An Adaptive Wireless Ad Hoc Network QoS Routing Method and Device Based on Ocean Evaporation Waveguide Effect

Abstract

This invention discloses an adaptive wireless ad hoc network QoS routing method and apparatus based on the marine evaporative waveguide effect, comprising: constructing a path loss model based on the propagation characteristics of marine evaporative waveguides; calculating array factor, beamwidth, and gain using a uniform linear array to achieve directional communication; dividing the network into multiple logical clusters, each cluster containing a cluster head and several member nodes, with the cluster heads forming a backbone routing subnet; using path loss as link weight in the backbone routing subnet and calculating the shortest path loss between any two cluster heads, defining its maximum value as the network diameter; receiving service data streams and prioritizing services according to service type; selecting feasible paths that meet constraints for each type of service; ranking feasible paths based on a normalized comprehensive cost function; and selecting the path with the lowest cost for data forwarding. This method can improve the communication quality and service quality assurance of the network in complex marine environments, and reduce link latency and packet loss rate.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to an adaptive wireless ad hoc network QoS routing method and apparatus based on the marine evaporation waveguide effect. Background Technology

[0002] Maritime communication serves as a core support for marine resource development, ocean shipping, maritime supervision, and emergency rescue; its quality directly impacts the safety and efficiency of national maritime economic activities. Microwave communication, with its advantages of high bandwidth, flexible deployment, and controllable cost, plays a crucial role in near-shore communication within a 50km-200km range. However, traditional maritime microwave communication suffers from severe signal attenuation over long distances, and free-space path loss typically limits its effective communication distance to within 50km. Furthermore, the channel is highly dynamic, with complex and variable marine atmospheric environments causing significant fluctuations in channel parameters. The diverse Quality of Service (QoS) requirements across multiple services, including control commands, video surveillance, and sensor data, make it difficult for traditional routing protocols to achieve coordinated optimization of multi-dimensional QoS objectives.

[0003] Evaporated waveguides are a special atmospheric refraction phenomenon formed in the air-sea boundary layer due to evaporation. By altering the vertical distribution of the refractive index of the atmosphere near the sea surface, they can confine electromagnetic waves within the waveguide layer, enabling beyond-line-of-sight propagation and significantly increasing communication distance. Wireless ad hoc networks, with their decentralized, self-organizing, and multi-hop relay characteristics, have become an ideal solution for constructing dynamic maritime communication networks. However, existing typical routing protocols do not fully consider the time-varying characteristics of evaporated waveguides and the differentiated quality-of-service requirements of maritime operations, leading to problems such as conservative routing decisions, excessive network overhead, and insufficient quality-of-service guarantees. Summary of the Invention

[0004] In view of the aforementioned existing problems, this invention is proposed. Therefore, this invention provides an adaptive wireless ad hoc network QoS routing method and apparatus based on the marine evaporative waveguide effect to solve the problems of severe signal attenuation, strong channel time-varying characteristics, and insufficient service quality assurance in traditional maritime microwave communication under long-distance, high-dynamic, and multi-service scenarios.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide an adaptive wireless ad hoc network QoS routing method based on the marine evaporating waveguide effect, comprising: constructing a path loss model based on the propagation characteristics of the marine evaporating waveguide, wherein the path loss model is the path loss obtained by subtracting the waveguide factor from the free space path loss; A uniform linear array antenna is deployed at each network node. The array factor is calculated by generating the azimuth angle of the next hop node of the target through array beamforming. A directional beam with the main lobe pointing in that direction is generated, and the side lobes are controlled within the minimum gain limit to obtain the pointing gain of the corresponding link. The network is divided into multiple logical clusters, each containing a cluster head and several member nodes. The cluster head is dynamically elected based on the remaining energy of the nodes and the communication distance. Member nodes only communicate with their respective cluster heads. The cluster heads form a backbone routing subnet. The backbone routing subnet uses path loss as link weight and calculates the shortest path loss between any two cluster heads. Its maximum value is defined as the network diameter, and the maximum path loss and communication distance upper limit are evaluated. The system receives business data streams and prioritizes them according to business type. For each type of business, it filters feasible paths that meet the constraints, sorts the feasible paths based on the normalized comprehensive cost function, and selects the path with the lowest cost for data forwarding.

[0006] As a preferred embodiment of the adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect described in this invention, the path loss model is obtained by subtracting the waveguide factor from the free space path loss, wherein the free space path loss is expressed as: in, For frequency, Communication distance; The waveguide factor is expressed as: in, For waveguide height, This is the frequency correction factor.

[0007] As a preferred embodiment of the adaptive wireless ad hoc network QoS routing method based on the marine evaporative waveguide effect described in this invention, the method includes: deploying uniform linear array antennas at each network node; calculating the array factor by generating the directional angle of the target next-hop node through array beamforming; generating a directional beam with the main lobe pointing in that direction; and controlling the side lobes within the minimum gain limit to obtain the pointing gain of the corresponding link. This includes: the number of elements in the uniform linear array antenna is... The element spacing is half a wavelength. ; The array factor is expressed as: in, The incident wave azimuth angle; The beamwidth of the main lobe decreases as the number of antenna array elements increases. In response to the increase in the number of array elements, the main lobe becomes narrower and the energy is concentrated in the direction of the target. Conversely, the smaller the number of array elements, the wider the beam and the worse the directivity.

[0008] As a preferred embodiment of the adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect described in this invention, it further includes: The main lobe gain is expressed as: in, Main lobe direction; Sidelobe gain is expressed as: .

[0009] As a preferred embodiment of the adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect described in this invention, the cluster head is dynamically elected based on the node's remaining energy and communication distance, including: the cluster head election is based on a priority calculation of the dual indicators of node's remaining energy and communication distance, and the priority formula is: in, For energy weighting, For nodes Remaining energy For maximum energy, For nodes Average distance to neighboring nodes; The optimal cluster head ratio is obtained by minimizing the total cost: in, This represents the total number of nodes.

[0010] As a preferred embodiment of the adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect described in this invention, the backbone routing subnet uses path loss as link weight and calculates the shortest path loss between any two cluster heads, defining its maximum value as the network diameter. The evaluation of the maximum path loss and the upper limit of communication distance includes: defining a distance matrix. ,in Represents a node To the node The shortest path loss; If node With nodes If directly connected, then ;like ,but ,otherwise, ; The core formula for iteratively updating the distance matrix is: in, As an intermediate node; The network diameter D is defined as: .

[0011] As a preferred embodiment of the adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect described in this invention, the method includes: receiving service data streams and classifying service priorities according to service types; selecting feasible paths that meet the constraints for each type of service; sorting feasible paths based on a normalized comprehensive cost function; and selecting the path with the lowest cost for data forwarding. The service types include control services with a first priority, video services with a second priority, and data services with a third priority. Set latency, bandwidth, and reliability constraints for the corresponding services, and exclude paths that do not meet the service quality requirements; calculate the routing weights for feasible paths that meet the constraints. The path to the minimum value is selected, which is represented as: in, , , These are path loss, latency, and bandwidth, respectively. , , These represent the maximum allowable path loss, the maximum acceptable latency, and the upper limit of bandwidth requirements, respectively. These are the weighting coefficients corresponding to path loss, latency, and bandwidth, respectively. .

[0012] Secondly, the present invention provides an adaptive wireless ad hoc network QoS routing system based on the marine evaporation waveguide effect, comprising: The link modeling module is used to construct a path loss model based on the propagation characteristics of ocean evaporation waveguides. The path loss model is obtained by subtracting the waveguide factor from the free space path loss. The smart antenna control module is used to deploy uniform linear array antennas at each network node, calculate the array factor by generating the azimuth angle of the next hop node of the target through array beamforming, generate a directional beam with the main lobe pointing in that direction, and control the side lobes within the minimum gain limit to obtain the pointing gain of the corresponding link. The cluster management module is used to divide the network into multiple logical clusters. Each cluster contains a cluster head and several member nodes. The cluster head is dynamically elected based on the remaining energy of the node and the communication distance. Member nodes only communicate with their respective cluster heads. The cluster heads form a backbone routing subnet. The diameter estimation module is used to calculate the shortest path loss between any two cluster heads in the backbone routing subnet, using path loss as the link weight, and defining its maximum value as the network diameter, and to evaluate the maximum path loss and the upper limit of communication distance. The business service quality decision module is used to receive business data streams and prioritize business according to business type. For each type of business, it filters feasible paths that meet the constraints, sorts feasible paths based on a normalized comprehensive cost function, and selects the path with the lowest cost for data forwarding.

[0013] Thirdly, the present invention provides an electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the adaptive wireless ad hoc network QoS routing method based on the ocean evaporation waveguide effect.

[0014] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the adaptive wireless ad hoc network QoS routing method based on the ocean evaporation waveguide effect.

[0015] Compared with the prior art, the beneficial effects of the present invention are: the present invention can achieve more accurate link reachability assessment, lower control overhead, faster route convergence and differentiated quality of service guarantee for multiple types of services in the marine evaporative waveguide environment, and maintain stable and reliable self-organizing network service capabilities in long-distance, high-density and time-varying marine communication scenarios. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a schematic diagram of the method flow of an adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect according to an embodiment of the present invention; Figure 2 This is a diagram of the ad hoc network topology in an marine evaporating waveguide environment, illustrating an adaptive wireless ad hoc network QoS routing method based on marine evaporating waveguide effect according to an embodiment of the present invention. Figure 3This is a schematic diagram showing the comparison of network convergence time versus node density for different protocols of an adaptive wireless ad hoc network QoS routing method based on marine evaporation waveguide effect according to an embodiment of the present invention. Figure 4 This is a schematic diagram showing the comparison of packet delivery rate versus communication distance for different protocols in an adaptive wireless ad hoc network QoS routing method based on marine evaporative waveguide effect, as described in an embodiment of the present invention. Figure 5 This is a schematic diagram of the packet arrival rate comparison curves in a scenario where the variable is the number of nodes and the node speed is 15m / s, according to an embodiment of the present invention, of an adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect. Figure 6 This is a schematic diagram of the end-to-end delay comparison curves in a scenario where the variable is the number of nodes and the node speed is 15m / s, according to an embodiment of the present invention, of an adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect. Figure 7 This is a schematic diagram of network throughput comparison curves in a scenario where the variable is the number of nodes and the node speed is 15m / s, according to an embodiment of the present invention, for an adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect. Figure 8 This is a schematic diagram of the normalized routing overhead comparison curves in a scenario where the variable is the number of nodes and the node speed is 15m / s, according to an embodiment of the adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect of the present invention. Detailed Implementation

[0017] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0018] Example 1, referring to Figure 1 As one embodiment of the present invention, this embodiment provides an adaptive wireless ad hoc network QoS routing method based on the ocean evaporation waveguide effect, comprising: S100: Based on the propagation characteristics of ocean evaporation waveguides, a path loss model is constructed. The path loss model is obtained by subtracting the waveguide factor from the free space path loss. S200: Deploy uniform linear array antennas at each network node, calculate the array factor by generating the azimuth angle of the next hop node of the target through array beamforming, generate a directional beam with the main lobe pointing in that direction, and control the side lobes within the minimum gain limit to obtain the directional gain of the corresponding link. S300: The network is divided into multiple logical clusters. Each cluster contains a cluster head and several member nodes. The cluster head is dynamically elected based on the remaining energy of the nodes and the communication distance. Member nodes only communicate with their respective cluster heads. The cluster heads form a backbone routing subnet. S400: The backbone routing subnet uses path loss as the link weight and calculates the shortest path loss between any two cluster heads. Its maximum value is defined as the network diameter, and the maximum path loss and communication distance limit are evaluated. S500: Receives service data streams and prioritizes services according to service type. For each service type, it filters feasible paths that meet the constraints, sorts the feasible paths based on the normalized comprehensive cost function, and selects the path with the lowest cost for data forwarding.

[0019] It should be noted that existing typical routing protocols such as AODV, DSR, and OLSR do not fully consider the time-varying characteristics of evaporative waveguides and the differentiated quality of service requirements of maritime services, resulting in problems such as conservative routing decisions, excessive network overhead, and insufficient quality of service guarantees. To address the challenges of fast signal fading, link time-varying characteristics, and multipath interference in marine evaporative waveguide environments, this invention presents a reliable beyond-line-of-sight wireless communication solution applicable to harsh marine environments. By introducing an evaporating waveguide-corrected path loss model, the impact of evaporating waveguide effects on signal transmission is accurately quantified, significantly improving the link quality assessment accuracy for long-distance communication compared to traditional free-space path loss models. Through array factor adjustment and beam pointing control, directional communication is achieved, reducing sidelobe interference and improving link quality and network reliability, particularly adapting to the complex propagation characteristics of marine environments. A cluster-based routing architecture and dynamic cluster head election mechanism reduce control message overhead while ensuring efficient network operation. By using the Floyd-Warshall algorithm to estimate the network diameter, the system can assess network connectivity and the upper limit of path loss, ensuring network stability in time-varying marine environments and avoiding latency issues caused by selecting excessively long paths. The proposed QoS routing decision mechanism can provide differentiated service quality assurance based on different service requirements, such as control commands, video surveillance, and data transmission, supporting multi-dimensional constraints such as latency, bandwidth, and packet loss rate, ensuring the priority of different service types and the rational allocation of network resources.

[0020] Furthermore, in this embodiment of the invention, the physical phenomenon that evaporation waveguides cause signals to propagate beyond the line of sight and reduce path loss is utilized to construct a path loss model that includes waveguide factors. This model is used to correct the received power estimation in the evaporation waveguide environment and improve the accuracy of link quality assessment.

[0021] In this embodiment of the invention, the path loss model in step S100 is the free space path loss minus the waveguide factor, resulting in the path loss. The free space path loss is expressed as: in, For frequency, Communication distance; Waveguide factor, expressed as: in, For waveguide height, This is the frequency correction factor.

[0022] Furthermore, when the frequency is between 3GHz and 6GHz, .

[0023] Specifically, the final path loss PL is expressed as: .

[0024] In this embodiment of the invention, step S200 involves deploying a uniform linear array antenna at each network node, calculating the array factor by generating the azimuth angle of the target next-hop node through array beamforming, generating a directional beam with the main lobe pointing in that direction, and controlling the side lobes within the minimum gain limit to obtain the pointing gain of the corresponding link. This includes: the number of elements in the uniform linear array antenna is... The element spacing is half a wavelength. ; The array factor is expressed as: in, The incident wave azimuth angle; The beamwidth of the main lobe decreases as the number of antenna array elements increases. In response to the increase in the number of array elements, the main lobe becomes narrower and the energy is concentrated in the direction of the target. Conversely, the smaller the number of array elements, the wider the beam and the worse the directivity.

[0025] Furthermore, the beamwidth is used to describe the range of energy concentration on the main lobe, and its approximate expression is: .

[0026] In this embodiment of the invention, step S200 further includes: The main lobe gain is expressed as: in, Main lobe direction; Sidelobe gain is expressed as: .

[0027] It should be noted that, in this embodiment of the invention, the minimum gain limit of the sidelobe can be set to -40dB to prevent noise interference.

[0028] In this embodiment of the invention, step S200 can also design the radiation pattern of the smart antenna using a planar array, and it supports symmetrical / asymmetrical beamforming and sidelobe threshold constraints for array beamforming and pointing gain estimation.

[0029] In this embodiment of the invention, step S300 involves the dynamic election of cluster heads based on the remaining energy of nodes and communication distance, including: cluster head election is based on a priority calculation using two indicators: remaining energy of nodes and communication distance. The priority formula is as follows: in, For energy weighting, For nodes Remaining energy For maximum energy, For nodes Average distance to neighboring nodes; It should be noted that the energy weight should be higher than the distance weight to avoid the re-election overhead caused by frequent cluster head failures. In this embodiment of the invention, the energy weight... It can be set to 0.7.

[0030] Furthermore, the optimal cluster head ratio is obtained by minimizing the total cost: in, This represents the total number of nodes.

[0031] It should be noted that the embodiments of the present invention adopt a cluster-based routing architecture, which divides the network into multiple logical clusters. Each cluster contains a cluster head and multiple zero-member nodes. The cluster head is responsible for data aggregation, scheduling and inter-cluster routing forwarding within the cluster, while the member nodes only communicate with the cluster head to reduce global routing overhead.

[0032] In this embodiment of the invention, in step S400, the backbone routing subnet uses path loss as link weight and calculates the shortest path loss between any two cluster heads, defining its maximum value as the network diameter. The evaluation of the maximum path loss and the upper limit of communication distance includes: defining a distance matrix. ,in Represents a node To the node The shortest path loss; If node With nodes Direct connection, i.e. dBm, then ;like ,but ,otherwise, ; The core formula for iteratively updating the distance matrix is: in, As an intermediate node; The network diameter D is defined as: .

[0033] It should be noted that the network diameter D can be used to evaluate the maximum path loss and the upper limit of communication distance.

[0034] In one feasible approach, the Floyd-Warshall algorithm can be used to calculate the shortest path loss between any two nodes in order to estimate the network diameter.

[0035] In this embodiment of the invention, step S500 involves receiving a service data stream and prioritizing services according to service type. For each type of service, feasible paths that meet the constraints are selected. The feasible paths are sorted based on a normalized comprehensive cost function, and the path with the lowest cost is selected for data forwarding. The service types include control services with first priority, video services with second priority, and data services with third priority. Set latency, bandwidth, and reliability constraints for the corresponding services, and exclude paths that do not meet the service quality requirements; calculate the routing weights for feasible paths that meet the constraints. The path to the minimum value is selected, which is represented as: in, , , These are path loss, latency, and bandwidth, respectively. , , These represent the maximum allowable path loss, the maximum acceptable latency, and the upper limit of bandwidth requirements, respectively. These are the weighting coefficients corresponding to path loss, latency, and bandwidth, respectively. .

[0036] It should be noted that, in this embodiment of the invention, the maximum allowable path loss, the maximum acceptable latency, and the upper limit of bandwidth requirement can be set as follows: 150dB ms Mbps.

[0037] Furthermore, in this embodiment of the invention, the path with the least weight is selected as the optimal path, and smart antenna beamforming technology is combined for directional communication to improve link quality and spatial reuse rate.

[0038] It should be noted that the embodiments of this invention establish an evaporating waveguide path loss model, including calculating free space loss and waveguide factor, to obtain the final path loss; further, a smart antenna radiation pattern is designed, and a uniform linear array is used to calculate the array factor, beamwidth, and gain to achieve directional communication; an EG-AQR routing protocol is constructed, including cluster-based architecture design, cluster head election, and derivation of the optimal cluster head ratio; the Floyd-Warshall algorithm is used to calculate the shortest path loss for network diameter estimation; and path selection is achieved through constraint filtering and weight optimization to realize multi-service priority scheduling. The EG-AQR algorithm proposed in this invention, by introducing an evaporating waveguide-corrected path loss model, smart antenna technology, and cluster-based routing architecture, can improve the communication quality and service quality assurance of the network in complex marine environments. The routing decision mechanism for selecting the optimal path combines service priority and multi-dimensional QoS constraints to optimize path selection and bandwidth allocation, thereby reducing link latency and packet loss rate while maintaining high network throughput.

[0039] Example 2: The above example is an illustrative scheme of an adaptive wireless ad hoc network QoS routing method based on the ocean evaporation waveguide effect. It should be noted that the technical solution of this adaptive wireless ad hoc network QoS routing system based on the ocean evaporation waveguide effect belongs to the same concept as the technical solution of the aforementioned adaptive wireless ad hoc network QoS routing method based on the ocean evaporation waveguide effect. Details not described in detail in this example of the adaptive wireless ad hoc network QoS routing system based on the ocean evaporation waveguide effect can be found in the description of the aforementioned adaptive wireless ad hoc network QoS routing method based on the ocean evaporation waveguide effect.

[0040] This embodiment presents an adaptive wireless ad hoc network QoS routing system based on the marine evaporation waveguide effect, comprising: The link modeling module is used to construct a path loss model based on the propagation characteristics of ocean evaporation waveguides. The path loss model is obtained by subtracting the waveguide factor from the free space path loss. The smart antenna control module is used to deploy uniform linear array antennas at each network node, calculate the array factor by generating the azimuth angle of the next hop node of the target through array beamforming, generate a directional beam with the main lobe pointing in that direction, and control the side lobes within the minimum gain limit to obtain the pointing gain of the corresponding link. The cluster management module is used to divide the network into multiple logical clusters. Each cluster contains a cluster head and several member nodes. The cluster head is dynamically elected based on the node's remaining energy and communication distance. Member nodes only communicate with their respective cluster heads. The cluster heads form a backbone routing subnet. The diameter estimation module is used to calculate the shortest path loss between any two cluster heads in the backbone routing subnet, using path loss as the link weight. The maximum value of this shortest path loss is defined as the network diameter, and the maximum path loss and communication distance limit are evaluated. The business service quality decision module is used to receive business data streams and prioritize business according to business type. For each type of business, it filters feasible paths that meet the constraints, sorts feasible paths based on a normalized comprehensive cost function, and selects the path with the lowest cost for data forwarding.

[0041] Furthermore, it includes a route discovery module; this module is responsible for path selection and routing information forwarding between cluster heads. This module uses an improved RREQ protocol for path discovery, broadcasting routing information from cluster heads to find the optimal path. During path selection, it assesses link quality based on the path loss corrected by evaporating waveguides, ensuring that the selected path is not only the shortest but also meets QoS constraints such as latency, bandwidth, and packet loss rate. Through this path selection strategy, the network can avoid unstable or unreliable links, improving communication success rate and efficiency.

[0042] Specifically, the main task of the link modeling module is to establish a path loss model in an evaporating waveguide environment. This module calculates path loss by acquiring parameters of the air-sea boundary layer, such as the height of the evaporating waveguide and the refractive index gradient, and corrects the traditional free-space loss model, thus forming a link quality assessment model with ocean waveguide characteristics. Using this model, the system can accurately assess signal attenuation in an evaporating waveguide environment, especially in long-distance and beyond-line-of-sight propagation scenarios, effectively improving the accuracy of link quality assessment and supporting subsequent path selection and signal transmission decisions.

[0043] Specifically, the smart antenna control module is responsible for optimizing the signal propagation direction and reducing sidelobe interference. The system employs a uniform linear array or planar array antenna, utilizing array factors to control the main lobe's direction towards the next hop, and employing beamforming technology to improve the link's signal-to-noise ratio. The array factors control the direction of signal energy propagation, concentrating it in the target direction, thus avoiding energy waste and multipath interference. Through directional communication and interference suppression, the system effectively improves signal quality and network reliability in waveguide environments. Especially in marine environments, this directional communication capability of the antenna is more adapted to waveguide characteristics, thereby improving communication stability and reliability.

[0044] Specifically, the cluster management module is responsible for dynamically adjusting the cluster head ratio based on network needs, and for forming clusters and electing cluster heads. Cluster head election is based on the remaining energy and communication distance of nodes, prioritizing nodes with sufficient energy and good link quality as cluster heads. By setting a priority function, it ensures that the selection of cluster heads optimizes the network topology and guarantees the stability and availability of nodes within the cluster. Setting the cluster head ratio balances intra-cluster and inter-cluster overhead, ensuring efficient network operation and topology optimization, thereby improving network scalability and stability.

[0045] Furthermore, the cluster management module supports adaptive adjustment of the cluster head ratio within the range of 15%–30%, which is used for cluster formation, cluster maintenance, and cluster head priority calculation.

[0046] Specifically, the diameter estimation module uses the Floyd-Warshall algorithm to estimate the network's maximum path loss, which is the network's diameter. By calculating the shortest path between all nodes, the diameter module can assess the network's maximum communication latency, ensuring that excessively long or unstable paths are not selected. This module optimizes network connectivity and reduces potential latency and network congestion issues through weighted calculations of communication paths between cluster heads.

[0047] Specifically, the service quality decision module filters and selects paths based on the latency, bandwidth, packet loss rate, and other requirements of different services. This module first constrains and filters paths according to service requirements; for example, control services may have strict latency requirements, while video services may require higher bandwidth. Then, the module performs weighted optimization based on the QoS performance of different paths, selecting the optimal path that meets multi-dimensional QoS requirements. Through this decision-making mechanism, the system can provide differentiated service guarantees for different types of services, ensuring low latency and high reliability for high-priority services while guaranteeing bandwidth and throughput for low-priority services.

[0048] It should be noted that the functional modules in this embodiment are implemented in software, facilitating parameter adjustment and algorithm optimization, and enabling flexible adaptation to different application scenarios and changing requirements. Due to its modular design, the system can dynamically adjust the configuration and performance of each module according to changes in the actual environment, thus providing greater flexibility and scalability. Especially in marine evaporative waveguide environments, due to the time-varying characteristics of this environment, the system can dynamically correct path loss, signal interference, and other factors in real time, ensuring link stability and communication reliability. Furthermore, by integrating an evaporative waveguide path loss correction model with smart antenna beamforming technology, this device can optimize signal propagation in long-distance, high-density, and complex marine environments, reducing interference and improving data transmission rates and system throughput. The design of this device not only improves the efficiency of routing decisions but also ensures efficient network operation without increasing hardware overhead. The decoding device also improves overall network performance through cross-layer optimization, combining physical layer channel information and network layer routing strategies, especially providing accurate QoS guarantees during multi-service transmission. Adaptive path selection and link recovery mechanisms effectively reduce network latency and packet loss rates, exhibiting excellent robustness in complex dynamic environments.

[0049] This embodiment also provides an electronic device applicable to the adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect, including: The system includes a memory and a processor. The memory stores computer-executable instructions, and the processor executes these instructions to implement the adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect proposed in the above embodiments.

[0050] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the adaptive wireless ad hoc network QoS routing method based on the ocean evaporation waveguide effect as proposed in the above embodiments.

[0051] The storage medium proposed in this embodiment and the adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0052] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0053] Example 3, referring to Figures 2-8 This is one embodiment of the present invention. Unlike the first embodiment, this embodiment verifies the effectiveness of the method of the present invention by conducting simulation comparison on the NS3 platform and constructing a comparative experiment.

[0054] Figure 3 Among them, the convergence time of EG-AQR increases the most gradually, and the convergence time is still controlled within 7 seconds when the node density reaches 50; while the convergence time of the baseline protocol, AODV, DSR and OLSR increase rapidly with the increase of node density. For example, the convergence time of the baseline protocol and DSR exceeds 10 seconds at high density.

[0055] This embodiment specifically utilizes evaporating waveguide channels, enabling EG-AQR to prioritize beyond-line-of-sight links supported by evaporating waveguides during routing decisions. This avoids the excessive hop count and cumulative loss problems associated with traditional multi-hop routing. Because traditional protocols do not consider special ocean channels and assume line-of-sight multi-hop by default, delivery rates drop sharply over long distances. Figure 4 As shown, the delivery rate of EG-AQR remains above 65% over long distances (such as 150km), which is superior to traditional AODV, DSR, OLSR and baseline protocols.

[0056] This embodiment of EG-AQR's cluster-based architecture, combined with the beyond-line-of-sight characteristics of evaporative waveguides, reduces routing hop count and link interruption probability. Long-distance links between cluster heads are more stable, and the association between nodes within a cluster and the cluster head is more reliable due to the QoS mechanism. Traditional protocols, on the other hand, suffer from hop-by-hop instability, such as OLSR link awareness lag and the inability of DSR source routing to dynamically adapt, leading to increased packet loss rates. Figure 5 As shown, the packet arrival rate of EG-AQR can always maintain a high level, that is, it can still maintain more than 75% when the number of nodes reaches 200, while the arrival rates of OLSR and DSR drop sharply with the increase of the number of nodes, and AODV also shows a significant decline.

[0057] In this embodiment, cluster heads communicate directly via evaporative waveguide beyond-line-of-sight links, reducing forwarding and processing delays at intermediate nodes. In contrast, the route discovery delay of AODV, the topology maintenance delay of OLSR, and the source route encapsulation delay of DSR increase exponentially with the number of nodes. Figure 6 It can be seen that the end-to-end latency of EG-AQR is much lower than that of OLSR, DSR and AODV.

[0058] In this embodiment, the cluster head's QoS-aware scheduling dynamically allocates intra-cluster / inter-cluster bandwidth, avoiding bandwidth waste caused by link contention. Evaporated waveguide beyond-line-of-sight transmission reduces multi-hop contention (single-hop coverage extends further, reducing packet retransmission probability) and improves effective bandwidth utilization. In contrast, traditional protocols like AODV and DSR's on-demand routing consume significant bandwidth due to frequent route discovery; OLSR's periodic control messages also consume effective transmission resources, thus limiting throughput improvement. Figure 7 It can be seen that the throughput of EG-AQR continues to increase with the number of nodes and is consistently higher than that of other comparative protocols.

[0059] The cluster-based routing architecture of EG-AQR is as follows: Figure 2 As shown, centralized processing of inter-cluster routing by the cluster head avoids the redundant control overhead of OLSR's periodic global topology flooding and AODV's on-demand route discovery; the over-the-line link of the marine evaporation waveguide shortens the transmission hop count, directly reducing the relay overhead of data forwarding. Traditional multi-hop routing requires more nodes, amplifying both control and data overhead. Figure 8 It can be seen that the normalized routing cost of EG-AQR is significantly lower than that of AODV, OLSR, and DSR, and the growth trend is more gradual with the increase of the number of nodes. The core reason is: In summary, this invention proposes a multi-mode quality of service cluster-based routing algorithm EG-AQR in the context of marine evaporative waveguide communication. Through theoretical analysis, protocol design, and simulation verification, it is demonstrated that the algorithm has better performance than traditional protocols.

[0060] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect, characterized in that, include: Based on the propagation characteristics of marine evaporative waveguides, a path loss model is constructed. The path loss model is obtained by subtracting the waveguide factor from the free space path loss. A uniform linear array antenna is deployed at each network node. The array factor is calculated by generating the azimuth angle of the next hop node of the target through array beamforming. A directional beam with the main lobe pointing in that direction is generated, and the side lobes are controlled within the minimum gain limit to obtain the pointing gain of the corresponding link. The network is divided into multiple logical clusters, each containing a cluster head and several member nodes. The cluster head is dynamically elected based on the remaining energy of the nodes and the communication distance. Member nodes only communicate with their respective cluster heads. The cluster heads form a backbone routing subnet. The backbone routing subnet uses path loss as link weight and calculates the shortest path loss between any two cluster heads. Its maximum value is defined as the network diameter, and the maximum path loss and communication distance upper limit are evaluated. The system receives business data streams and prioritizes them according to business type. For each type of business, it filters feasible paths that meet the constraints, sorts the feasible paths based on the normalized comprehensive cost function, and selects the path with the lowest cost for data forwarding.

2. The adaptive wireless ad hoc network QoS routing method based on marine evaporative waveguide effect as described in claim 1, characterized in that, The path loss model is obtained by subtracting the waveguide factor from the free-space path loss, whereby the free-space path loss is expressed as: in, For frequency, Communication distance; The waveguide factor is expressed as: in, For waveguide height, This is the frequency correction factor.

3. The adaptive wireless ad hoc network QoS routing method based on marine evaporation waveguide effect as described in claim 2, characterized in that, A uniform linear array antenna is deployed at each network node. The array factor is calculated by generating the azimuth angle of the next-hop node using array beamforming. A directional beam with the main lobe pointing in that direction is generated, and the side lobes are controlled within the minimum gain limit to obtain the pointing gain of the corresponding link. This includes: the number of elements in the uniform linear array antenna is... The element spacing is half a wavelength. ; The array factor is expressed as: in, The incident wave azimuth angle; The beamwidth of the main lobe decreases as the number of antenna array elements increases. In response to the increase in the number of array elements, the main lobe becomes narrower and the energy is concentrated in the direction of the target. Conversely, the smaller the number of array elements, the wider the beam and the worse the directivity.

4. The adaptive wireless ad hoc network QoS routing method based on marine evaporation waveguide effect as described in claim 3, characterized in that, Also includes: The main lobe gain is expressed as: in, Main lobe direction; Sidelobe gain is expressed as: 。 5. The adaptive wireless ad hoc network QoS routing method based on marine evaporation waveguide effect as described in claim 4, characterized in that, Cluster heads are dynamically elected based on the node's remaining energy and communication distance. The election process involves prioritizing both remaining energy and communication distance, using the following formula: in, For energy weighting, For nodes Remaining energy For maximum energy, For nodes Average distance to neighboring nodes; The optimal cluster head ratio is obtained by minimizing the total cost: in, This represents the total number of nodes.

6. The adaptive wireless ad hoc network QoS routing method based on marine evaporation waveguide effect as described in claim 5, characterized in that, The backbone routing subnet uses path loss as link weight and calculates the shortest path loss between any two cluster heads. Its maximum value is defined as the network diameter. The evaluation of the maximum path loss and the upper limit of communication distance includes: defining the distance matrix. ,in Represents a node To the node The shortest path loss; If node With nodes If directly connected, then ;like ,but ,otherwise, ; The core formula for iteratively updating the distance matrix is: in, As an intermediate node; The network diameter D is defined as: 。 7. The adaptive wireless ad hoc network QoS routing method based on marine evaporation waveguide effect as described in claim 6, characterized in that, The system receives business data streams and prioritizes them according to business type. For each type of business, it selects feasible paths that meet the constraints, sorts the feasible paths based on the normalized comprehensive cost function, and selects the path with the lowest cost for data forwarding. The business types include control services with the first priority, video services with the second priority, and data services with the third priority. Set latency, bandwidth, and reliability constraints for the corresponding services, and exclude paths that do not meet the service quality requirements; calculate the routing weights for feasible paths that meet the constraints. The path to the minimum value is selected, which is represented as: in, , , These are path loss, latency, and bandwidth, respectively. , , These represent the maximum allowable path loss, the maximum acceptable latency, and the upper limit of bandwidth requirements, respectively. These are the weighting coefficients corresponding to path loss, latency, and bandwidth, respectively. .

8. An adaptive wireless ad hoc network QoS routing system based on the marine evaporation waveguide effect, applied to the method described in any one of claims 1-7, characterized in that, include: The link modeling module is used to construct a path loss model based on the propagation characteristics of ocean evaporation waveguides. The path loss model is obtained by subtracting the waveguide factor from the free space path loss. The smart antenna control module is used to deploy uniform linear array antennas at each network node, calculate the array factor by generating the azimuth angle of the next hop node of the target through array beamforming, generate a directional beam with the main lobe pointing in that direction, and control the side lobes within the minimum gain limit to obtain the pointing gain of the corresponding link. The cluster management module is used to divide the network into multiple logical clusters. Each cluster contains a cluster head and several member nodes. The cluster head is dynamically elected based on the remaining energy of the node and the communication distance. Member nodes only communicate with their respective cluster heads. The cluster heads form a backbone routing subnet. The diameter estimation module is used to calculate the shortest path loss between any two cluster heads in the backbone routing subnet, using path loss as the link weight, and defining its maximum value as the network diameter, and to evaluate the maximum path loss and the upper limit of communication distance. The business service quality decision module is used to receive business data streams and prioritize business according to business type. For each type of business, it filters feasible paths that meet the constraints, sorts feasible paths based on a normalized comprehensive cost function, and selects the path with the lowest cost for data forwarding.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the adaptive wireless ad hoc network QoS routing method based on the marine evaporation waveguide effect as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the adaptive wireless ad hoc network QoS routing method based on the marine evaporative waveguide effect as described in any one of claims 1 to 7.

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