A data transmission method, device and electronic equipment for marine sensing data

Abstract

The application provides a data transmission method and device for marine sensing data and electronic equipment, and relates to the technical field of communication networks. In the application, at least one sensing node, an intermediate node and a computing node included in a node set corresponding to a target sea area can be used to construct a multi-source target marine sensing network, meeting the high requirements of marine weather forecasting on data transmission and processing and empowering future intelligent marine weather forecasting scenarios. Furthermore, at least one data transmission link meeting preset data transmission link conditions is selected from the target marine sensing network, the link resources in the target marine sensing network are optimized, the link configuration in the target marine sensing network is dynamically adjusted, the transmission delay of marine sensing data is reduced, and the overall transmission efficiency of the target marine sensing network is improved. That is, the rationality and timeliness of marine sensing data transmission can be improved, and the performance and real-time forecasting capability of the marine sensing network can be 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 sensing data. Background Art

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

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

[0004] Therefore, ocean sensing networks, comprised of a variety of sensing devices, are being constructed to collect, transmit, and process large-scale ocean sensing data, adapting to the complex and ever-changing ocean environment. However, current ocean sensing networks may experience issues with inefficient data transmission links or high latency when transmitting ocean sensing data. This can lead to inability to report collected ocean sensing data to the network in a timely manner, or even to failure to do so, hindering real-time ocean weather forecasting.

[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 urgent problem that needs to be solved. 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 capabilities of the ocean perception network.

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

[0008] Obtaining node information of a node set corresponding to a target sea area; the node information represents data transmission performance corresponding to a plurality of nodes included in the node set, the plurality of nodes including: at least one sensing node, an intermediate node, and a computing node, each intermediate node being configured to transmit ocean sensing data of the target sea area sensed by a corresponding sensing node to a corresponding computing node, so that the computing node predicts ocean weather in the target sea area based on 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 node subset is transmitted.

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

[0013] The node's node association number 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 node's environment;

[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 perception 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 the 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 except for a 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 a set ocean data sensing range and at least one node in a node subset other than a set number of nodes, an initial ocean sensing network is expanded to obtain a target ocean sensing 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 current sensing range of the ocean sensing network;

[0025] The current ocean sensing network is expanded based on the node association number corresponding to at least one newly added node within the expanded sensing range.

[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 corresponding to a sensing node and meeting the data transmission link condition.

[0030] In an optional embodiment, after 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, 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 corresponding to a sensing node and meeting the data transmission link condition.

[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 includes:

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

[0035] Obtaining a first metric value based on a first ratio obtained by the total 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 configured to acquire node information of a node set corresponding to a target sea area; the node information represents the data transmission performance corresponding to each of the multiple nodes included in the node set, wherein the multiple nodes include: at least one sensing node, an intermediate node, and a computing node; each intermediate node is configured 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 can predict the marine weather of the target sea area based on the ocean sensing data;

[0040] A network construction module is used to filter out a node subset that meets preset data transmission performance conditions from the 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 is used to select at least one data transmission link that meets preset data transmission link conditions from the target ocean sensing network;

[0042] The data transmission module 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.

[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 the 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 except for a set number of nodes, the initial ocean perception network is expanded to obtain a target ocean perception network.

[0046] In an alternative embodiment, when the target marine sensing network is obtained by expanding the initial marine sensing network based on the set marine data sensing range and at least one node in the node subset other than the set number of nodes, the network construction module is specifically configured to:

[0047] expanding the initial marine sensing network multiple times according to the set network expansion speed until the sensing range of the expanded marine sensing network is the marine data sensing range;

[0048] the expanded marine sensing network as the target marine sensing network;

[0049] In an alternative embodiment, when the initial marine sensing network is expanded multiple times according to the set network expansion speed, the network construction module is specifically configured to:

[0050] In one expansion process of the initial marine sensing network, the following operations are performed:

[0051] determine the sensing range after expansion based on the network expansion speed and the sensing range of the current marine sensing network;

[0052] expand the current marine sensing network based on the node association number corresponding to the at least one newly added node in the sensing range after expansion.

[0053] In an alternative embodiment, when at least one data transmission link that meets the preset data transmission link condition is selected from the target marine sensing network, the link selection module is specifically configured to:

[0054] for at least one sensing node in the target marine sensing network, the following operations are performed respectively:

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

[0056] select at least one data transmission link from the target marine sensing network, with one sensing node as the source node and any computing node in the target marine sensing network as the destination node;

[0057] In an alternative embodiment, after at least one data transmission link is selected from the target marine sensing network, with one sensing node as the source node and any computing node in the target marine sensing network as the destination node, the link selection module is further configured 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 corresponding to a sensing node and meeting the data transmission link condition.

[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 configured to:

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

[0062] Obtaining a first metric value based on a first ratio obtained by the total 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 including at least one perception node, intermediate node and computing node 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 following description, and in part will become apparent from the description, or may be understood by practicing the present application. The objectives and other advantages of the present application can be realized and obtained through 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 of the present application. In the drawings:

[0075] Figure 1 A schematic diagram of the network architecture of an ocean sensing network applicable to embodiments 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 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 structural diagram 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 following describes embodiments of the present application in more detail 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 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 for illustrative purposes only 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 embodiments of the present application can be performed in different orders and / or in parallel. In addition, the method embodiments 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". The 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 "multiple" mentioned in this application are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, they 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 following briefly introduces the design concept of the embodiment of the present application:

[0087] With the growing demand for AI-based forecasting of marine weather (e.g., storms, ocean currents, and waves), efficient transmission of ocean sensing data has become crucial for accurate marine weather prediction. Consequently, efforts are underway to improve existing ocean environment models or marine sensing networks to more accurately predict marine weather. As marine weather forecasting systems rapidly evolve toward greater precision and heterogeneity, an increasing number of marine sensing networks are emerging, using a variety of large-scale sensing devices (e.g., sensors) to collect real-time ocean data, such as seawater temperature, wave height, wind speed, and ocean current direction.

[0088] To fully leverage the capabilities of emerging technologies and achieve intelligent and precise marine weather forecasting, ocean sensing networks are facing higher requirements, including high-precision perception, collaborative transmission, distributed computing, and rapid forecasting. The future ocean sensing network will be a new collaborative system based on cyber-physical fusion. This requires not only multi-dimensional, distributed sensing and detection, but also real-time, stable communication and transmission, and powerful, 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 evolves towards digitalization, diversification, and intelligence, the limitations of a single type of sensing device are becoming increasingly prominent. Coordinated sensing with multiple sensing devices is becoming an inevitable trend. Ocean sensing networks cover vast areas, including space, land, surface, and underwater. The unique geographical and climatic conditions make the construction and maintenance of network infrastructure extremely complex and costly. Although various network systems have been deployed in the ocean, the coordinated sensing of these heterogeneous devices is poor due to their diverse deployment methods and inconsistent communication formats and standards.

[0090] Therefore, there is an urgent need to build a unified ocean perception network architecture to enable the efficient collection, transmission, and processing of large-scale ocean (environmental) data and adapt to complex and changing environmental demands. Within the ocean perception network architecture, efficient allocation of link resources is one of the key elements to ensure the quality of ocean perception data transmission. Irrational link resource allocation can lead to data congestion during ocean perception data transmission, significantly increasing transmission latency and impacting the real-time nature of marine meteorological forecasts. Furthermore, unoptimized link resources can reduce the resilience of the ocean perception network, leading to poor performance in the face of traffic bursts or failures, and reduced robustness and reliability.

[0091] From the perspective of system level, the optimization of link resources is closely related to the scheduling resources, and the rationality of scheduling resources directly depends on the allocation of link resources. If the scheduling resources are not optimized on the basis of the optimization of link resources, it may lead to suboptimal or invalid selection of link resources, causing overload or imbalance of data transmission link, further exacerbating the congestion problem of ocean sensing network, and thus significantly increasing the transmission delay. This not only affects the overall stability of the network, but also may even cause local network collapse or communication interruption. Therefore, the optimization of link resources and scheduling resources is crucial, and both must complement each other in the architecture design of ocean sensing network, and jointly act on the efficient operation of ocean sensing network. Ocean sensing network without collaborative optimization not only faces the risk of unbalanced resource allocation and unreasonable transmission path, but also may lead to low utilization of ocean sensing network, and cannot adapt to complex dynamic changes.

[0092] Therefore, in order to solve or improve the above problems, through the optimization of link and scheduling resources, the rationality and timeliness of data transmission path can be ensured, the continuity and stability of network operation can be maintained, and the performance and real-time forecasting ability of ocean sensing network can be further improved. Therefore, the embodiment of the present application proposes a data transmission of ocean sensing data, which can specifically include: obtaining node information of a node set corresponding to a target sea area; the node information represents the data transmission performance of 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, each intermediate node is used to transmit ocean sensing data of a target sea area sensed by a corresponding sensing node to a corresponding computing node, so that the computing node predicts the ocean meteorology of the target sea area according to the ocean sensing data; then, based on the obtained node information, a node subset satisfying 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; further, at least one data transmission link satisfying a preset data transmission link condition is selected from the target ocean sensing network; finally, 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.

[0093] In this way, a multi-source target ocean perception network can be constructed by including at least one perception node, intermediate node, and computing node in the node set, meeting the high requirements of marine meteorological forecasting for data transmission and processing, and empowering 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. In addition, 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 Figure 1 , which is a schematic diagram of the network architecture of an ocean perception network applicable to embodiments 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. Nodes between the perception layer 101, the edge layer 102, and the computing layer 103 can exchange information through a communication network, wherein the communication methods adopted by the aforementioned communication network may include: wireless communication methods and wired communication methods.

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

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

[0098] The number of nodes involved in each network layer in the network architecture is not limited in the embodiments of the present application. For example, more perception nodes can be included in the perception layer 101, or fewer perception nodes can be included, or other network devices can also be included. Optionally, the number of network layers in the network architecture is also not limited in the embodiments of the present application. For example, more network layers can also be included. As shown in the following figure, only the perception layer 101, the edge layer 102 and the computing layer 103 are taken as examples for description, and the following briefly introduces each network layer and its respective function. Figure 1

[0099] The perception layer 101 is located at the bottom layer of the network architecture, and is composed of various perception devices such as satellites, unmanned aerial vehicles, buoys and submersible vehicles distributed in space, sky, land and ocean, responsible for the perception of ocean wave data and communication with upper layer nodes.

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

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

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

[0103] The computing layer 103 is located at the top layer of the network architecture, and can be composed of supercomputers or server clusters. These devices have strong computing and storage capabilities. The tasks of this layer include data processing, AI model training and prediction result analysis, etc. 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 perception nodes in the perception layer 101 can be connected to the computing nodes in the computing layer 103 through the intermediate nodes in the edge layer 102, or some perception nodes can be directly connected to the computing nodes in the computing layer 103, in order to improve the stability and robustness of the ocean perception network. In addition, the perception nodes in the perception layer 101 can be connected only to the intermediate nodes in the edge layer 102, in order to improve the response speed of the ocean perception network and reduce the computing load of the computing layer 103.

[0105] ​Since accurate and timely ocean weather forecasts (e.g., wave conditions) require a large amount of multi-source data as input, it is important to ensure that the sensing devices that acquire this input data can work together. Therefore, based on the structural design of the ocean sensing network, the ocean sensing data sensed by each sensing node in the sensing layer 101 can be acquired and processed in real time and comprehensively, thereby more accurately predicting ocean 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 marine data, improves the management efficiency of marine perception data, and thus improves the performance of the ocean perception network and the real-time forecasting capability of marine meteorology.

[0107] It is worth noting that the ocean perception network provided in the embodiments of the present application can be constructed based on the node information of the node set corresponding to the target sea area. Exemplarily, this can include: obtaining the node information of the node set corresponding to the target sea area; the node information represents the data transmission performance corresponding to each of the multiple nodes included in the node set, where the multiple nodes include: at least one perception node, an intermediate node, and a computing node. Based on the node information, a node subset that meets the preset data transmission performance conditions is screened from the node set, and a target ocean perception network for the target sea area is constructed 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 understanding of the spirit and principles of the present application, and the implementation of the present application is not limited in this respect.

[0109] See Figure 2 As shown, it is a schematic diagram of the implementation process of a data transmission method for ocean perception data provided by an embodiment of the present application. The execution subject takes the server of 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 node information characterizing the plurality of nodes in the node set comprises data transmission performance of the plurality of nodes respectively, and the plurality of nodes can comprise at least one perception node, at least one intermediate node and at least one computing node.

[0112] Each perception node can be configured to perceive a target sea area to obtain corresponding marine perception data, each intermediate node can be configured to transmit marine perception data perceived by the corresponding perception node to the corresponding computing node, and each computing node can be configured to predict marine weather of the target sea area according to the marine perception data of the target sea area. Optionally, the intermediate node can also predict marine weather of the target sea area according to the marine perception data uploaded by the perception node.

[0113] The marine perception data can comprise, but is not limited to, marine data such as sea temperature (i.e. sea water temperature), sea surface height, sea surface wind speed and sea water flow direction. The marine weather can comprise sea wave state, whether a storm is generated or not.

[0114] For example, when step S201 is performed, the server can obtain a node set for marine weather prediction of a target sea area. The node set can comprise a plurality of perception nodes (i.e. marine data perception devices) located in the sea (e.g. seabed, sea, sea surface), land, sky and space, for example, 100 sensors in the marine space, each sensor having a spacing of 200 meters in the marine space; a plurality of intermediate nodes (i.e. intermediate node cluster) are deployed on the ground, and the intermediate node cluster comprises 100 intermediate nodes; and a plurality of computing nodes (i.e. computing node cluster) are deployed on the ground, and the computing node cluster comprises 50 computing nodes.

[0115] In an optional implementation, the node information can comprise any one or combination of a node association number, a node transmission delay and a stability metric value of each node 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 the node is the number of edges connected to the node; for a directed graph, the in-degree of the node refers to the number of edges pointing to the node from other nodes, and the out-degree refers to the number of edges departing from the node, so the node association number is the sum of the in-degree and the out-degree. The node transmission delay refers to the data transmission delay between two nodes, i.e. the end-to-end delay. The stability metric value, i.e. the stability factor, is used to measure the data transmission quality of the node in the environment. If the stability metric value is smaller, it indicates that the corresponding node is less stable and the data transmission quality is poorer; on the contrary, if the stability metric value is larger, it indicates that the corresponding node is more stable and the data transmission quality is better.

[0116] In the embodiments of the present application, the above node set corresponds to an undirected graph. For example, the undirected graph can be represented as G (V, E), V represents the node set, and E represents the edge set. It is assumed that the node set V comprises 100 perception nodes, 100 intermediate nodes and 50 computing nodes.N nodes, then the node set V={ =1,..., N}. Optional, node The node association number can be expressed as ,node The node transmission delay can be expressed as ,node The stability measure of can be expressed as .

[0117] Ocean sensing data to be transmitted (i.e. data stream) For example, express The source node (i.e., the perception node), express The destination node (i.e., the intermediate node or computing node with computing capabilities), express The size of express The upper bound of the link transmission delay (that is, 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 a combination of the node association number, node transmission delay, and stability metric value corresponding to each of the multiple nodes in the node set, the preset data transmission performance conditions may 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 node's environment; the node transmission delay of the node is less than a node transmission delay threshold set for the node's environment; and the node stability metric value is less than a stability metric threshold set for the node's environment.

[0120] For example, the node subset obtained from the above node set V can be expressed as , and the node set V except the node subset The node subset outside can be represented as Correspondingly, in the edge set E corresponding to the node set V, the node subset The corresponding edge set can be expressed as , a subset of nodes The corresponding edge set can be expressed as .

[0121] A subset of the nodes above It can also be understood as a node subset obtained by optimizing the node association number, node transmission delay and stability metric. 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 space, sky, ground and ocean (i.e., space, sky, ground and ocean) are set. Nodes in The node association number is defined as For example, if the node The node association threshold is expressed as Then, the node association threshold of the node in space can be expressed as , the node association number threshold of the node in the sky can be expressed as , the node association number threshold of the node on the ground can be expressed as , the node association number threshold of nodes in the ocean can be expressed as 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 for different nodes in different environments of air, space, land and sea can be expressed as follows:

[0124]

[0125]

[0126]

[0127]

[0128] in, Represents a node in space The number of node associations, Represents a node in the sky The number of node associations, Represents a node on the ground The number of node associations, Indicates that the ocean is at the node The number of node associations.

[0129] There are also differences in node transmission delay thresholds between nodes in different environments in the sky, land, and sea. the node in the space the node transmission delay of the node For example, if the node the node transmission delay threshold of the node is represented as . Then, the node transmission delay threshold of the node in the space can be represented as the node transmission delay threshold of the node in the sky can be represented as the node transmission delay threshold of the node on the ground can be represented as the node transmission delay threshold of the node in the sea can be represented as . Then, the node transmission delay constraint that the node transmission delay of the node is less than the node transmission delay threshold set for the environment where the node is located can be represented as:

[0130] , ,

[0131] Based on the above representation of the node transmission delay constraint, the node transmission delay constraint for different nodes in different environments of space, sky, ground and sea can be represented as:

[0132]

[0133]

[0134]

[0135]

[0136] wherein, represents the node transmission delay of the node in the space, represents the node transmission delay of the node in the sky, represents the node transmission delay of the node on the ground, represents the node transmission delay of the node in the sea.

[0137] Nodes in different environments, such as the sky, land, and sea, also have different stability metric thresholds. For example, nodes in space (e.g., satellites) are located in Earth orbit and are not affected by ground weather, but may be disturbed by the space environment (e.g., head-on storms) and are subject to mobility. Nodes in the sky (e.g., drones) are subject to weather conditions and battery life, and may experience stability issues during flight. The flight environment is highly variable and susceptible to interference. Nodes on the ground (e.g., weather stations) are typically fixed in a specific location, less affected by the environment, and have relatively stable connections and operations. Nodes on the sea surface (e.g., buoys) move with the waves and are designed to operate normally in inclement weather, but may still be affected by natural factors such as wind and waves. Nodes below the sea surface (e.g., underwater vehicles) operate in underwater environments and may encounter complex water currents and other obstacles, resulting in unstable connections.

[0138] Still based on node subset Nodes in The stability measure is For example, if the node The stability metric threshold is expressed as Then, the node transmission delay threshold of the node in space can be expressed as , the node transmission delay threshold of the node in the sky can be expressed as , the node transmission delay threshold of the ground node can be expressed as , the node transmission delay threshold of the node in the ocean can be expressed as The stability metric value constraint of the node above is less than the stability metric threshold set for the node's environment, which can be expressed as:

[0139] , ,

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

[0141]

[0142]

[0143]

[0144]

[0145] in, Represents a node in space The stability measure of Represents a node in the sky The stability measure of Represents a node on the ground The stability measure of Indicates that the ocean is at the node 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 filtering out the node subset based on the above method, the server can select a set number of nodes in the node subset (eg, nodes), and a preset node connection relationship, to construct an initial ocean perception network of the target sea area; 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., edge).

[0148] For example, see Figure 3 As shown in Figure 1, the initial ocean perception network can 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 sensing 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 sensing network, the server can expand the initial ocean sensing network multiple times according to the set network expansion speed until the perception range of the expanded ocean sensing network reaches the ocean data perception range, thereby using the expanded ocean sensing network as the target ocean sensing network. Furthermore, during one expansion of the initial ocean sensing network, the following operations can be performed: determining the expanded perception range based on the network expansion speed and the perception range of the current ocean sensing network; and expanding the current ocean sensing network based on the node association number corresponding to each of the at least one newly added nodes within the expanded perception range. Thus, it can be seen that the link resource optimization of the wave sensing network can change constantly as the network perception range changes.

[0150] Assume that in the above process of expanding or expanding the initial ocean perception network, the initial ocean perception network is defined as nodes and Edges, set the initial radius of expansion (i.e. the coverage radius of the initial ocean perception network) to , the global radius (i.e. the coverage radius of the target ocean sensing network is ), choose the center of the initial ocean perception network as the center of the circle. The coverage radius of the initial ocean perception network is from Start with c The speed of network expansion increases. When a new node is added to the already built ocean sensing network, it will m Existing nodes (i.e., nodes in the already constructed ocean sensing network) m nodes) connected, where m , until it grows to the initial radius = 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 subsets can be defined is the set of nodes within the expansion radius, as well as the above node subsets is the node set outside the expansion radius, and the above node subset The corresponding edge set That is, the edge set within the expansion radius, the above node subset The corresponding edge set That is, the edge set outside the expansion radius is the node subset in the process of initial ocean perception network expansion or expansion. The nodes in will gradually join the node subset In the node subset The nodes in join the node subset Will choose later n Node subset At this time, when selecting n When connecting nodes, the connection needs to be optimized according to the link resource design.

[0152] According to the rules of link resource optimization, assuming A subset of nodes Nodes that already exist in A subset of nodes Prepare a new node subset To add a link between two nodes, the added link must meet the constraints of node association number, node transmission delay and stability metric value before it can be added to the node. and nodes If the link is successfully added, you can add the node Joining a subset of nodes In, and the edge [ ]Add edge set In, that is ,at the same time[ ] If the constraints of the number of node associations, node transmission delay and stability metric value are not met (i.e. the threshold requirements of the number of node associations, node transmission delay and stability metric value), the node will not be connected to the node. and nodes Add links between them.

[0153] In ocean wave sensing networks, long data transmission times prevent real-time analysis, leading to an inability to accurately grasp the true ocean weather conditions. Furthermore, longer transmission times increase the likelihood of noise and interference, affecting the accuracy of predicted ocean weather conditions. Furthermore, sensing equipment, whether in the air or underwater, operates in relatively harsh environments, potentially subject to external attacks or unexpected situations such as power exhaustion, which can cause node failure. Therefore, ensuring the real-time and stable nature of data is crucial. By optimizing the link resources of multi-source ocean sensing network nodes through the aforementioned method, link resources can be allocated rationally and efficiently to adapt to the changing ocean environment, thereby reducing network latency. Furthermore, a robust link structure enhances the stability of the entire system. This significantly improves data transmission efficiency and enhances network robustness.

[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 may perform the following operations for at least one perception node in the target ocean perception network: select at least one data transmission link from the target ocean perception network with a perception node as the source node and any computing node in the target ocean perception network as the destination node; 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 that meets the data transmission link conditions.

[0156] To ensure sufficient computing resources for subsequent marine weather forecasts, the server can select computing nodes with the most remaining computing resources as target nodes based on certain rules. For example, multiple computing nodes in the computing layer can be sorted by the amount of remaining computing resources, thereby selecting computing nodes based on the order of remaining computing resources.

[0157] Taking the perception node A as an example, if the link transmission delay of the data transmission link corresponding to the perception node A is less than the link transmission delay threshold value set for the perception node A that is , the data transmission link can be used as the data transmission link corresponding to the perception node A that meets the data transmission link condition. If the link transmission delay of the data transmission link corresponding to the perception node A is greater than or equal to the aforementioned link transmission delay threshold value that is , it is necessary to perform link optimization (or scheduling link resource optimization) on the data transmission link corresponding to the perception node A according to the target marine perception network to ensure that the data transmission delay requirement of marine perception data is met, thereby improving the data transmission efficiency.

[0158] Since it is crucial to implement a scheduling resource optimization strategy in a multi-source marine perception network, it can ensure efficient data transmission through the best data transmission link, reduce transmission delay, avoid data congestion, and improve the load balancing of the marine perception network. In addition, a good scheduling resource optimization strategy can enhance the robustness of the marine perception network, enabling it to adapt to complex and changing marine environments. Therefore, scheduling optimization of data transmission links not only improves the response speed and accuracy of data processing, but also enhances the adaptability and stability of the marine perception network when facing environmental challenges.

[0159] In a multi-source marine perception network, perception nodes usually require low-latency and high-bandwidth transmission paths or data transmission links. That is, for a multi-source marine perception network, the scheduling resource optimization strategy considers both link transmission delay and bandwidth as key factors.

[0160] Therefore, in an optional implementation, if the first data transmission link does not exist in the at least one data transmission link, the link transmission performance metric value corresponding to each of the at least one data transmission link can be determined based on the total amount of remaining bandwidth and the link transmission delay corresponding to each of the at least one data transmission link, and the second data transmission link with the largest link transmission performance metric value among the at least one data transmission link can be used as the data transmission link corresponding to the perception node that meets the data transmission link condition.

[0161] Obviously, based on the above method, the scheduling resource optimization strategy proposed in the present application can optimize the link transmission delay and bandwidth together to determine the link transmission performance metric value of the data transmission link.

[0162] ​​Firstly, the residual bandwidth of the data transmission link is one of the important resources that can be scheduled, and the path with larger residual bandwidth can effectively avoid the ocean sensing data congestion on one data transmission link, thereby achieving load balancing of the entire ocean sensing network. For example, assuming that the ocean sensing data of a certain sensing node from the source node to the destination node searches for M data transmission links, indicates the ocean sensing data in the first data transmission link in the ocean sensing network, wherein, [ , ],..., , ],..., , }, the data transmission direction of the aforementioned data transmission link can also be represented as: → →...→ → →...→ → . Therefore, the server can use to represent the link transmission delay of the ocean sensing data in the first data transmission link in the ocean sensing network, and use to represent the total residual bandwidth of the ocean sensing data in the first data transmission link in the ocean sensing network.

[0163] Optionally, the calculation formula of the total residual bandwidth of the aforementioned first data transmission link can be specifically represented as follows:

[0164]

[0165] wherein, represents the total bandwidth of the aforementioned first data transmission link, represents the bandwidth used by the aforementioned first data transmission link. If there are multiple ocean sensing data occupying bandwidth on the aforementioned first data transmission link, and assuming that the aforementioned multiple ocean sensing data respectively occupy bandwidth , ,..., , then the aforementioned first The bandwidth used by the data transmission link The sum of the bandwidths occupied by the plurality of marine sensing data.

[0166] In other words, the first The bandwidth used by the data transmission link may be specifically expressed as follows:

[0167]

[0168] Therefore, the first The total amount of residual bandwidth of the data transmission link may be further expressed as follows:

[0169]

[0170] Secondly, in the transmission process of marine sensing data, the link transmission delay of marine sensing data from the sensing end (i.e. the sensing node) to the computing end (i.e. the computing node) mainly consists of four parts: sending delay, propagation delay, processing delay and queuing delay. For example, the aforementioned processing delay may represent the time required for a node in the target marine sensing network to process marine sensing data (such as routing or link selection, data analysis, etc.), which is usually relatively short. Optionally, the processing delay of a node in the target marine sensing network may be defined as .

[0171] The aforementioned queuing delay may represent the time for marine sensing data to wait for transmission in a node of the target marine sensing network. This part of the delay is usually uncertain and depends on the load and congestion state of the node in the target marine sensing network. Optionally, the queuing delay of a node in the target marine sensing network may be defined as .

[0172] The aforementioned sending delay may represent the time required for marine sensing data to be sent to the data transmission link, which is mainly related to the size of the marine sensing data and the bandwidth of the data transmission link. Optionally, the sending delay of a node in the target marine sensing network may be defined as . The calculation formula of the aforementioned sending delay may be specifically expressed as follows:

[0173]

[0174] wherein, represents the size of the marine sensing data, represents the bandwidth of the data transmission link.

[0175] The propagation delay The time required for the ocean perception data to propagate on the data transmission link can be characterized, which mainly depends on the link length of the data transmission link and the propagation speed of the ocean perception data. Optionally, the propagation delay on the data transmission link (L) can be defined as , . The calculation formula of the aforementioned propagation delay can be specifically expressed as follows:

[0176]

[0177] wherein, denotes the link length of the data transmission link, denotes the propagation speed of the data transmission link. Since the multi-source perception nodes are respectively in different environments in space, air, land and sea, the propagation delays caused by different transmission media exist differences, and therefore, the aforementioned propagation delay can be expressed as follows:

[0178]

[0179] wherein, denotes the propagation delay of the data transmission link in space, denotes the propagation delay of the data transmission link in air, denotes the propagation delay of the data transmission link on land, denotes the propagation delay of the data transmission link in sea.

[0180] Since the aforementioned scheduling resource optimization needs to consider whether congestion occurs in the target ocean perception network during transmission, a congestion flag can be designed. Specifically, if there is no congestion in the scheduled data transmission link, the total delay (i.e., the link transmission delay) is the sum of the sending delay , the propagation delay and the processing delay . If congestion occurs in the scheduled data transmission link, the total delay is the sum of the sending delay , the propagation delay , the processing delay and the queuing delay . Therefore, the calculation formula of the total delay (i.e., the aforementioned ) of the nodes is specifically 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, it 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 by the total remaining bandwidth to 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 by the link transmission delay to the link transmission delay threshold corresponding to the 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 impact of the remaining total bandwidth and the link transmission delay on the link transmission performance determined based on a plurality of experimental data.

[0184] For example, assuming that the scheduling optimization target (i.e., the above-mentioned data transmission link, such as m The link transmission performance metric value is , then the weighted optimization formula for the total remaining bandwidth and link transmission delay is expressed as follows:

[0185]

[0186] in, represents the first weight factor mentioned above, / represents the first ratio mentioned above, Indicates the total remaining bandwidth of the above data transmission link, Indicates the total bandwidth of the above data transmission link, represents the second weight factor mentioned above, / represents the second ratio mentioned above, represents the link transmission delay of the above data transmission link, Indicates the link transmission delay threshold set for 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 above scheduling resource optimization strategy can be based on the optimization target corresponding to When When the value is larger, it means that the remaining bandwidth of the data transmission link is more abundant and the data transmission delay is smaller, so it is preferred. Larger data transmission links are used for resource scheduling.

[0188] In another optional implementation, the server can also determine a link transmission performance metric corresponding to at least one data transmission link based on the total remaining bandwidth and total link transmission delay corresponding to each of the at least one data transmission links. The server can then select the data transmission link with the highest link transmission performance metric among the at least one data transmission link as the data transmission link that meets the data transmission link conditions for the sensing node. This approach can ensure, to the greatest extent possible, that the stability, reliability, and data transmission efficiency of the selected data transmission link meet data transmission requirements.

[0189] For example, see Figure 4 As shown, assuming 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, the data transmission links that meet the above data transmission link conditions are selected. Figure 4 As shown, the aforementioned data transmission link is: node S→node 2→node 1→node D.

[0190] It should be noted that, given that sensing nodes in the target ocean sensing network are often located in harsh environments and are prone to abnormal situations such as communication interruptions or device disconnection, scheduling resource (or link) optimization strategies can incorporate mechanisms such as disjoint paths and multipath routing. This means that at least one data transmission link must contain no identical nodes other than the source and destination nodes, thereby improving the reliability and fault tolerance of the target ocean sensing network. This design enables the continuous transmission of ocean sensing data via backup paths when the primary 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 ocean 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 ocean environment, sensor equipment may frequently lose connection or malfunction. Therefore, 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 the scheduling resource optimization strategy. 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. Second, multi-path routing can disperse traffic, achieve load balancing and bandwidth optimization, and reduce overall transmission latency by selecting data transmission links with low data transmission latency to meet real-time requirements.

[0192] For example, in the design of multi-path routing and disjoint paths, assuming that the topology of the target ocean-aware network is a graph G'(V', E'), given the source node and destination node , find multiple data transmission links from source node to destination node , ,..., These paths are used for data transmission. Define each path as , represent the set of links that the path passes through. The selection of multi-path routing can be represented as a set of paths { , ,..., } where . That is, the set of all possible paths from source node s to destination node t : ={ | , → }.

[0193] The above disjoint paths or routes refer to the multiple data transmission links from the source node to the destination node without sharing links or nodes. Assuming that the paths , ,..., pass through the link sets , ,..., , the condition for link or path disjointness can be represented as:

[0194] ,

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

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

[0197] ​The at least one sensing node included in the above-mentioned subset of transmission nodes is a sensing node corresponding to the at least one data transmission link. For example, assuming that five data transmission links meeting the preset data transmission link condition are selected from the target marine sensing network, the server can transmit marine 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 marine sensing data transmission method provided in the embodiments of the present application, at least one sensing node, an intermediate node, and a computing node included in the node set corresponding to the target sea area can be used to construct a multi-source target marine sensing network, meeting the high requirements of marine weather prediction on data transmission and processing, and empowering future intelligent marine weather forecasting scenarios. Moreover, by selecting at least one data transmission link meeting the preset data transmission link condition from the target marine sensing network, the link resources in the target marine sensing network are optimized, that is, the link configuration in the target marine sensing network can be dynamically adjusted according to the data transmission demand and the link state to reduce the transmission delay of marine sensing data, thereby improving the overall transmission efficiency of the target marine sensing network. That is, the rationality and timeliness of marine sensing data transmission can be improved, and the performance and real-time forecasting capability of the marine sensing network can be improved.

[0199] Further, based on the same technical concept, the embodiments of the present application provide a marine sensing data transmission device for implementing the above-mentioned method flow of the embodiments of the present application. As shown in Figure 5 The marine sensing data transmission device 500 can 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 configured to acquire node information of a node set corresponding to a target sea area. The node information represents data transmission performance of a plurality of nodes included in the node set. The plurality of nodes include at least one sensing node, an intermediate node, and a computing node. Each intermediate node is configured to transmit marine sensing data sensed by a corresponding sensing node to a corresponding computing node, so that the computing node predicts marine weather of the target sea area according to the marine sensing data.

[0201] The network construction module 502 is configured to filter a node subset meeting a preset data transmission performance condition from the node set based on the node information, and construct a target marine sensing network of the target sea area based on the node subset.

[0202] The link selection module 503 is configured to select at least one data transmission link meeting a preset data transmission link condition from the target marine sensing network.

[0203] The data transmission module 504 is configured to transmit marine 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 the target marine sensing network of the target sea area is constructed based on the node subset, the network construction module 502 is specifically configured to:

[0205] construct an initial marine sensing network of the target sea area based on the preset number of nodes in the node subset and the preset node connection relationship;

[0206] perform network expansion on the initial marine sensing network based on the preset marine data sensing range and at least one node in the node subset other than the preset number of nodes, to obtain the target marine sensing network.

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

[0208] perform multiple expansions on the initial marine sensing network at a preset network expansion speed, until the sensing range of the expanded marine sensing network is the marine data sensing range;

[0209] take the expanded marine sensing network as the target marine sensing network;

[0210] In an optional embodiment, when the multiple expansions are performed on the initial marine sensing network at the preset network expansion speed, the network construction module 502 is specifically configured to:

[0211] in one expansion process of the initial marine sensing network, the following operations are performed:

[0212] determine the sensing range after expansion based on the network expansion speed and the sensing range of the current marine sensing network;

[0213] expand the current marine sensing network based on the node association number corresponding to each of the at least one newly added node in the sensing range after expansion.

[0214] In an optional embodiment, when the at least one data transmission link satisfying the preset data transmission link condition is selected from the target marine sensing network, the link selection module 503 is specifically configured to:

[0215] for at least one sensing node in the target marine sensing network, the following operations are respectively performed:

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

[0217] selecting, from the at least one data transmission link, a first data transmission link with a link transmission delay being less than a link transmission delay threshold set for the one sensing node, as the data transmission link satisfying the data transmission link condition corresponding to the one sensing node.

[0218] In an optional embodiment, after selecting, from the target ocean sensing network, at least one data transmission link with a source node being one sensing node and a destination node being any computing node in the target ocean sensing network, the link selecting module 503 is further configured 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 link based on a remaining bandwidth total amount and a link transmission delay corresponding to each of the at least one data transmission link, respectively;

[0220] selecting, from the at least one data transmission link, a second data transmission link with a largest link transmission performance metric value as the data transmission link satisfying the data transmission link condition corresponding to the one sensing node.

[0221] In an optional embodiment, when determining the link transmission performance metric value corresponding to each of the at least one data transmission link based on a remaining bandwidth total amount and a link transmission delay corresponding to each of the at least one data transmission link, respectively, the link selecting module 503 is specifically configured to:

[0222] for each of the at least one data transmission link, performing the following operations:

[0223] obtaining a first metric value based on a first ratio obtained from the remaining bandwidth total amount and a total bandwidth of one 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 from the link transmission delay and a link transmission delay threshold corresponding to one data transmission link, and a second weight factor set for the second ratio;

[0225] determining the link transmission performance metric value based on the first metric value and the second metric value.

[0226] Based on the description of the method embodiments and the device embodiments, the exemplary embodiments of the present application further provide an electronic device, comprising: at least one processor; and a memory connected with the at least one processor in communication. The memory stores a computer program capable of being executed by the at least one processor, and the computer program, when executed by the at least one processor, is configured to cause the electronic device to perform the method according to the embodiments of the present application.

[0227] The embodiments of the present application further provide a non-transitory computer readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is configured to cause the computer to perform the method according to the embodiments of the present application.

[0228] The embodiments of the present application further provide a computer program product comprising a computer program, wherein the computer program, when executed by a processor of a computer, is configured to cause the computer to perform the method according to the embodiments of the present application.

[0229] Referring to Figure 6 As shown in FIG. 6, a block diagram of an electronic device 600 that can be a server or a client of the present application will now be described, which is an example of a hardware device that can be applied to various aspects of the present application. The electronic device is intended to represent a wide variety of digital electronic computing devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computing devices. The electronic device can also represent a wide variety of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown in FIG. 6, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application described and / or claimed in this document.

[0230] As Figure 6 shown in FIG. 6, the electronic device 600 includes a computing unit 601 that 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 into 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 through 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 can be any type of device that can input information to the electronic device 600, and can receive inputted digital or character information, and generate key signal inputs related to user settings and / or function controls of the electronic device. The output unit 607 can be any type of device that can present information, and can 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 can include, but is not limited to, a magnetic 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 can 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 can be various general and / or special purpose 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, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, and the like. The computing unit 601 performs various methods and processes described above. For example, in some embodiments, the above-described data transmission method of ocean-aware data can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 608. In some embodiments, part or all of the computer program can 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 can be configured to perform the above-described data transmission method of ocean-aware data by any other appropriate means, for example, by means of firmware.

[0234] The program code for implementing the methods of the present application can be written in any combination of one or more programming languages. Such program code 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 when the program code is executed by the processor or controller, the functions / operations specified in the flow charts and / or block diagrams are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0235] In the context of this 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 apparatus. 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 apparatus, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, RAM, ROM, erasable programmable read-only memory (EPROM) or flash memory, optical fiber, 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., a magnetic disk, an optical disk, a memory, a programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including machine-readable media that receives machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0237] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a cathode ray tube (CRT) or a liquid crystal display (LCD) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, 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, speech, or tactile input.

[0238] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, 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] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[0240] And, it should be understood that all the disclosed herein are only preferred embodiments of the application, and cannot be used to limit the scope of the patent rights, therefore, the equivalent changes made according to the claims of the application, still belong to the scope of the application.

Claims

1. A method for transmitting ocean sensing data, characterized in that: include: Obtain node information of the node set corresponding to the target sea area; The node information represents data transmission performance corresponding to each of 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 being configured 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 marine weather of the target sea area based on the ocean sensing data; Based on the node information, a node subset that meets a preset data transmission performance condition 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; wherein, the target ocean perception network of the target sea area is constructed based on the node subset, including: constructing an initial ocean perception network of the target sea area based on a set number of nodes in the node subset and a preset node connection relationship; based on a set ocean data perception range and at least one node in the node subset other than the set number of nodes, expanding the initial ocean perception network to obtain the target ocean perception network; the links added in the target ocean perception network meet the constraints of node association number, node transmission delay and stability metric value; Selecting at least one data transmission link that meets a preset data transmission link condition from the target ocean sensing network; The ocean sensing data sensed by at least one sensing node included in the node subset is transmitted based on the at least one data transmission link.

2. The method according to claim 1, wherein 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 the environment where the node is located.

3. The method according to claim 1, wherein The method of expanding 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: Expanding the initial ocean sensing network multiple times according to a set network expansion speed until the sensing range of the expanded ocean sensing network reaches the ocean data sensing range; The expanded ocean sensing network is used as the target ocean sensing network.

4. The method according to claim 3, wherein The initial ocean sensing network is expanded multiple times according to the set network expansion speed, including: During an expansion of the initial ocean sensing network, the following operations are performed: Determining the expanded sensing range based on the network expansion speed and the current sensing range of the ocean sensing network; The current ocean sensing network is expanded based on the node association number corresponding to the at least one newly added node within the expanded sensing range.

5. The method according to claim 1 or 2, wherein: 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: 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; 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 the one sensing node is used as the data transmission link corresponding to the one sensing node and meeting the data transmission link condition.

6. The method according to claim 5, wherein After 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, the method further includes: 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 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.

7. The method according to claim 6, wherein The determining, based on the total 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 includes: For the at least one data transmission link, perform the following operations respectively: Obtaining a first metric value based on a first ratio obtained by the total 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.

8. 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 data transmission performance corresponding to each of 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 being configured 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 marine weather of the target sea area based on the ocean sensing data; A network construction module is used to screen out a node subset that meets preset data transmission performance conditions from the node set based on the node information, and construct a target ocean perception network for the target sea area based on the node subset; wherein, when constructing the target ocean perception network for the target sea area based on the node subset, the network construction module is specifically used to: construct an initial ocean perception network for the target sea area based on a set number of nodes in the node subset and a preset node connection relationship; expand the initial ocean perception network based on a 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 links added to the target ocean perception network meet the constraints of node association number, node transmission delay and stability metric value; A link selection module, configured 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 configured to transmit, 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.

9. 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 7.

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