An adaptive clustering routing method based on dynamic threshold and energy efficiency factor

Abstract

The application is suitable for the field of wireless sensor network, and provides a self-adaptive clustering routing method based on dynamic threshold and energy efficiency factor, which comprises the following contents: cluster establishment stage: the task of this stage is to elect cluster head and complete cluster construction; self-adaptive data transmission stage: after the cluster structure is established, the network enters the stable data transmission stage, which comprises two levels; one is that the member nodes in the cluster transmit the collected data to the home cluster head according to the self-adaptive transmission strategy in the cluster; the other is that each cluster head transmits the data after being integrated and fused to the base station through the self-adaptive routing strategy between clusters. The application significantly prolongs the overall network life cycle, greatly improves the network energy utilization efficiency and load balancing, enhances the stability of network operation and the reliability of data collection, and improves the self-adaptive capacity of the network to dynamic changes.

Description

Technical Field

[0001] This invention relates to the field of wireless sensor networks, and more particularly to an adaptive clustering routing method based on dynamic thresholds and energy efficiency factors. Background Technology

[0002] While wireless sensor networks (WSNs) are demonstrating their enormous potential, they also face a fundamental constraint: the challenge of powering nodes. Most sensor nodes are small in size and rely on batteries with limited power. In typical application scenarios, such as vast farmlands, rugged mountainous areas, disaster-prone remote regions, or large-scale industrial facilities, once nodes are deployed, subsequent battery replacements or power replenishment are often extremely difficult, even uneconomical and impractical. This means that the "life" of each node begins its countdown from the moment its battery is installed, thus severely limiting the effective operating time of the entire network.

[0003] When some nodes in a network cease operation due to energy depletion, the monitoring areas they are responsible for will be unable to continue providing data, potentially interrupting important environmental changes or event information. In multi-hop self-organizing wireless sensor networks, each node not only collects and transmits its own data but may also act as a "relay" for forwarding data to other nodes. If some critically located nodes stop working, it may affect the data transmission paths of other nodes that still have sufficient energy, thereby impacting the overall data acquisition capability and coverage of the network.

[0004] To effectively manage network resources, organize data flows, and maximize overall network uptime, researchers have employed various network organization and data transmission strategies in the design of wireless sensor networks. Among these, hierarchical or clustered routing mechanisms are a widely used approach. This mechanism manages network nodes by organizing them into several "clusters," each typically containing a "cluster head" node. The cluster head node is responsible for collecting data sensed by other member nodes within its cluster, performing preliminary data integration or fusion processing, and then sending the processed information to a higher-level cluster head or directly to the network's base station (data aggregation center). This hierarchical network structure aims to reduce unnecessary long-distance direct communication in the network by optimizing data transmission paths and methods, and to reduce redundant information through data fusion within clusters, thereby managing the overall energy consumption of the network. However, how to efficiently construct these cluster structures, dynamically adapt to changes in network energy and topology, and select the optimal cluster head and routing path to maximize the energy-saving potential of hierarchical or clustered strategies remains a core issue for ongoing exploration in this field. Summary of the Invention

[0005] This invention provides an adaptive clustering routing method based on dynamic thresholds and energy efficiency factors, which solves the technical problems mentioned in the background art.

[0006] An adaptive clustering routing method based on dynamic thresholds and energy efficiency factors, the method comprising:

[0007] Cluster Establishment Phase: The core task of this phase is to elect a suitable cluster head and complete the construction of the cluster;

[0008] Adaptive Data Transmission Phase: After the cluster structure is established, the network enters a stable data transmission phase, which includes two aspects:

[0009] First, ordinary nodes transmit the collected data to their respective cluster heads according to the intra-cluster adaptive transmission strategy.

[0010] Secondly, each cluster head aggregates and merges the data, and then transmits it hop-by-hop or directly to the base station through an inter-cluster adaptive routing strategy.

[0011] Preferably, the cluster establishment phase includes:

[0012] Under the premise of meeting basic operating conditions, eligible nodes in the network become candidate cluster heads through a probabilistic candidate qualification determination mechanism;

[0013] Calculation of the unbalanced competition radius: candidate cluster head It will be based on its remaining energy and its distance from the base station Dynamically calculate a competition radius ;

[0014] The final cluster head node is determined through an energy-based competitive process: before broadcasting its ADV message, the candidate cluster head calculates a waiting time inversely proportional to its remaining energy. The node that successfully broadcasts the ADV message and is not suppressed by other higher-priority candidate cluster heads becomes the final cluster head of this round.

[0015] ;

[0016] in, This represents the maximum remaining energy of all active nodes in the current network. This represents the remaining energy of the current candidate cluster head. This is the preset maximum waiting time limit. This is an exponential adjustment factor used to control the sensitivity of energy levels to waiting time. This is the random adjustment coefficient;

[0017] Once the final cluster head is confirmed, it broadcasts its ADV message. Other suppressed temporary cluster heads and ordinary nodes that have not yet been assigned clusters within its dynamic contention radius, upon receiving the ADV, complete the association with the final cluster head by sending a "Join-REQ" message. The cluster head records its member information accordingly. For the remaining ordinary nodes in the network that have not been assigned clusters after this stage, the protocol specifies a supplementary association mechanism: the remaining ordinary nodes will evaluate the signal strength (RSSI) of all final cluster heads that they can receive and select the final cluster head with the strongest signal to send a "Join-REQ" message to complete the association. After receiving and processing all "Join-REQ" messages, each final cluster head completes the construction and maintenance of its cluster member list.

[0018] Preferably, the content that becomes a candidate cluster head through the candidate qualification determination mechanism includes:

[0019] Each eligible node generates a random number between 0 and 1;

[0020] The protocol sets a fixed probability threshold T (this value is set to 0.35).

[0021] If the random number generated by a node is less than or equal to T, then the node is selected as a candidate cluster head.

[0022] Preferably, the calculation principle of the unbalanced competition radius is as follows:

[0023] and Positive correlation with Negative correlation, and limited to the maximum competition radius. This allows candidate cluster heads with more energy or better locations to cover a larger area, forming non-equilibrium clusters whose size is commensurate with their capabilities.

[0024] Preferably, during the adaptive data transmission phase, cluster member nodes During its allocated data upload time slot, it sends data to its home cluster head. When sending the collected data, the following intra-cluster adaptive transmission strategy is executed to achieve energy-efficient intra-cluster data aggregation:

[0025] S1.1 Preliminary determination of transmission mode: First calculate its relationship with straight-line distance If the straight-line distance Less than or equal to the preset intra-cluster direct transmission threshold ,but Determining direct single-hop transmission as the optimal mode, and preparing to send data directly to... ;

[0026] S1.2, Feasibility assessment and optimal relay selection for multi-hop relays:

[0027] If straight-line distance Greater than the direct transmission threshold ,but An evaluation and selection mechanism for initiating multi-hop relay transmission is required. Obtain those within its communication range and belonging to the same category The state information of other member nodes (i.e., potential relay nodes) (including their positions to calculate distances, and remaining energy) can be synchronized during network initialization or cluster establishment phases via neighbor discovery mechanisms or cluster head assistance; subsequently, For each potential relay node Calculate its intra-cluster relay scoring function The relay scoring function within this cluster By using a weighted combination approach, the theoretical energy-saving potential of the path (composed of relative energy-saving factors) is integrated. Quantization) and potential relay nodes Its own energy state, intra-cluster relay scoring function The definition is as follows:

[0028] ;

[0029] ;

[0030] in, The higher the score, the more likely the node is to be selected. The better the overall benefits of a node as a relay, therefore... Choose what makes it The neighbor with the largest value is selected as the optimal relay node for the next hop. , via node The relative energy saving factor of the relay , and This is the proportionality coefficient. , and These represent the current node to the cluster head and the current node to a potential relay node, respectively. Potential relay nodes Distance to the cluster head; A value greater than 0 indicates that the signal is transmitted via relay. The transmission is energy-efficient. as a potential relay node The remaining energy, As initial energy, and These are the weighting coefficients;

[0031] S1.3, Relay Forwarding, Data Compression, and Iterative Decision Making: Send data to the selected optimal relay node. Optimal relay node After successfully receiving data, the data is first compressed to reduce the packet size, thereby reducing the energy consumption of subsequent transmissions; after compression, the optimal relay node... As the new data holder, it will repeat the decision-making process of steps S1 and S2: that is, determine its own relationship with the cluster head it belongs to. Does the distance meet the direct transmission condition (less than or equal to)? ), or is it necessary to maximize its own again? The value is used to select the next better relay node for further forwarding; this iterative relay process continues until the data is finally successfully transmitted. If, in any decision, the node currently holding the data (whether the original CM node or an intermediate relay node) fails to find any way to make it... If the value indicates a valid relay with clear energy-saving benefits, then the node will abandon multi-hop relays and instead choose to directly connect to the relay. Transmit data to ensure reliable delivery;

[0032] It incorporates the relative energy-saving factor within the cluster ( The data is compressed during the relay process, taking into account the relative energy-saving potential of the data transmitted through the relay and the remaining energy of the relay node. This decision-making process is then repeated by the relay node until the data reaches the cluster head.

[0033] Preferably, the inter-cluster adaptive routing strategy is as follows:

[0034] S2.1 Establishment and Interpretation of Core Decision Parameters: The selection of inter-cluster routing mode and the determination of the next-hop relay cluster head are primarily based on the current cluster head. Straight-line distance between the base station (BS) and the base station (BS) Simultaneously, the protocol introduces a key energy efficiency switching critical distance coefficient. In this invention, the optimal value was scientifically determined through a combination of rigorous theoretical analysis of wireless communication energy consumption models and verification through multi-scenario simulation experiments; this value is 1.25. Coefficients and characteristic switching distances in widely used wireless communication energy consumption models (That is, the distance dividing point where the energy consumption calculation formula of the free space propagation model and the multipath fading propagation model is switched) is combined to calculate the inter-cluster transmission distance threshold of a core. The calculation formula is: ; This establishes a preliminary energy efficiency boundary that distinguishes short-distance direct transmission from medium-distance multi-hop transmission. Furthermore, to further optimize transmission efficiency over extremely long distances and avoid excessively long multi-hop chains, the protocol introduces a long-distance routing policy activation threshold. ;

[0035] S2.2, Distance-based multi-mode adaptive routing strategy and execution process: Based on source cluster head Current distance to base station (BS) Relative to threshold and The relationship dynamically activates one of the following three routing modes:

[0036] S2.2.1, Short-distance routing mode, i.e. :like The distance from BS is no greater than the threshold. The protocol determines that direct single-hop transmission to the BS is the most energy-efficient and reliable method. The data packet will be sent directly to the BS;

[0037] S2.2.2, Medium-distance routing mode, i.e. :like If the distance to the BS is within this range, the protocol will prioritize attempting to select an optimal next-hop relay cluster head. To achieve this, energy-efficient transmission can be performed using two-hop or limited multi-hop methods; Actively broadcast query messages to obtain the current status of other candidate cluster heads within its communication range; optimal relay cluster head. The selection is based on calculating the inter-cluster relay scoring function for all potential candidates. And select the one that maximizes the score, inter-cluster relay scoring function. The definition is as follows:

[0038] ;

[0039] ;

[0040] in, To represent candidate relay cluster heads The final "inter-cluster relay score" is calculated. The higher the score, the more advantageous it is to choose k as the relay. via node The relative energy saving factor of the relay , and Source cluster head to base station relay cluster head to base station Source cluster head To the relay cluster head The distance; A value greater than 0 indicates that the signal is transmitted via relay. The transmission is energy-efficient. For relay cluster head The remaining energy, For the energy of the remaining cluster heads, and These are the weighting coefficients; For the power amplifier coefficients of the free-space propagation model, The power amplifier coefficient represents the energy consumption of the multipath fading propagation model.

[0041] S2.2.3, Long-distance routing mode, i.e. :like The distance from BS reaches or exceeds This indicates that direct transmission or simple two-hop routing may still face excessively high energy consumption or excessively long single-hop distances. In this case, the protocol will activate a more complex iterative multi-hop routing mechanism and introduce the concept of a "virtual base station" to optimize hop-by-hop forwarding decisions for long-distance paths. Under this mechanism, the source cluster head... When selecting its next-hop relay, the target reference point is no longer a distant base station (BS), but is dynamically set to the location of a closer "virtual base station" (VBS); the location of the VBS is usually based on the source cluster head. The coordinates of the base station (BS) are dynamically calculated and set at... The midpoint of the line connecting the VBS and the base station (BS) makes the VBS a temporary target that gradually "approaches" the base station (BS); the selection of the next-hop relay cluster head is still based on maximizing the dynamically calculated VBS as the target. Value, at this time in the formula This refers to the distance from the current cluster head to the VBS; after a data packet is sent to the selected next-hop relay cluster head, that relay cluster head will become the new data source node; it will reassess its own distance to the base station (BS): if it still meets the requirements... The process of VBS positioning (setting up a new VBS between itself and the base station BS) and next-hop selection based on the new VBS will be repeated. If the distance between it and the base station BS has entered the medium or short distance range, it will switch to the corresponding mode (i.e., the routing strategy of ii or i above) for subsequent transmission. This iterative selection and forwarding process continues until the data finally arrives at the base station BS efficiently and energy-savingly through a series of carefully selected relays.

[0042] The beneficial effects achieved by this invention are as follows:

[0043] This invention (DEXTRA-CR protocol), an adaptive clustering routing method based on dynamic thresholds and energy efficiency factors, is applied to wireless sensor networks. Through its unique multi-stage dynamic adaptive mechanism, it brings significant improvements in network energy management and data routing. Simulation experiments in various typical network scenarios, including configurations deploying 500 nodes in a 500×500 meter area, 600 nodes in a 500×500 meter area, and 600 nodes in a 600×600 meter area, fully validated the effectiveness of the DEXTRA-CR protocol. Specifically, the effectiveness is demonstrated as follows:

[0044] Significantly extends the overall lifespan of the network:

[0045] Through an innovative cluster head election mechanism (which includes probabilistic preliminary determination of candidate qualifications and final confirmation through subsequent energy optimization), a dynamic unbalanced clustering strategy, and adaptive hierarchical routing for energy optimization within and between clusters, this invention can more effectively balance the energy consumption rate of each node in the network. This significantly alleviates the "bottleneck effect" caused by the premature energy depletion of some critical nodes (such as cluster heads near the base station or high-load relay nodes). Simulation results from all the above test scenarios consistently demonstrate the advantages of the DEXTRA-CR protocol: compared with other representative protocols, the DEXTRA-CR protocol can significantly delay the time of the first node death (FND) in the network and extend the total duration of the last node death (LND) or network function failure, thereby improving the effective working life of the entire network.

[0046] Significantly improves network energy efficiency and load balancing:

[0047] This invention dynamically adjusts the cluster size and cluster head selection, making the cluster structure more adaptable to the real-time energy status of nodes and their location in the network topology. This ensures that nodes with sufficient energy and good connectivity can assume more appropriate responsibilities. Simultaneously, during data transmission, whether it's cluster members aggregating data to the cluster head or the cluster head relaying data to the base station, both utilize real-time energy efficiency assessment (through...). and The path selection (implemented by a scoring function) prioritizes the transmission path and mode with the lowest energy consumption. In all tested scenarios, experimental data (such as total network energy consumption, average node energy consumption, etc., whose effectiveness can be indirectly reflected by the persistence of the number of surviving nodes) show that the DEXTRA-CR protocol not only reduces the average energy consumption of a single data transmission, but more importantly, promotes a more balanced distribution of network load in space and time, effectively mitigating the formation and deterioration of energy "hot spots".

[0048] Enhance network stability and data acquisition reliability:

[0049] Due to the extended network lifetime and balanced energy consumption, more sensor nodes can remain active for a longer period, ensuring continuous coverage of the network monitoring area and the integrity of data collection. Network connectivity is also better maintained due to the extended lifespan of key nodes, increasing the probability of successful data transmission to the base station and improving overall network reliability. In experiments across various test scenarios, the longer node lifetime under the DEXTRA-CR protocol resulted in more persistent data collection capabilities and a more stable network topology, thereby guaranteeing data transmission success rates and network service quality.

[0050] Improve the network's ability to adapt to dynamic changes:

[0051] The decision-making mechanisms in this invention, such as cluster head election, competition radius calculation, and route selection, are all dynamically adaptive, capable of adjusting according to changes in node energy, local density, and potential changes in network topology. The DEXTRA-CR protocol exhibits stable performance advantages in various simulation scenarios with different numbers of nodes and network area sizes, fully demonstrating its excellent adaptability. Regardless of initial network conditions, DEXTRA-CR can effectively adjust its network structure and routing strategy to adapt to the current state, maintaining high energy efficiency and operational performance. Attached Figure Description

[0052] Figure 1 The present invention provides an overall flowchart of an adaptive clustering routing method based on dynamic threshold and energy efficiency factor.

[0053] Figure 2 A flowchart of the cluster establishment stage provided by the present invention.

[0054] Figure 3 A flowchart of the adaptive data transmission stage provided by the present invention.

[0055] Figure 4 This is a comparison chart of the death times of key lifecycle nodes of each protocol in a 500×500 meter scenario in an embodiment of the present invention.

[0056] Figure 5 This is a comparison chart of the number of surviving nodes for each protocol in a 500-node network in a 500×500 meter scenario according to an embodiment of the present invention.

[0057] Figure 6 This is a comparison chart of the total remaining energy of a 500-node network in a 500×500 meter scenario in an embodiment of the present invention.

[0058] Figure 7 This is a comparison chart of the cumulative number of data packets sent to the base station by each protocol from 500 nodes in a 500×500 meter scenario according to an embodiment of the present invention.

[0059] Figure 8 This is a comparison chart of the death times of key lifecycle nodes of each protocol in a 500×500 meter scenario in an embodiment of the present invention.

[0060] Figure 9 This is a comparison chart of the number of surviving nodes for each protocol in a 600-node network in a 500×500 meter scenario according to an embodiment of the present invention.

[0061] Figure 10 This is a comparison chart of the total remaining energy of a 600-node network in a 500×500 meter scenario in an embodiment of the present invention.

[0062] Figure 11 This is a comparison chart showing the cumulative number of data packets sent to the base station by various protocols in a 600-node network under a 500×500 meter scenario in this embodiment of the invention.

[0063] Figure 12 This is a comparison chart of the death times of key lifecycle nodes of each protocol in a 600×600 meter scenario in an embodiment of the present invention.

[0064] Figure 13 This is a comparison chart of the number of surviving nodes for each protocol in a 600-node network in a 600×600 meter scenario according to an embodiment of the present invention.

[0065] Figure 14 This is a comparison chart of the total remaining energy of a 600-node network in a 600×600 meter scenario in an embodiment of the present invention.

[0066] Figure 15 This is a comparison chart of the cumulative number of data packets sent to the base station by each protocol from 600 nodes in a 600×600 meter scenario according to an embodiment of the present invention. Detailed Implementation

[0067] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as a limitation of the present invention, but rather as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0068] It should be understood that the terminology used in this invention is merely for describing particular embodiments and is not intended to limit the invention. Furthermore, with respect to numerical ranges in this invention, it should be understood that each intermediate value between the upper and lower limits of the range is also specifically disclosed. Every smaller range between any stated value or intermediate value within a stated range, and any other stated value or intermediate value within said range, is also included in this invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range.

[0069] Please see Figure 1This invention provides an adaptive clustering routing method based on dynamic thresholds and energy efficiency factors, the method comprising:

[0070] Cluster Establishment Phase: The core task of this phase is to elect a suitable cluster head and complete the construction of the cluster;

[0071] Adaptive Data Transmission Phase: After the cluster structure is established, the network enters a stable data transmission phase, which includes two aspects:

[0072] First, ordinary nodes rely on an intra-cluster adaptive transmission strategy (e.g., based on distance to the cluster head and via an intra-cluster relay scoring function). The optimal relay is selected during the evaluation process and then transmitted to its assigned cluster head.

[0073] Second, the data aggregated and merged by each cluster head is then processed through inter-cluster adaptive routing strategies (e.g., based on distance to the base station and key energy efficiency handover threshold coefficients). and through inter-cluster relay scoring function The optimal relay is selected through evaluation (which may include mechanisms such as virtual base stations) and transmitted hop-by-hop or directly to the base station.

[0074] Please see Figure 2 In this embodiment, the cluster establishment stage includes:

[0075] Provided that the basic operating conditions are met (e.g., the remaining energy is greater than zero), eligible nodes in the network become candidate cluster heads through a probabilistic candidate qualification determination mechanism;

[0076] Calculation of the unbalanced competition radius: candidate cluster head It will be based on its remaining energy and its distance from the base station Dynamically calculate a competition radius ;

[0077] The final cluster head node is determined through an energy-based competitive process: before broadcasting its cluster head identity (ADV message), the candidate cluster head calculates a waiting time inversely proportional to its remaining energy. The node that successfully broadcasts the ADV message and is not suppressed by other higher-priority candidate cluster heads becomes the final cluster head of this round. The higher the energy of the candidate cluster head, the shorter the waiting time, thus giving it priority in broadcasting, effectively suppressing lower-energy candidate cluster heads within its competition radius, and quickly completing the confirmation of the final cluster head.

[0078] ;

[0079] in, This represents the maximum remaining energy of all active nodes in the current network. This is the preset maximum waiting time limit. This is an exponential adjustment factor used to control the sensitivity of energy levels to waiting time. This is the random adjustment coefficient;

[0080] After the final cluster head is confirmed, it broadcasts its ADV message. Other suppressed temporary cluster heads within its dynamic contention radius, as well as ordinary nodes that have not yet been assigned clusters, upon receiving the ADV, complete the association with the final cluster head by sending a "Join-REQ" message. The cluster head then records its member information accordingly. For the remaining ordinary nodes in the network that have not yet been assigned clusters after this stage, the protocol specifies a supplementary association mechanism: the remaining ordinary nodes will evaluate the signal strength (RSSI) of all final cluster heads they can receive and select the final cluster head with the strongest signal to send a "Join-REQ" message to complete the association. After receiving and processing all "Join-REQ" messages, each final cluster head completes the construction and maintenance of its cluster member list. For a detailed process of this stage, please refer to […]. Figure 2 Cluster establishment phase flowchart.

[0081] In this embodiment, the content that becomes a candidate cluster head through the candidate qualification determination mechanism includes:

[0082] Each eligible node generates a random number between 0 and 1;

[0083] The protocol sets a fixed probability threshold T (this value is set to 0.35).

[0084] If the random number generated by a node is less than or equal to T, then the node is selected as a candidate cluster head.

[0085] This candidate cluster head election method ensures that a subset of nodes in the network qualify as candidates. In this specific step of candidate cluster head generation, a node's eligibility is not directly determined by its own specific operating parameters. The subsequent final cluster head confirmation phase will further filter these qualified nodes based on their relevant attributes to determine the final cluster head.

[0086] In this embodiment, the calculation principle of the unbalanced competition radius is as follows:

[0087] and Positive correlation with Negative correlation, and limited to the maximum competition radius. This allows candidate cluster heads with more energy or better locations to cover a larger area, forming non-equilibrium clusters whose size is commensurate with their capabilities.

[0088] Please see Figure 3 In this embodiment, during the adaptive data transmission phase, cluster member nodes During its allocated data upload time slot, it sends data to its home cluster head. When sending the collected data, the following intra-cluster adaptive transmission strategy is executed to achieve energy-efficient intra-cluster data aggregation:

[0089] S1.1 Preliminary determination of transmission mode: First calculate its relationship with straight-line distance If the straight-line distance Less than or equal to the preset intra-cluster direct transmission threshold ,but Determining direct single-hop transmission as the optimal mode, and preparing to send data directly to... ;

[0090] S1.2, Feasibility Assessment and Optimal Relay Selection for Multi-Hop Relays: If the straight-line distance... Greater than the direct transmission threshold ,but An evaluation and selection mechanism for initiating multi-hop relay transmission is required. Obtain those within its communication range and belonging to the same category The state information of other member nodes (i.e., potential relay nodes) (including their positions to calculate distances, and remaining energy) can be synchronized during network initialization or cluster establishment phases via neighbor discovery mechanisms or cluster head assistance; subsequently, For each potential relay node Calculate its intra-cluster relay scoring function The relay scoring function within this cluster By using a weighted combination approach, the theoretical energy-saving potential of the path (composed of relative energy-saving factors) is integrated. Quantization) and potential relay nodes Its own energy state, intra-cluster relay scoring function The definition is as follows:

[0091] ;

[0092] ;

[0093] in, The higher the score, the more likely the node is to be selected. The better the overall benefits of a node as a relay, therefore... Choose what makes it The neighbor with the largest value is selected as the optimal relay node for the next hop. , via node The relative energy saving factor of the relay , and This is the proportionality coefficient. , and These represent the current node to the cluster head and the current node to a potential relay node, respectively. Potential relay nodes Distance to the cluster head; A value greater than 0 indicates that the signal is transmitted via relay. The transmission is energy-efficient. as a potential relay node The remaining energy, As initial energy, and These are the weighting coefficients;

[0094] S1.3, Relay Forwarding, Data Compression, and Iterative Decision Making: Send data to the selected optimal relay node. Optimal relay node After successfully receiving data, the data is first compressed to reduce the packet size, thereby reducing the energy consumption of subsequent transmissions; after compression, the optimal relay node... As the new data holder, it will repeat the decision-making process of steps S1 and S2: that is, determine its own relationship with the cluster head it belongs to. Does the distance meet the direct transmission condition (less than or equal to)? ), or is it necessary to maximize its own again? The value is used to select the next better relay node for further forwarding; this iterative relay process continues until the data is finally successfully transmitted. If, in any decision, the node currently holding the data (whether the original CM node or an intermediate relay node) fails to find any way to make it... If the value indicates a valid relay with clear energy-saving benefits, then the node will abandon multi-hop relays and instead choose to directly connect to the relay. Transmit data to ensure reliable delivery;

[0095] It incorporates the relative energy-saving factor within the cluster ( The data is compressed during the relay process, taking into account the relative energy-saving potential of the data transmitted through the relay and the remaining energy of the relay node. This decision-making process is then repeated by the relay node until the data reaches the cluster head.

[0096] Please see Figure 3 In this embodiment, the inter-cluster adaptive routing strategy is as follows:

[0097] S2.1 Establishment and Interpretation of Core Decision Parameters: The selection of inter-cluster routing mode and the determination of the next-hop relay cluster head are primarily based on the current cluster head. Straight-line distance between the base station (BS) and the base station (BS) Simultaneously, the protocol introduces a key energy efficiency switching critical distance coefficient. In this invention, the optimal value was scientifically determined through a combination of rigorous theoretical analysis of wireless communication energy consumption models and verification through multi-scenario simulation experiments; this value is 1.25. Coefficients and characteristic switching distances in widely used wireless communication energy consumption models (That is, the distance dividing point where the energy consumption calculation formula of the free space propagation model and the multipath fading propagation model is switched) is combined to calculate the inter-cluster transmission distance threshold of a core. The calculation formula is: ; This establishes a preliminary energy efficiency boundary that distinguishes short-distance direct transmission from medium-distance multi-hop transmission. Furthermore, to further optimize transmission efficiency over extremely long distances and avoid excessively long multi-hop chains, the protocol introduces a long-distance routing policy activation threshold. ;

[0098] S2.2, Distance-based multi-mode adaptive routing strategy and execution process: Based on source cluster head Current distance to base station (BS) Relative to threshold and The relationship dynamically activates one of the following three routing modes:

[0099] S2.2.1, Short-distance routing mode, i.e. :like The distance from BS is no greater than the threshold. The protocol determines that direct single-hop transmission to the BS is the most energy-efficient and reliable method. The data packet will be sent directly to the BS;

[0100] S2.2.2, Medium-distance routing mode, i.e. :like If the distance to the BS is within this range, the protocol will prioritize attempting to select an optimal next-hop relay cluster head. To achieve this, energy-efficient transmission can be performed using two-hop or limited multi-hop methods; Actively broadcast query messages to obtain the current status of other candidate cluster heads within its communication range; optimal relay cluster head. The selection is based on calculating the inter-cluster relay scoring function for all potential candidates. And select the one that maximizes the score, inter-cluster relay scoring function. The definition is as follows:

[0101] ;

[0102] ;

[0103] in, To represent candidate relay cluster heads The final "inter-cluster relay score" is calculated. The higher the score, the more advantageous it is to choose k as the relay. via node The relative energy saving factor of the relay , and Source cluster head to base station relay cluster head to base station Source cluster head To the relay cluster head The distance; A value greater than 1 indicates that the signal is transmitted via relay. The transmission is energy-efficient. For relay cluster head The remaining energy, For the energy of the remaining cluster heads, and For weighting system; For the power amplifier coefficients of the free-space propagation model, The power amplifier coefficient represents the energy consumption of the multipath fading propagation model.

[0104] S2.2.3, Long-distance routing mode, i.e. :like The distance from BS reaches or exceeds This indicates that direct transmission or simple two-hop routing may still face excessively high energy consumption or excessively long single-hop distances. In this case, the protocol will activate a more complex iterative multi-hop routing mechanism and introduce the concept of a "virtual base station" to optimize hop-by-hop forwarding decisions for long-distance paths. Under this mechanism, the source cluster head... When selecting its next-hop relay, the target reference point is no longer a distant base station (BS), but is dynamically set to the location of a closer "virtual base station" (VBS); the location of the VBS is usually based on the source cluster head. The coordinates of the base station (BS) are dynamically calculated and set at... The midpoint of the line connecting the VBS and the base station (BS) makes the VBS a temporary target that gradually "approaches" the base station (BS); the selection of the next-hop relay cluster head is still based on maximizing the dynamically calculated VBS as the target. Value, at this time in the formula This refers to the distance from the current cluster head to the VBS; after a data packet is sent to the selected next-hop relay cluster head, that relay cluster head will become the new data source node; it will reassess its own distance to the base station (BS): if it still meets the requirements... The process of VBS positioning (setting up a new VBS between itself and the base station BS) and next-hop selection based on the new VBS will be repeated. If the distance between it and the base station BS has entered the medium or short distance range, it will switch to the corresponding mode (i.e., the routing strategy of ii or i above) for subsequent transmission. This iterative selection and forwarding process continues until the data finally arrives at the base station BS efficiently and energy-savingly through a series of carefully selected relays.

[0105] To verify the performance of the proposed adaptive clustering routing method (DEXTRA-CR protocol) based on dynamic threshold and energy efficiency factor, we evaluated it through simulation experiments and compared it with several existing representative wireless sensor network routing protocols (LEACH, EBUC, LEACH IM, LEACH EDP). All simulation examples used the following uniform parameter configuration unless otherwise specified in specific examples.

[0106] The general simulation parameter configuration is shown in Table 1:

[0107] Table 1: General Simulation Parameter Configuration

[0108]

[0109] Performance evaluation metrics include: network lifespan, the number of surviving nodes in the network over time, the total amount of data sent to the base station in each round, and the total remaining energy of the network in each round.

[0110] Experiment Example 1: Simulation of a network scenario with 500×500 meter area and 500 nodes

[0111] 1) Specific scenario configuration

[0112] Network area: 500 meters × 500 meters.

[0113] Number of nodes: 500 sensor nodes.

[0114] Base station (BS) location: (250, 500)

[0115] 2) Effects:

[0116] Network lifecycle and surviving nodes:

[0117] Simulation results show that the network lifecycle metrics for each protocol are as follows (protocol order: LEACH, EBUC, LEACHIM, LEACH EDP, DEXTRA-CR):

[0118] Please see Figure 4 Comparison chart of death times of key lifecycle nodes of various protocols;

[0119] First Node Death (FND) Time (rounds): LEACH is 41 rounds, EBUC is 478 rounds, LEACH IM is 44 rounds, LEACH EDP is 63 rounds, while the FND of the DEXTRA-CR protocol of this invention is 710 rounds.

[0120] The death time of the tenth node (rounds): LEACH is 74 rounds, EBUC is 753 rounds, LEACH IM is 106 rounds, LEACHEDP is 147 rounds, and DEXTRA-CR protocol is 771 rounds.

[0121] The time to death (LND) of all nodes (rounds) is as follows: LEACH is 1750 rounds, EBUC is 1017 rounds, LEACH IM is 1805 rounds, LEACH EDP is 1316 rounds, and the overall network survival time of the DEXTRA-CR protocol is the longest, reaching 1860 rounds.

[0122] Reference Figure 5 A comparison chart of the number of surviving nodes for each protocol in a 500-node network in a 500×500 meter scenario. This chart visually verifies the above lifecycle data points:

[0123] All protocols in the diagram initially have 500 surviving nodes.

[0124] The DEXTRA-CR protocol (green curve) of this invention stands out: its FND is the latest (approximately 710 rounds), and the node survival curve remains high for a relatively long period after the initial stage, followed by a relatively gentle decline until it reaches the longest LND (approximately 1860 rounds). This clearly demonstrates that the DEXTRA-CR protocol can most effectively extend the active time of nodes in the network and postpone the time of network function failure.

[0125] Energy consumption characteristics:

[0126] Reference Figure 6A comparison chart of the total remaining energy of a 500-node network in a 500×500 meter scenario. The chart clearly shows that the initial total network energy is approximately 500 joules. Compared to LEACH EDP, LEACH IM, LEACH, and EBUC, the DEXTRA-CR protocol of this invention exhibits optimal energy consumption management. Its rate of total network energy decline differs from other protocols in the initial stage, and even when the energy of other major comparative protocols has significantly decreased or been exhausted (e.g., at round 1000), the DEXTRA-CR protocol network still retains a considerable amount of remaining energy. The DEXTRA-CR protocol's total network energy is not completely exhausted until approximately 1800 rounds later.

[0127] This result specifically demonstrates the excellent energy balancing and energy-saving effect of the DEXTRA-CR protocol in a 500-node network, thus supporting longer network operation.

[0128] Reference Figure 7 A comparison chart of the cumulative number of data packets sent to the base station by various protocols in a 500×500 meter scenario with 500 nodes. This chart shows the cumulative total number of data packets successfully sent to the base station (aggregation node) by each protocol during network operation:

[0129] The LEACH protocol (black curve) has the lowest cumulative number of data packets sent, approximately 16,455.

[0130] The LEACH IM protocol (cyan curve) has sent a total of approximately 20,695 data packets.

[0131] The EBUC protocol (blue curve) has sent a total of approximately 22,783 data packets. Its curve flattens out after about 1,050 rounds (corresponding to its LND).

[0132] The LEACH EDP protocol (red curve) has sent a total of approximately 23,836 data packets. Its curve flattens out after about 1,000 rounds (corresponding to its LND).

[0133] The DEXTRA-CR protocol (green curve) of this invention performs best, with a cumulative total of 33,002 data packets sent to the base station, significantly higher than all comparable protocols. Although the instantaneous data packet transmission rate of the DEXTRA-CR protocol may not be the highest in the initial stage (approximately the first 200 rounds), thanks to its significantly extended network lifetime and continuous node activity, it can maintain effective data collection and transmission for a longer period, thereby achieving maximum data throughput.

[0134] This result fully demonstrates that the DEXTRA-CR protocol can not only extend network lifespan, but also ensure a higher total amount of data collection and transmission reliability during that lifespan.

[0135] Experiment Example 2: Network Scenario Simulation Based on a 500×500 meter Area and 600 Nodes

[0136] 1) Specific scenario configuration

[0137] Network area: 500 meters × 500 meters.

[0138] Number of nodes: 600 sensor nodes.

[0139] Base station (BS) location: (250, 500)

[0140] 2) Effects:

[0141] In this simulation scenario, the DEXTRA-CR protocol exhibits significant performance advantages, as detailed below:

[0142] Network lifecycle and surviving nodes:

[0143] Simulation results show that the network lifecycle metrics for each protocol are as follows (protocol order: LEACH, EBUC, LEACHIM, LEACH EDP, DEXTRA-CR):

[0144] First Node Death (FND) Time (rounds): LEACH IM is the earliest at 42 rounds; LEACH is at 41 rounds; LEACH EDP is at 61 rounds; EBUC is at 370 rounds; while the FND of the DEXTRA-CR protocol of this invention is 680 rounds, which is significantly later than all other comparative protocols, effectively maintaining the integrity of the network in the initial stage.

[0145] The time to death of the tenth node (rounds) is as follows: LEACH: 71 rounds; LEACH IM: 106 rounds; LEACH EDP: 153 rounds; EBUC: 711 rounds; DEXTRA-CR protocol: 832 rounds, further demonstrating DEXTRA-CR's outstanding ability to delay early node cluster failures.

[0146] Time to death (LND) of all nodes (rounds): EBUC is 1204 rounds; LEACH EDP is 1437 rounds; LEACH is 1855 rounds; LEACH IM is 1841 rounds; the DEXTRA-CR protocol has the longest overall network survival time, reaching 2000 rounds, far exceeding all other comparison protocols.

[0147] These data clearly demonstrate that the DEXTRA-CR protocol, through its unique energy management and routing mechanisms, can most effectively balance network energy consumption and significantly extend various lifecycle indicators of the network.

[0148] Figure 8The comparison chart of critical lifecycle node death times for 600 nodes in a 500×500 meter scenario should intuitively show that the DEXTRA-CR protocol (usually represented by a green curve) can maintain more surviving nodes at each stage compared to other protocols, and the curve declines more gently, resulting in the longest overall effective network working time, which is consistent with the data points mentioned above.

[0149] Reference Figure 9 Comparison of the number of surviving nodes for various protocols in a 600-node network in a 500×500 meter scenario. All protocols initially have 600 surviving nodes. The node counts for LEACH IM (cyan curve), LEACH (black curve), and LEACH EDP (red curve) decrease very rapidly, with their first node death (FND) occurring at rounds 43, 40, and 62 respectively, prematurely entering the network decline phase. The EBUC protocol (blue curve) has a relatively later FND (approximately 470 rounds), maintaining network stability for a period, but then the number of nodes drops sharply, resulting in complete network death after approximately 1000 rounds. The DEXTRA-CR protocol of this invention (green curve) performs best: its FND is significantly delayed to round 712, after which the number of nodes begins to decline steadily until reaching the longest total node death time, LND (1860 rounds). This clearly demonstrates that the DEXTRA-CR protocol can most effectively balance network energy consumption, maximizing the network's stable runtime and overall lifespan.

[0150] Energy consumption characteristics:

[0151] Reference Figure 10 A comparison chart of the total remaining energy of a 600-node network in a 500×500 meter scenario. The chart clearly shows that the initial total network energy is approximately 600 joules. Compared to LEACH EDP (red curve), LEACH IM (cyan curve), LEACH (black curve), and EBUC (blue curve), the DEXTRA-CR protocol of this invention (green curve) exhibits optimal energy consumption management. Its rate of total network energy decrease differs from other protocols in the initial stage, and even when the energy of other major comparison protocols has significantly decreased or is nearly exhausted (e.g., around round 1000, when the EBUC protocol's energy is almost depleted), the DEXTRA-CR protocol network still retains significant remaining energy. The DEXTRA-CR protocol's total network energy is not completely exhausted until approximately 1900 rounds (coinciding with its LND data of 2000 rounds).

[0152] This result specifically demonstrates the excellent energy balancing and energy-saving effect of the DEXTRA-CR protocol in a 600-node network, thus supporting longer network operation.

[0153] Data transmission performance:

[0154] Reference Figure 11 A comparison chart of the cumulative number of data packets sent to the base station by various protocols in a 600-node network with a 500×500 meter scenario. This chart shows the cumulative total number of data packets successfully sent to the base station by each protocol.

[0155] The LEACH protocol (black curve) has the lowest cumulative number of data packets sent, at 19,478.

[0156] The LEACH IM protocol (cyan curve) is shown on the graph to have a higher cumulative total of packets than LEACH, eventually reaching approximately 27,142.

[0157] The EBUC protocol (blue curve) has sent a total of 28,305 data packets, and its curve flattens out after about 1,000 rounds (close to its LND).

[0158] The LEACH EDP protocol (red curve) has sent a total of 31,779 data packets. Its curve flattens out after about 1,200 rounds (close to its LND).

[0159] The DEXTRA-CR protocol (green curve) of this invention performs best, with a total of 36,509 data packets sent to the base station, significantly higher than all comparable protocols. The data packet accumulation curve of the DEXTRA-CR protocol shows that although the accumulation rate in the initial stage is similar to or slightly slower than that of its EBUC protocol, it can ultimately achieve the maximum data throughput by virtue of its longer network lifetime and continuous effective data transmission. The curve only flattens out when it approaches its LND (1500 rounds).

[0160] This result demonstrates that the DEXTRA-CR protocol not only excels in extending network lifetime, but also performs exceptionally well in ensuring the total amount of network data collected and the reliability of transmission.

[0161] Experiment Example 3: Network Scenario Simulation Based on a 600×600 meter Area and 600 Nodes

[0162] 1) Specific scenario configuration

[0163] Network area: 600 meters × 600 meters.

[0164] Number of nodes: 600 sensor nodes.

[0165] Base station (BS) location: (300, 600)

[0166] 2) Effects:

[0167] Network lifecycle and surviving nodes:

[0168] Simulation results show that the network lifecycle metrics for each protocol are as follows (protocol order: LEACH, EBUC, LEACHIM, LEACH EDP, DEXTRA-CR):

[0169] Reference Figure 12 Comparison chart of critical lifecycle node death times for 600 nodes across 600 protocols in a 600×600 meter scenario;

[0170] First Node Death (FND) Time (rounds): LEACH IM is the earliest, at 3 rounds; LEACH at 5 rounds; LEACH EDP at 21 rounds; the DEXTRA-CR protocol of this invention at 398 rounds; EBUC at 166 rounds. In this scenario, DEXTRA-CR's FND performance is superior to most comparative protocols.

[0171] The time to death of the tenth node (rounds): LEACH is 38 rounds; LEACH IM is 49 rounds; LEACH EDP is 74 rounds; EBUC is 370 rounds; and DEXTRA-CR protocol is 573 rounds, showing a significant advantage in maintaining the number of surviving nodes in the early stages of the network.

[0172] The time to death (LND) of all nodes (rounds) is as follows: EBUC is 907 rounds; LEACH EDP is 1312 rounds; LEACH IM is 1597 rounds; LEACH is 1594 rounds; the DEXTRA-CR protocol has the longest overall network survival time, reaching 1886 rounds, far exceeding all other comparison protocols.

[0173] Reference Figure 13 A comparison chart of the number of surviving nodes for each protocol in a 600-node network in a 600×600 meter scenario. This chart visually verifies the above lifecycle data points:

[0174] All protocols in the diagram initially have 600 surviving nodes.

[0175] The number of nodes in LEACH IM (cyan curve), LEACH EDP (red curve), and LEACH (black curve) decreases rapidly and FND occurs very early.

[0176] The EBUC protocol (blue curve) has a relatively late FND (around 166 rounds), but its nodes are quickly exhausted after about 700 rounds.

[0177] The DEXTRA-CR protocol (green curve) of this invention exhibits the most outstanding performance: after its FND (approximately 398 rounds), the number of nodes begins to decline rapidly, but after approximately 800 rounds, it can still maintain the survival of some nodes for a long time, until reaching the longest LND (1886 rounds). This clearly demonstrates that even under conditions of increased network size and relatively sparse nodes, the DEXTRA-CR protocol can still most effectively extend the active time of nodes in the network and postpone the time of network function failure.

[0178] Energy consumption characteristics:

[0179] Reference Figure 14 A comparison chart of total remaining energy in a 600×600 meter scenario with a 600-node network. This chart shows the total energy consumption of each protocol during network operation (initial total energy 600 joules):

[0180] As can be seen from the figure, there are significant differences in the energy consumption rates of each protocol. At round 1000, the remaining network energy for each protocol is as follows: LEACH EDP less than 1 joule, LEACH IM about 2 joules, LEACH about 6 joules, EBUC energy completely depleted, while the remaining energy of the DEXTRA-CR protocol of this invention is about 9 joules.

[0181] The energy consumption strategy of the DEXTRA-CR protocol prioritizes long-term balance and maintaining the overall network lifetime. The energy degradation curve of the DEXTRA-CR protocol is flatter in the later stages, ensuring its longest network uptime.

[0182] Data transmission performance:

[0183] Reference Figure 15 A comparison chart of the cumulative number of data packets sent to the base station by various protocols in a 600×600 meter network with 600 nodes. This chart shows the cumulative total number of data packets successfully sent to the base station by each protocol at this network scale.

[0184] The LEACH protocol (black curve) has the lowest cumulative number of data packets sent, at 15,148.

[0185] The LEACH IM protocol (cyan curve) has sent a total of 20,889 data packets.

[0186] The EBUC protocol (blue curve) has sent a total of 20,205 data packets.

[0187] The LEACH EDP protocol (red curve) has sent a total of 24,799 data packets.

[0188] The DEXTRA-CR protocol (green curve) of this invention still performs best in this larger network scenario, with a total of 33,788 data packets sent to the base station, significantly higher than all the comparison protocols. As shown in the figure, the curve of the DEXTRA-CR protocol continues to grow steadily until later rounds before flattening out, indicating that it can still maintain efficient data collection and transmission capabilities and make full use of its extended network lifetime even under conditions of expanded network range and relatively sparse nodes.

[0189] This further validates the robustness of the DEXTRA-CR protocol under different network sizes and densities and its effectiveness in improving the overall data throughput of the network.

[0190] It should be noted that, in this document, the term "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0191] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. An adaptive clustering routing method based on dynamic thresholds and energy efficiency factors, characterized in that, The method includes; Cluster establishment phase: The task of this phase is to elect a cluster head and complete the construction of the cluster; Adaptive data transmission phase: After the cluster structure is established, the network enters a stable data transmission phase, which includes two levels: First, member nodes within a cluster transmit the collected data to their respective cluster head according to the cluster's adaptive transmission strategy. Second, each cluster head aggregates and merges the data, and then transmits it to the base station hop-by-hop or directly through an inter-cluster adaptive routing strategy. During the adaptive data transmission phase, cluster member nodes During its allocated data upload time slot, it sends data to its home cluster head. When sending the collected data, the following intra-cluster adaptive transmission strategy is executed: S1.1 Preliminary determination of transmission mode: First calculate its relationship with straight-line distance If the straight-line distance Less than or equal to the preset intra-cluster direct transmission threshold ,but Determining direct single-hop transmission as the optimal mode, we prepare to send the data directly to... ; S1.2, Feasibility Assessment and Optimal Relay Selection for Multi-Hop Relays: If the straight-line distance... Greater than the direct transmission threshold ,but An evaluation and selection mechanism for initiating multi-hop relay transmission is required. Obtain those within its communication range and belonging to the same category Status information of other member nodes; Subsequently, For each potential relay node Calculate its intra-cluster relay scoring function The relay scoring function within this cluster By using a weighted combination approach, the theoretical energy-saving potential of the path and potential relay nodes are integrated. Its own energy state, intra-cluster relay scoring function The definition is as follows: ； ； in, The higher the score, the more likely the node is to be selected. The better the overall benefits as a relay, therefore... Choose what makes it The neighbor with the largest value is selected as the optimal relay node for the next hop. , via node The relative energy saving factor of the relay , and This is the proportionality coefficient. , and These represent the current node to the cluster head and the current node to a potential relay node, respectively. Potential relay nodes Distance to the cluster head; A value greater than 0 indicates that the signal is transmitted via relay. The transmission is energy-efficient. as a potential relay node The remaining energy, As initial energy, and These are the weighting coefficients; S1.3, Relay Forwarding, Data Compression, and Iterative Decision Making: Send data to the selected optimal relay node. Optimal relay node After successfully receiving data, the data is first compressed to reduce the packet size; after compression, the optimal relay node... As the new data holder, repeat the decision-making process in steps S1.1 and S1.2: that is, determine its own relationship with the cluster head it belongs to. Does the distance meet the conditions for direct transmission, or is it necessary to maximize its own distance again? The value is used to select the next better relay node for further forwarding; this iterative relay process continues until the data is finally successfully transmitted. If, in any decision, the node currently holding the data fails to find any way to make it... If the value indicates a valid relay with clear energy-saving benefits, then the node will abandon multi-hop relays and instead choose to directly connect to the relay. Transmit data; It incorporates the relative energy-saving factor within the cluster. The data is compressed during the relay process, and the decision-making process is repeated by the relay node until the data reaches the cluster head. The data is also considered in conjunction with the remaining energy of the candidate relay node, which combines the relative energy-saving potential of the data transmission through the relay and the remaining energy of the relay node. Inter-cluster adaptive routing strategy: S2.1 Establishment and Interpretation of Core Decision Parameters: The selection of inter-cluster routing mode and the determination of the next-hop relay cluster head are primarily based on the current cluster head. Straight-line distance between the base station (BS) and the base station (BS) Simultaneously, an energy efficiency switching critical distance coefficient is introduced. ,this Coefficients and characteristic switching distance in wireless communication energy consumption models Combined, this is used to calculate a core inter-cluster transmission distance threshold. The calculation formula is: ; This establishes a preliminary energy efficiency boundary to distinguish between short-distance direct transmission and medium-distance multi-hop transmission; in addition, a long-distance routing policy activation threshold is introduced. ; S2.2, Distance-based multi-mode adaptive routing strategy and execution process: Based on the source cluster head Current distance to base station (BS) Relative to threshold and The relationship dynamically activates one of the following three routing modes: S2.2.1, Short-distance routing mode, i.e. :like The distance from BS is no greater than the threshold. The protocol determines that direct single-hop transmission to the BS is the most energy-efficient and reliable method. The data packet will be sent directly to the BS; S2.2.2, Medium-distance routing mode, i.e. :like If the distance to the BS is within this range, the protocol will prioritize attempting to select an optimal next-hop relay cluster head. To perform energy-efficient transmission in two-hop or limited multi-hop configurations; to achieve this, the source cluster head... Actively broadcast query messages to obtain the current status of other candidate cluster heads within its communication range; optimal relay cluster head. The selection is based on calculating the inter-cluster relay scoring function for all potential candidates. And select the one that maximizes the score, inter-cluster relay scoring function. The definition is as follows: ； ； in, To represent candidate relay cluster heads The final "inter-cluster relay score" indicates that choosing k as the relay is more advantageous, as the score is higher. via node The relative energy saving factor of the relay , and Source cluster head to base station relay cluster head to base station , source cluster head To the relay cluster head The distance; A value greater than 1 indicates that the relay cluster head is used. The transmission is energy-efficient. For relay cluster head The remaining energy, For the energy of the remaining cluster heads, and These are the weighting coefficients; For the power amplifier coefficients of the free-space propagation model, The power amplifier coefficient represents the energy consumption of the multipath fading propagation model. S2.2.3, Long-distance routing mode, i.e. If the source cluster head The distance from BS reaches or exceeds At this point, the protocol will activate an iterative multi-hop routing mechanism and introduce the concept of a "virtual base station" to optimize hop-by-hop forwarding decisions for long-distance paths; under this mechanism, the source cluster head When selecting its next-hop relay, its target reference point is no longer the base station (BS), but is dynamically set to the location of a closer "virtual base station" (VBS); the location of the VBS is based on the source cluster head. The coordinates of the base station (BS) are dynamically calculated and set at... The midpoint of the line connecting the VBS and the base station (BS) makes the VBS a temporary target that gradually "approaches" the base station (BS); the selection of the next-hop relay cluster head is still based on maximizing the VBS dynamically calculated from this point as the target. Value, at this time in the formula This refers to the distance from the current cluster head to the VBS; after a data packet is sent to the selected next-hop relay cluster head, that relay cluster head will become the new data source node; it will reassess its own distance to the base station BS: if it still meets the requirements... The process of VBS location and next-hop selection based on the new VBS will be repeated; if the distance between it and the base station BS has entered the medium or short distance range, it will switch to the corresponding routing strategy for subsequent transmission; this iterative selection and forwarding process continues until the data arrives at the base station BS.

2. The adaptive clustering routing method based on dynamic threshold and energy efficiency factor according to claim 1, characterized in that, The cluster establishment phase includes: Under the premise of meeting the basic operating conditions, eligible nodes in the network become candidate cluster heads through the candidate qualification determination mechanism; Calculation of the unbalanced competition radius: for each candidate cluster head It will be based on its remaining energy and its distance from the base station Dynamically calculate a competition radius ; The final cluster head node is determined through an energy-based competitive process: before broadcasting its ADV message, the candidate cluster head calculates a waiting time inversely proportional to its remaining energy. The node that successfully broadcasts the ADV message and is not suppressed by other higher-priority candidate cluster heads becomes the final cluster head of this round. ； in, This represents the maximum remaining energy of all active nodes in the current network. This represents the remaining energy of the current candidate cluster head. This is the preset maximum waiting time limit. This is an exponential adjustment factor used to control the sensitivity of energy levels to waiting time. This is the random adjustment coefficient; After the final cluster head is confirmed, other suppressed temporary cluster heads within its dynamic contention radius and ordinary nodes that have not yet been assigned clusters, upon receiving ADV, complete the association with the final cluster head by sending a "join request" message, and the cluster head records its member information accordingly. For the remaining ordinary nodes in the network that have not been assigned clusters after this stage, the protocol specifies a supplementary association mechanism: the remaining ordinary nodes will evaluate the signal strength of all final cluster heads that they can receive, and select the final cluster head with the strongest signal to send a "join request" message to complete the association; after receiving and processing all "join request" messages, each final cluster head completes the construction and maintenance of its cluster member list.

3. The adaptive clustering routing method based on dynamic threshold and energy efficiency factor according to claim 2, characterized in that, The following are the contents that become candidate cluster heads through the candidate qualification determination mechanism: Each eligible node generates a random number between 0 and 1; The protocol sets a fixed probability threshold T; If the random number generated by a node is less than or equal to T, then the node is selected as a candidate cluster head.

4. The adaptive clustering routing method based on dynamic threshold and energy efficiency factor according to claim 2, characterized in that, The principle for calculating the radius of unbalanced competition is as follows: and Positive correlation with Negative correlation, and limited to the maximum competition radius. Inside.

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