Underwater optical communication routing method based on three-dimensional dynamic conical sector

Abstract

The invention discloses an underwater optical communication routing method based on a three-dimensional dynamic conical sector, belongs to the technical field of underwater wireless communication, and is used for solving the problems of poor routing stability, low communication success rate, high energy consumption, non-adaptive path and the like in the existing underwater optical communication network. The method comprises the following steps: constructing an underwater optical communication network model in a three-dimensional space, and defining a dynamic cone communication sector based on a divergence angle and a direction angle between nodes; discovering neighbor nodes through a conical scanning mechanism, and performing multi-index optimization on candidate forwarding nodes based on distance progress, expected progress, energy efficiency indexes and time delay indexes; selecting an optimal path according to an evaluation result; performing competition coordination among candidate nodes by using a fast time slot response mechanism, and selecting a next hop node; and completing path construction through hop-by-hop transmission, dynamically adjusting a divergence angle, and executing path maintenance and updating. The method does not need global topological information, and is suitable for an underwater communication scene with uncertain node distribution in a dynamic environment.

Description

Technical Field

[0001] This invention relates to the field of underwater wireless optical communication networks, specifically an underwater optical communication routing method based on three-dimensional dynamic conical sectors, applicable to multi-hop optical communication routing optimization in underwater IoT environments. Background Technology

[0002] With the rapid development of underwater Internet of Things (IoT) in fields such as environmental monitoring, marine science, oil and gas resource exploration, seabed earthquake early warning, and military reconnaissance, building an efficient and stable data communication network has become a crucial foundation. Traditional underwater communication mainly relies on acoustic communication, which has a wide coverage area but low bandwidth, large propagation delay, and high energy consumption. Furthermore, it is susceptible to multipath interference in shallow water and complex environments, making it difficult to meet the demands of large-scale, low-latency data transmission. In contrast, underwater wireless optical communication, with its advantages of high bandwidth, high speed, low latency, and strong anti-interference capabilities, has become an important direction for the future development of underwater communication. However, due to the susceptibility of light to absorption and scattering in water, the effective communication distance of underwater wireless optical communication is typically only a few meters to tens of meters, and it requires extremely high precision in the relative position and alignment between nodes.

[0003] The irregularity and dynamic changes of the underwater environment further exacerbate the uncertainty of communication paths. Existing routing protocols are mostly based on fixed topologies and shortest path strategies, ignoring the directional and divergent characteristics of beams in underwater optical communication. They cannot dynamically optimize beam divergence and deflection angles, leading to unstable link quality, high energy consumption, and low data transmission success rates. Furthermore, some routing methods based on acoustic network design fail to fully adapt to the physical channel characteristics of underwater wireless optical communication. Therefore, there is an urgent need to propose an innovative routing scheme that combines physical layer modeling, spatial constraint awareness, and opportunistic routing mechanisms to improve the energy efficiency and adaptability of the entire network while ensuring communication quality. Summary of the Invention

[0004] In view of the shortcomings of existing underwater wireless optical communication systems in terms of routing efficiency, path stability and energy consumption control, this invention aims to provide an underwater optical communication routing method based on three-dimensional dynamic conical sectors to improve the success rate, energy efficiency and latency performance of data transmission in underwater networks and adapt to complex and ever-changing underwater environments.

[0005] This invention provides an underwater optical communication routing method based on three-dimensional dynamic conical sectors, comprising the following steps:

[0006] A three-dimensional underwater optical communication network model is constructed. The network model consists of multiple nodes that support directional optical communication. Each node includes a directional optical module for transmitting and receiving optical signals. The optical signals form a conical sector through defined divergence angles and azimuth angles.

[0007] Based on the node position relationships, construct a system based on pitch angles. The dynamic scanning area defined by the azimuth angle γ and the divergence angle θ;

[0008] A conical scanning mechanism is used for neighbor node discovery. Nodes periodically change their emission direction and divergence angle to dynamically scan the neighborhood space and identify neighbor nodes within the communication range.

[0009] The distance progress (DP) metric is used to pre-screen candidate nodes, and only nodes that have a positive driving effect in the target direction are retained as valid candidate forwarding nodes.

[0010] The candidate nodes are scored based on a multi-index weighted evaluation function F(j), which includes the following indices: distance progress (DP), expected distance progress (EDP), energy efficiency index (EEM), and low latency index (LLM). By assigning different weights to each index, comprehensive scoring and path selection under different routing objectives are achieved.

[0011] Based on the Fast Time Slot Response (FSA) mechanism, candidate nodes are quickly coordinated according to priority to select the final next-hop forwarding node.

[0012] Before each data hop is forwarded, the neighboring nodes are re-evaluated and a conical scan is performed. The divergence angle θ is adjusted according to the link status to achieve path maintenance and reconstruction, ensuring that routing stability is maintained in a dynamic underwater environment.

[0013] Preferably, the conical scanning area is a three-dimensional spatial region with the node itself as the vertex, the divergence angle θ as the opening, and the direction angle ψ as the main axis. During the scanning process, the node periodically changes the combination of ψ and θ to expand the coverage area.

[0014] Preferably, the successful establishment of the communication route simultaneously satisfies the following conditions: the receiving node is located within the conical sector of the transmitting node; the distance between nodes is less than the maximum communication distance; and the link channel loss is lower than the receiving threshold.

[0015] Preferably, the distance progress (DP) calculation method is as follows:

[0016] DP ij =||n i -n d ||-||n j -n d ||

[0017] Where, n i and n j These represent the positions of the current node and the candidate node, respectively, n. d The target node location.

[0018] Preferably, the energy efficiency index (EEM) is calculated from the average energy consumption per unit bit of data across multiple transmission attempts.

[0019] Preferably, the Low Latency Metric (LLM) is defined as the total latency generated by a node performing n transmission attempts, taking into account the cumulative transmission and coordination time.

[0020] Preferably, the multi-index weighted evaluation function F(j) is:

[0021] F(j)=ω1·DP(j)+ω2·EDP(j)-ω3·EEM(j)-ω4·LLM(j)

[0022] Among them, ω1, ω2, ω3, and ω4 are adjustable weight coefficients that can be flexibly configured according to network requirements.

[0023] Preferably, the steps of the Fast Time Slot Response (FSA) mechanism include: candidate nodes determining their priorities according to their index scores; starting to listen to the channel after a unique offset time delay based on the priority; immediately sending an acknowledgment frame (ACK) if the channel is idle; and automatically withdrawing from the competition if the channel is occupied, assuming that a higher priority node has responded.

[0024] Preferably, when a node fails to forward a message or fails to find a candidate node, it dynamically increases the divergence angle θ to improve coverage. The adjustment strategy is as follows:

[0025] θ new =θ old +δ

[0026] Where δ is the angle step size.

[0027] Preferably, the method can be deployed in hardware devices, embedded systems, or software platforms, and the algorithms and control logic used can be executed through program instructions.

[0028] Compared with the prior art, the present invention has the following technical features: dynamically adjusting the divergence angle and direction angle to achieve 360° neighbor discovery and efficient path selection; each hop is based only on local neighborhood information, without the need for global topology information to complete the routing decision, significantly reducing control overhead; and the optimization target can be flexibly selected under different network conditions.

[0029] To ensure routing quality and system adaptability, the routing mechanism in this invention employs the following specific control strategies:

[0030] Candidate Filtering: To improve the directionality and effectiveness of forwarding paths, this invention employs a candidate node pre-screening mechanism based on the forward distance progress (DP) metric. For any current node n... i Only neighboring nodes n within its forward propagation sector (i.e., those pointing towards the target node) that have a positive propagation effect are considered.j This eliminates nodes that could cause path rollback or relay redundancy.

[0031] Candidate Selection: To select the optimal forwarding path from the selected candidate nodes, this invention introduces an adaptive scanning strategy based on divergence and orientation angles. Nodes emit conical beams with different scanning directions ψ=(φ,γ) and divergence angles θ to dynamically cover the neighborhood space, and the fitness values ​​of the candidate set are calculated under different parameter combinations.

[0032] Candidate Coordination: To prevent channel collisions caused by multiple candidate nodes responding simultaneously, this invention introduces a Fast Response (FSA) mechanism based on index ranking. Each candidate node determines a unique priority identifier ρ based on its index score, which is embedded in the routing response packet.

[0033] Path maintenance: To adapt to potential location drift, equipment failure, or channel changes in underwater nodes, this invention employs a hop-by-hop construction and update mechanism, eliminating the need for global path maintenance. Each node dynamically triggers a conical scan process before sending data packets and reassesses the current neighborhood structure and indicator distribution. If environmental changes result in no effective forwarding nodes in the original candidate set, the divergence angle θ is automatically adjusted to improve coverage; if no candidate nodes are still found, a backoff and path recovery mechanism is implemented.

[0034] The present invention has the following beneficial effects:

[0035] (1) Improved communication success rate: This invention introduces a three-dimensional dynamic conical scanning mechanism, enabling nodes to flexibly adjust their transmission direction and sector coverage in space. This allows for omnidirectional and refined searching and identification of neighboring nodes, effectively avoiding the neighbor blind spot problem caused by angle limitations in traditional directional communication. Simultaneously, by combining multi-dimensional indicators such as distance progress (DP) and expected progress (EDP) for candidate node optimization, link quality and routing potential are comprehensively evaluated from multiple perspectives, improving packet transmission success rate and reliability in a dynamic environment.

[0036] (2) Energy consumption control optimization: Considering that underwater communication nodes usually rely on battery power, energy consumption control becomes a key indicator. This invention introduces the energy efficiency index EEM in the routing decision process, incorporating the energy consumed per unit bit transmission during each hop forwarding into the forwarding node selection function, prompting the system to prioritize the path with high energy cost-effectiveness, effectively reducing the energy consumption of node communication;

[0037] (3) Delay Control: For delay-sensitive underwater applications, this invention introduces the Low Latency Metric (LLM). By measuring and predicting the average delay between the forwarding node and the channel, the path selection order for each hop is dynamically adjusted. Combined with the Fast Time Slot Response (FSA) mechanism, the system can quickly confirm the next hop node, reducing waiting time and effectively lowering the average coordination delay per hop and the overall transmission delay. This mechanism ensures stable network operation in time-sensitive tasks such as emergency response and task data backhaul.

[0038] (4) High adaptability: This invention adopts a fully distributed routing protocol architecture. Each node can complete path discovery and maintenance by relying only on its own locally available neighbor information, without the need for central coordination or global topology synchronization, which greatly improves the system's adaptability to dynamic environmental changes. Combining the Beer-Lambert attenuation model and geometric loss modeling, it can perceive the impact of water quality changes and environmental disturbances on the communication channel in real time, automatically adjust the transmission angle and path direction, realize path adaptive optimization, and ensure the continuous effectiveness of the communication link. It is suitable for actual deployment scenarios with complex marine environmental changes and irregular water structure.

[0039] (5) Easy to deploy and expand: Unlike traditional routing algorithms that rely on fixed topology or centralized control strategies, the conical scanning mechanism of this invention naturally supports the access of heterogeneous nodes and dynamic expansion of network size. New nodes only need to participate in conical neighbor scanning and index negotiation based on their own location information to quickly integrate into the existing communication path; failed nodes can be automatically bypassed through the path reconstruction process, reducing the risk of interference to overall communication.

[0040] In summary, the three-dimensional conical dynamic scanning sector routing method proposed in this invention breaks the limitations of traditional point-to-point communication and provides a feasible system-level technical solution for underwater optical communication networks in terms of large-scale deployment, autonomous collaboration, and efficient data transmission. It has significant theoretical value and engineering application prospects. Attached Figure Description

[0041] Figure 1 : Flowchart of the underwater optical communication routing method of the present invention.

[0042] Figure 2 The present invention describes the relationship between the communication distance and the divergence angle between two adjacent nodes. Detailed Implementation

[0043] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used to better understand the principles and implementation of the present invention, but do not constitute a limitation on the scope of protection of the present invention.

[0044] A specific embodiment of the present invention discloses an underwater optical communication routing method based on dynamic three-dimensional conical sector scanning. This method fully integrates node location information, divergence angle, link quality, and energy efficiency factors to achieve adaptive multi-target routing selection. The overall process of this method is as follows: Figure 1 As shown.

[0045] Step S1: Construct an underwater optical communication network model.

[0046] The model comprises multiple randomly distributed communication nodes, which can be source nodes, sink nodes, or relay nodes. Each node has directional transmission capability, and its optical communication link is defined by a divergence angle θ and a direction angle ψ, forming a conical scanning area. Successful communication depends on whether the nodes are located within each other's divergence sectors and whether the distance between them is less than the maximum communication range r. max This modeling process considers not only geometric relationships but also the propagation loss model of light in water, providing a reliable physical basis for subsequent communication path planning and performance evaluation. It also considers whether the channel loss is below the receiver sensitivity threshold.

[0047] To ensure the model has computational operability and physical consistency, this invention further defines key parameters for each node in the network, including location, communication angle, and channel conditions.

[0048] Step S11: Position Definition: Let the three-dimensional coordinates of node i be P. i =(x i ,y i ,z i The Euclidean distance between nodes is obtained through an acoustic positioning system or an inertial navigation system, and is ||P. i -P j ||.

[0049] Step S12: Communication angle definition: Define the divergence angle θ to control the size of the beam opening in space. The larger the angle, the wider the coverage area and the higher the communication energy consumption. Define the direction angle ψ = (φ, γ) to control the azimuth and elevation direction of the beam, which is used to define the direction of the central axis of the cone.

[0050] Step S13: Channel Definition: According to the Beer-Lambert attenuation model, the exponential attenuation of the optical signal in water due to absorption and scattering is expressed as:

[0051]

[0052] Where, d ij φ represents the distance between node i and node j. ijThe angle between the transmitter and receiver is represented by c(λ) = a(λ) + b(λ). c(λ) represents the total attenuation coefficient at wavelength λ, where a(λ) and b(λ) are the absorption coefficient and scattering coefficient, respectively.

[0053] cosψ ij Represented as

[0054]

[0055] n i Represented as

[0056]

[0057] in, γ is the pitch angle. i It is the azimuth angle.

[0058] In addition to the losses caused by the propagation medium, underwater optical communication also faces geometric divergence loss caused by beam spread, which is expressed as follows:

[0059]

[0060] Where θ represents the divergence angle of the transmitted beam, and A j This indicates the effective photoelectric conversion area at the receiving end.

[0061] Preferably, in this embodiment, combining absorption-scattering loss and geometric loss, the total channel gain between node i and node j is expressed as follows:

[0062] G ij =GL ij BL ij (5)

[0063] Therefore, whether a stable link can be established between nodes depends not only on the spatial orientation relationship but also on the significant influence of the physical channel quality. The construction of this three-dimensional optical communication model provides a theoretical basis for subsequent neighbor scanning, candidate selection, and path maintenance.

[0064] Step S2: Scan neighboring nodes in the sector.

[0065] In this step, this embodiment selects a routing decision mechanism based on local metrics. This mechanism can complete path planning relying only on one-hop neighbor information, without requiring global topology awareness, thus avoiding frequent state updates and complex control information interactions. Specifically, each node actively scans the conical sector in its transmission direction to discover neighboring nodes. Specifically, the node controls its optical transmission module to emit scanning signals at a set divergence angle θ and direction angle ψ, and records the information of nodes that successfully respond within the scan coverage area.

[0066] Preferably, in this embodiment, the conical scanning region can be modeled as a three-dimensional region in space with the node itself as the vertex, the direction vector as the axis, and the divergence angle as the included angle. Define C i n i If the candidate node index set is C, then the candidate set C i (θ i ,ψ i Each element in ) is subject to θ i and ψ i The different sectors are influenced by this. For example Figure 2 As shown, when n i With n j During communication, if ψi = 0, the optical transceivers are perfectly connected; when n i With n′ j During communication, the deflection angle is ψ i If this happens, the optical transceivers will not be perfectly aligned. In practical applications, the nodes will periodically adjust (θ). i ,ψ i A comprehensive scan is performed using a combination of methods to discover as many potential forwarding nodes as possible.

[0067] Step S3: Filter candidate nodes.

[0068] To improve the directionality and effectiveness of forwarding paths, this invention employs a candidate node pre-screening mechanism based on the forward distance progress (DP) metric. For any current node n... i Only neighboring nodes n within its forward propagation sector (i.e., those pointing towards the target node) that have a positive propagation effect are considered. j This eliminates nodes that could cause path rollback or relay redundancy.

[0069] Preferably, in this embodiment, the distance progression is defined as:

[0070] DP ij =||n i -n d ||-||n j -n d || (6)

[0071] Where, n d For the target node location, DP ij >0 indicates that node j has a positive driving force relative to the current node in the target direction.

[0072] The final candidate set is defined as:

[0073] C i ={n j |||n j -n i ||≤d max ,DPij >0} (7)

[0074] This operation can reduce invalid forwarding and improve path advancement and stability.

[0075] Step S4: Optimize Nodes Based on Multiple Indicators

[0076] To select the best-performing next-hop node from the candidate nodes selected in step S3, this invention proposes an optimization mechanism based on a multi-index comprehensive evaluation function. This mechanism comprehensively considers multiple factors affecting link quality and network performance, and uses the evaluation function to quantitatively score candidate nodes, thereby selecting the optimal node. This step can be further subdivided into the following two sub-steps:

[0077] Step S41: Link Parameter Acquisition

[0078] In this step, the key link parameters required to build the multi-index evaluation model are first extracted, including but not limited to the following:

[0079] Step S411: Packet Error Rate and Packet Delivery Rate

[0080] In this embodiment, the Packet Error Rate (PER) and Packet Delivery Rate (PDR) are defined as follows:

[0081]

[0082] in, L represents the bit error rate when node i sends data to node j, and L represents the data packet length.

[0083] Step S412: Successful forwarding rate

[0084] In step S2, C i In this process, when the j-th candidate node with higher priority fails to forward (where k > j), the k-th candidate node will attempt to forward. If the j-th node successfully receives the data, all j-1 preceding candidates have failed. The probability of successful forwarding is:

[0085]

[0086] Step S413: Expected number of retransmissions

[0087] Assuming that a data packet is discarded after K unsuccessful transmission attempts, the expected number of retransmissions in the maximum K retransmission scenario is:

[0088]

[0089] in, This represents the probability of dropping data packets when K transmissions fail. Preferably, the normalized number of K successful transmissions is:

[0090]

[0091] Step S42: Construction of evaluation indicators

[0092] Based on the link parameters obtained in step S41, the following four core evaluation metrics are constructed:

[0093] Step S421: Distance Progress (DP)

[0094] The distance progress indicator DP has been defined in step S3.

[0095] Step S422: Expected Distance Progress EDP

[0096] When considering link quality, n i The EDP metrics are as follows:

[0097]

[0098] It also takes into account connectivity, link quality, and distance progression to the convergence point.

[0099] Step S423: Energy Efficiency Index (EEM)

[0100] Since IoT nodes typically rely on limited battery capacity to operate, researching energy-efficient sector routing strategies is crucial for extending the overall network lifespan. In fact, as the number of transmission attempts increases, the energy consumed by a node also increases, because each transmission process introduces energy consumption for sending, receiving, and coordination control. Therefore, the energy cost of performing the k-th transmission can be expressed as:

[0101]

[0102] Among them, T s =(L / R i ) is the transmission duration. This is the monitoring power consumed by the decoding and signal processing circuitry, while P c During the coordination duration The coordination power consumed by the internal candidates. Therefore, n j The energy efficiency index (EEM) is

[0103]

[0104] Step S424: Delay Metric LLM

[0105] Latency is a critical metric, especially for latency-intolerant underwater applications. LLM increases with the number of transmission attempts, as each transmission introduces latency due to the transmission and coordination between candidate nodes. The latency caused by n transmission attempts is...

[0106]

[0107] Therefore, n j The LLM can be calculated as

[0108]

[0109] Step S425: Based on the above indicators, this invention proposes a comprehensive evaluation function based on multiple indicators to select the next-hop node with optimal performance. The evaluation function is defined as follows:

[0110] F(j)=ω1·DP(j)+ω2·EDP(j)-ω3·EEM(j)-ω4·LLM(j) (17)

[0111] Where ω1, ω2, ω3, and ω4 are the weights of each indicator, which can be flexibly adjusted according to the needs of the scenario. Under all combinations of (θ, ψ) parameters, the above evaluation is performed on the candidate nodes, and the node j with the highest score is calculated. * and its corresponding angle combination (θ) * ,ψ * This is used as the optimal next hop. This process is equivalent to performing parameter search and path optimization in angle space, achieving a dynamic trade-off between performance and directionality.

[0112] Step S5: FSA Quick Response - Selecting the Next Hop

[0113] To improve the best candidate set in sector routing To improve coordination efficiency, this invention introduces a candidate coordination mechanism based on Fast Time Slot Acknowledgment (FSA). FSA incorporates explicit priority control and fast time slot scheduling on top of the traditional contention-aware mechanism, effectively balancing acknowledgment delay, conflict probability, and energy efficiency.

[0114] Preferably, in this mechanism, the candidate set The nodes in the algorithm are prioritized according to a specific strategy and assigned corresponding sequence numbers. Where k=1 represents the highest priority node. After receiving the data packet forwarded by the previous hop, the receiving node initiates a fast candidate coordination process based on its own priority k.

[0115] First, during the waiting phase, each node waits for an offset time related to its priority, that is:

[0116] T wait (k)=τSIFS +(k-1)·τ sens (18)

[0117] Where, τ SIFS For short interval waiting time, τ sens It has an extremely short channel sensing time.

[0118] Then, in the channel sensing and response phase, T wait After (k) ends, the node executes once for a duration of τ. sens The coordination process involves listening to the channel. If the channel is idle, an ACK frame is immediately sent, indicating that the node has become a forwarding node, and the coordination process ends. If the channel is busy, it is determined that a higher-priority node has already sent an ACK, and the current node immediately abandons its response and exits the competition. Therefore, the upper bound of the coordination delay can be expressed as:

[0119]

[0120] Considering τ sens Typically, it is extremely small, and the above equation can be further approximated as:

[0121] This mechanism enables rapid confirmation from a single response node, effectively avoiding redundancy and channel occupancy caused by multiple nodes forwarding simultaneously.

[0122] Step S6: Dynamic Adjustment of Divergence Angle and Path Maintenance

[0123] Due to dynamic factors such as displacement, drift, equipment failure, or channel instability of underwater nodes, fixed paths are prone to failure. Therefore, this invention designs a dynamic path maintenance strategy based on a hop-by-hop mechanism: before each forwarding, the current node re-performs a conical scan; if the candidate node set is empty, an angle adjustment strategy is implemented to increase the divergence angle.

[0124] θ new =θ old +δ (21)

[0125] Where δ is the step size of the divergence angle increment.

[0126] If R is continuous i If no candidate node is found in the second scan, the current path is considered unreachable, and a path break event is reported to the upper-layer protocol, i.e.:

[0127]

[0128] Among them, R th This represents the maximum number of backoff retries allowed when a node fails to scan or adjust its angle consecutively. This path maintenance strategy features adaptive adjustment and fault tolerance, making it suitable for marine environments with highly dynamic nodes and frequent changes in network topology.

[0129] In summary, this invention proposes an underwater optical communication routing method based on three-dimensional dynamic conical sectors. By constructing a realistic communication model in space and combining node directionality, dynamic conical scanning, and a multi-index evaluation mechanism, it achieves comprehensive optimization of path selection, node coordination, and transmission energy efficiency in complex underwater environments. Specifically, this includes directional screening of candidate nodes, multi-dimensional scoring based on four indicators: distance propagation, expected propagation, energy efficiency, and latency, jump confirmation under a priority-based rapid competition mechanism, and a hop-by-hop adaptive path maintenance process. The entire scheme is fully distributed, requiring no reliance on a global topology or central node, and possesses excellent scalability and deployment flexibility, making it particularly suitable for large-scale heterogeneous underwater IoT networks.

[0130] This invention effectively improves the spatial coverage of neighbor node discovery and reduces communication blind spots by introducing a dynamically adjusted scanning direction and divergence angle strategy. Combined with a multi-index weighted scoring function, it enables flexible trade-offs between communication success rate, energy consumption control, and low latency in path selection. Simultaneously, the Fast Response (FSA) mechanism significantly reduces channel collisions and redundant forwarding, ensuring transmission stability and efficiency. This method exhibits strong robustness and adaptability in unstable and dynamically changing underwater environments, making it particularly suitable for latency-sensitive or energy-constrained missions such as deep-sea monitoring, submarine communication, and marine data backhaul.

[0131] It should be understood that the various steps described in the embodiments of the present invention can be implemented by hardware, software, or a combination of hardware and software. The algorithm logic can be programmably implemented in embedded devices, communication processors, or custom hardware circuits, or it can be executed by a program-controlled general-purpose computing platform; the relevant program can be stored in a non-volatile computer-readable medium, such as flash memory, disk, optical disk, EEPROM, or RAM.

[0132] Those skilled in the art will understand that, without departing from the technical essence of the present invention, various equivalent substitutions and adjustments made to the specific parameter selection, algorithm weight setting, index formula form, routing negotiation process, etc. in this embodiment are all within the protection scope of the present invention.

Claims

1. A method for routing of underwater optical communication based on three-dimensional dynamic conical sector, characterized in that, The method comprises the following steps: A three-dimensional underwater optical communication network model is constructed, and the network model is composed of multiple nodes supporting directional optical communication, each node comprising a directional optical module for transmitting and receiving optical signals, and the optical signals form a conical sector through a defined divergence angle and a direction angle; Based on the node position relationship, a dynamic scanning area defined by the elevation angle azimuth angle γ and the divergence angle θ is constructed. A conical scanning mechanism is used for neighbor node discovery, and the node dynamically scans the neighborhood space by periodically changing the transmission direction and divergence angle to identify neighbor nodes within the communication range; A distance progress (DP) index is used to pre-screen candidate nodes, and only nodes having a positive forward propulsion effect in the target direction are reserved as effective candidate forwarding nodes; A multi-index weighted evaluation function is used to score the candidate nodes, and the multi-index weighted evaluation function F(j) comprises the following indexes: distance progress (DP), expected distance progress (EDP), energy efficiency index (EEM), and low latency index (LLM), and different weights are given to each index to achieve comprehensive scoring and path selection under different routing targets; A fast time slot response (FSA) mechanism is used to quickly coordinate between candidate nodes according to priority to select the final next-hop forwarding node; The neighborhood nodes are re-evaluated and conical scanning is performed before each hop data forwarding, the divergence angle θ is adjusted according to the link state to achieve path maintenance and reconstruction, and the routing stability is ensured in the dynamic underwater environment.

2. The method of claim 1, wherein, The conical scanning area is a three-dimensional space area with the node itself as the vertex, the divergence angle θ as the opening, and the direction angle ψ as the main axis direction, and during the scanning process, the combination of ψ and θ is periodically changed to expand the coverage.

3. The method of claim 1, wherein, The successful establishment of the communication route meets the following conditions simultaneously: the receiving node is located within the conical sector of the transmitting node; the distance between the nodes is less than the maximum communication distance; and the link channel loss is lower than the receiving threshold.

4. The method of claim 1, wherein, The distance progress (DP) is calculated in the following manner: DP ij =||n i -n d ||-||n j -n d || wherein n i and n j are the positions of the current node and the candidate node, respectively, and n d is the position of the target node.

5. The method of claim 1, wherein, The energy efficiency index (EEM) is calculated from the average energy consumption of unit bit data in multiple transmission attempts.

6. The method of claim 1, wherein, The low latency index (LLM) is defined as the total delay generated by n transmission attempts of the node, and the cumulative transmission and coordination time is considered.

7. The method of claim 1, wherein, The multi-index weighted evaluation function F(j) is as follows: F(j) = ω1·DP(j) + ω2·EDP(j) - ω3·EEM(j) - ω4·LLM(j) wherein ω1, ω2, ω3, and ω4 are adjustable weight coefficients and are flexibly configured according to network requirements.

8. The method of claim 1, wherein, The steps of the fast time slot response (FSA) mechanism comprise the following steps: the candidate nodes determine the priority according to the index score; the channel is listened to after a unique offset time delay according to the priority; if the channel is idle, an acknowledgement frame (ACK) is immediately sent; if the channel is occupied, it is considered that a node with higher priority has responded, and the current node automatically exits the competition.

9. The method of claim 1, wherein, The node dynamically increases the divergence angle θ to improve the coverage rate when each forwarding fails or no candidate node is found, and the adjustment strategy is as follows: θ new = θ old + δ wherein δ is an angle step.

10. The method of claim 1, wherein, The method can be deployed in a hardware device, an embedded system, or a software platform, and the algorithms and control logic used can be executed through program instructions.

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