memory (EPROM) or a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0236] As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and / or device (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0237] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a cathode ray tub (CRT) or a liquid crystal display (LCD) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0238] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0239] A computer system may include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship to each other.

[0240] Furthermore, it should be understood that what is disclosed above is only a preferred embodiment of the present application, and certainly cannot be used to limit the scope of rights of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope covered by the present application.

Claims

1. A method for transmitting ocean sensing data, characterized in that: include: Obtain the node information of the node set corresponding to the target sea area; The node information represents the data transmission performances respectively corresponding to the multiple nodes included in the node set, the multiple nodes including: at least one sensing node, an intermediate node and a computing node, each intermediate node is used to transmit the ocean sensing data of the target sea area sensed by the corresponding sensing node to the corresponding computing node, so that the computing node predicts the marine weather of the target sea area according to the ocean sensing data; Based on the node information, a node subset that meets a preset data transmission performance condition is selected from the node set, and a target ocean sensing network of the target sea area is constructed based on the node subset; Selecting at least one data transmission link that meets a preset data transmission link condition from the target ocean sensing network; Based on the at least one data transmission link, the ocean sensing data sensed by at least one sensing node included in the node subset is transmitted.

2. The method according to claim 1, characterized in that The node information includes any one or a combination of node association numbers, node transmission delays, and stability metrics corresponding to the multiple nodes, respectively. The data transmission performance conditions include any one or a combination of the following: The node association number of the node is less than a node association number threshold set for the environment in which the node is located; The node transmission delay of the node is less than a node transmission delay threshold set for the environment in which the node is located; The stability metric value of the node is less than a stability metric threshold set for an environment where the node is located.

3. The method according to claim 1 or 2, characterized in that The constructing the target ocean sensing network of the target sea area based on the node subset includes: Based on a set number of nodes in the node subset and a preset node connection relationship, construct an initial ocean perception network of the target sea area; Based on the set ocean data perception range and at least one node in the node subset other than the set number of nodes, the initial ocean perception network is expanded to obtain the target ocean perception network.

4. The method according to claim 3, characterized in that The method of performing network expansion on the initial ocean sensing network based on the set ocean data sensing range and at least one node in the node subset other than the set number of nodes to obtain the target ocean sensing network includes: According to the set network expansion speed, the initial ocean sensing network is expanded multiple times until the sensing range of the expanded ocean sensing network is the ocean data sensing range; The expanded ocean sensing network is used as the target ocean sensing network.

5. The method according to claim 4, characterized in that The initial ocean sensing network is expanded multiple times according to the set network expansion speed, including: In a process of expanding the initial ocean sensing network, the following operations are performed: Determining the expanded sensing range based on the network expansion speed and the sensing range of the current ocean sensing network; The current ocean sensing network is expanded based on the node association numbers corresponding to at least one newly added node within the expanded sensing range.

6. The method according to claim 1 or 2, characterized in that: The step of selecting at least one data transmission link that meets a preset data transmission link condition from the target ocean sensing network includes: For at least one sensing node in the target ocean sensing network, perform the following operations respectively: Selecting, from the target ocean sensing network, at least one data transmission link with a sensing node as a source node and any computing node in the target ocean sensing network as a destination node; A first data transmission link in the at least one data transmission link whose link transmission delay is less than a link transmission delay threshold set for the one sensing node is used as a data transmission link corresponding to the one sensing node and meeting the data transmission link condition.

7. The method according to claim 6, characterized in that After selecting at least one data transmission link with a sensing node as a source node and any computing node in the target ocean sensing network as a destination node from the target ocean sensing network, the method further includes: If the first data transmission link does not exist in the at least one data transmission link, determining the link transmission performance metric value corresponding to each of the at least one data transmission links based on the total remaining bandwidth and link transmission delay corresponding to each of the at least one data transmission links; The second data transmission link with the largest link transmission performance metric value among the at least one data transmission link is used as the data transmission link corresponding to the one sensing node and meeting the data transmission link condition.

8. The method according to claim 7, characterized in that The determining, based on the total amount of remaining bandwidth and the link transmission delay respectively corresponding to the at least one data transmission link, the link transmission performance metric value respectively corresponding to the at least one data transmission link comprises: For the at least one data transmission link, the following operations are performed respectively: Obtain a first metric value based on a first ratio obtained by the total amount of the remaining bandwidth to the total bandwidth of a data transmission link, and a first weight factor set for the first ratio; Obtaining a second metric value based on a second ratio obtained between the link transmission delay and a link transmission delay threshold corresponding to the one data transmission link, and a second weight factor set for the second ratio; The link transmission performance metric value is determined based on the first metric value and the second metric value.

9. A data transmission device for ocean sensing data, characterized in that: include: An information acquisition module is used to obtain node information of a node set corresponding to a target sea area; The node information represents the data transmission performances respectively corresponding to the multiple nodes included in the node set, the multiple nodes including: at least one sensing node, an intermediate node and a computing node, each intermediate node is used to transmit the ocean sensing data of the target sea area sensed by the corresponding sensing node to the corresponding computing node, so that the computing node predicts the marine weather of the target sea area according to the ocean sensing data; A network construction module, configured to filter out a node subset that meets a preset data transmission performance condition from the node set based on the node information, and construct a target ocean perception network of the target sea area based on the node subset; A link selection module, used to select at least one data transmission link that meets a preset data transmission link condition from the target ocean sensing network; A data transmission module is used to transmit the ocean sensing data sensed by at least one sensing node included in the node subset based on the at least one data transmission link.

10. An electronic device comprising: processor; as well as Memory for storing programs, The program includes instructions, which, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 8.

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