Unmanned cluster network routing protocol optimization method based on node energy consumption and mobility

Abstract

The invention discloses an unmanned cluster network routing protocol optimization method based on node energy consumption and mobility, and belongs to the field of wireless networking communication. The invention provides a network node energy consumption evaluation index based on node degree balance. Providing a network node relative movement degree evaluation index; calculating the routing cost value between the nodes through the node energy consumption value based on node degree balance and the node relative movement degree; the frame structure of the AODV-EM protocol is designed; and designing the work flow of the AODV-EM protocol. According to the method, the balance of node loads in the unmanned cluster network and the stability of network links are comprehensively considered, a proper transmission link is planned for data transmission between the nodes, the number of forwarding times of information between the nodes is reduced, the network routing overhead is reduced to the maximum extent, and the network routing efficiency is improved. According to the invention, the unmanned cluster network can still have low transmission delay in a complex urban environment, and the success rate of data transmission is improved at the same time.

Description

Technical Field

[0001] The invention belongs to the field of wireless networking communications, and in particular refers to an unmanned cluster network routing protocol optimization method based on node energy consumption and mobility. Background Art

[0002] With the advancement of low-cost, miniaturized sensor component technology and high-performance processor technology, miniaturized UAVs have been rapidly developed and widely used in recent years. Clustering, autonomy, intelligence, and systematization not only mark the cutting-edge trend of UAV technology, but also open up new fields and prospects for the practical application of UAVs. In particular, in the fields of forest fire prevention and monitoring, agricultural crop pest patrol and prevention, earthquake relief communication relay, battlefield intelligence reconnaissance, and target tracking and identification in complex environments, intelligent unmanned swarms have demonstrated their unique advantages.

[0003] The core of the unmanned swarm network is that many drone nodes realize information interconnection through an autonomous distributed network structure. Compared with the traditional information transmission network, the unmanned swarm network supports the rapid deployment and movement of drone nodes, avoids dependence on ground base stations, has high flexibility for rapid movement, strong mobility without the need for pre-arrangement of ground base stations, and excellent adaptability to various complex and harsh ground environments, providing a solid guarantee for information interaction for the execution of unmanned swarm tasks.

[0004] One of the typical application scenarios of unmanned swarms is the land urban environment. However, the urban environment is densely populated with high-rise buildings, crisscrossing streets and alleys, and complex underground infrastructure. It has many non-line-of-sight situations, severe electromagnetic interference, and crowded frequency bands. When unmanned swarms perform tasks in highly dynamic and highly confrontational complex urban environments, the unmanned swarm network will face problems such as severely limited spectrum resources and fierce competition for network resources. The limited network resources and the instability of network links will greatly affect the success rate of unmanned swarm mission execution.

[0005] In order to ensure that unmanned cluster networks can accurately transmit data in real time in complex urban environments, the choice of routing protocols is crucial. The main function of routing protocols is to plan appropriate transmission links for information transmission between nodes based on the network link status, so as to reduce the number of times information is forwarded between nodes and minimize network routing overhead. Summary of the invention

[0006] In response to the demand for real-time and accurate information transmission of unmanned cluster networks in complex environments, the present invention proposes an unmanned cluster network routing protocol optimization method based on node energy consumption and mobility. The unmanned cluster network routing protocol is named AODV-EM protocol. This protocol addresses the problem that the traditional AODV protocol only uses "minimum hop count" as the only routing criterion, causing the network intermediate nodes to be overloaded and offline in advance, thereby affecting the connectivity and transmission efficiency of the network. It proposes two routing measurement indicators based on node degree balance: network node energy consumption and node relative mobility, and comprehensively considers the two indicators as the basis for new route selection to ensure the balance of network node load and the stability of network links.

[0007] The technical solution adopted by the present invention is:

[0008] A method for optimizing routing protocols in unmanned cluster networks based on node energy consumption and mobility comprises the following steps:

[0009] Step 1: The source node starts the route discovery process and broadcasts a RREQ data frame; wherein the RREQ data frame includes a data packet ID, a destination node address, a destination node serial number, a source node address, a source node serial number, node energy loss, node movement speed along the X-axis and Y-axis directions, and route cost information. When sending the RREQ data frame, the source node sets the node energy loss and route cost value in the frame to an initial value of 0, and stores the speed information of the source node;

[0010] Step 2: When an intermediate node receives the RREQ data frame, it confirms whether it is the first time to receive it. If it is the first time to receive it, it checks whether there is a reverse route. If there is a reverse route, it executes step 3. If there is no reverse route, it directly establishes the reverse route and continues to forward the RREQ data frame. If it is not the first time to receive it, it discards the RREQ data frame.

[0011] Step 3: The intermediate node calculates its own node energy loss based on node degree balance, extracts the speed information stored in the previous hop node, calculates the relative mobility between the previous hop node, and then calculates the routing cost between the previous hop node by combining the node energy consumption value and the relative mobility between nodes, and adds the calculated routing cost to the routing cost in the RREQ data frame; if the current calculated total routing cost value is less than the cache value in the routing table, continue to forward the RREQ data frame and update the information in the routing table, otherwise discard the RREQ data frame;

[0012] Step 4: When the destination node receives the RREQ data frame, the route discovery process ends and the route reply process is started. The destination node unicasts a reply RREP data frame to the source node. The RREP data frame includes the destination node address, the destination node sequence number, the source node address, the lifetime, the node energy loss, the node moving speed along the X-axis and Y-axis directions, and the route cost information. When sending the RREP data frame, the destination node sets the node energy loss and the route cost value in the frame to the initial value 0, and stores the speed information of the destination node.

[0013] Step 5: When an intermediate node receives a RREP data frame, it first checks whether there is a forward route. If so, it executes step 6. If not, it directly establishes reverse routing information and continues to forward the RREP data frame.

[0014] Step 6: The intermediate node calculates its own node energy loss based on node degree balance, extracts the speed information stored in the previous hop node, calculates the relative mobility between the previous hop node and the previous hop node, and then calculates the routing cost between the previous hop node and the previous hop node, and adds the calculated routing cost to the routing cost in the RREP data frame; if the current calculated total routing cost value is less than the cache value in the routing table, continue to forward this data frame and update the information in the routing table, otherwise discard the RREP data frame;

[0015] Step 7: When the source node receives the RREP data frame, the routing reply process ends and the source node starts to transmit data to the destination node.

[0016] Furthermore, in step 3 and step 6, the calculation process of node energy loss is:

[0017] The remaining energy E of any node i i_left The calculation formula is:

[0018]

[0019] In the formula, E i_start represents the initial energy value of node i; P idle represents the power consumption of node i in idle state; t i Represents the current survival time of node i; E i_send represents the energy consumption required for node i to send a message each time; N1 represents the number of times node i sends a message within time period t; E i_recv represents the energy consumption required by node i each time it receives a message; N2 represents the number of times node i receives a message within time period t;

[0020] The energy loss of node i sending a k-bit data packet is as follows:

[0021]

[0022] In the formula, E elec_send represents the energy consumed by node i to send a unit bit of data; ε fs represents the energy loss coefficient under the free space model; ε amp represents the energy loss coefficient under the multipath attenuation model; d represents the distance between the sending node i and the receiving node; d0 represents the distance threshold,

[0023] The energy loss calculation formula for node i receiving a k-bit data packet is:

[0024] E i_recv (k) = k × E elec_recv

[0025] In the formula, E elec_recv represents the energy consumed by node i to receive a unit bit of data;

[0026] The energy loss rate C of any node i in the network i The calculation formula is:

[0027]

[0028] Where η i represents the energy surplus rate of node i;

[0029] The energy loss calculation formula for any node i is:

[0030]

[0031] Where, d i Represents the node degree of node i, and its value is equal to the number of one-hop neighbor nodes of node i.

[0032] Furthermore, in step 3 and step 6, the calculation process of the relative mobility is:

[0033] Calculate the relative movement speed v between any two nodes i and j in the network i,j , expressed as:

[0034]

[0035] In the formula, v i_x 、v i_y 、v i_z are the velocity components of node i in the x, y, and z axes respectively; v j_x 、v j_y 、v j_zare the velocity components of node j along the x, y, and z axes respectively; each node is unified in the same reference coordinate system when calculating its own position information and moving speed. When the node flies along the coordinate axis, the velocity component in the coordinate axis direction is positive, otherwise it is negative;

[0036] Ignoring the velocity component of the node in the z-axis direction, the relative mobility calculation formula between node i and node j is:

[0037]

[0038] In the formula, r i,j represents the relative mobility between nodes i and j; v i,j represents the relative moving speed between nodes i and j; |v i | represents the absolute value of the velocity of node i.

[0039] Furthermore, in step 3 and step 6, the calculation formula of the routing cost is:

[0040]

[0041] In the formula, RC i,j represents the routing cost from node i to node j; represents the energy loss value of node j based on node degree balance; r i,j Represents the relative mobility between node i and node j; α and β represent weight coefficients, the sum of the two is always equal to 1, and the specific value is dynamically adjusted according to the network status.

[0042] The beneficial effects of the present invention are:

[0043] 1. Aiming at the problem that the traditional AODV routing protocol only uses "minimum hop count" as the only routing criterion, which easily causes the key network nodes to go offline prematurely due to excessive load, the method of the present invention proposes two routing metrics based on node degree balance: network node energy consumption and node relative mobility, which comprehensively considers the balance of network node load and the stability of network links.

[0044] 2. Aiming at the real-time and accurate data transmission requirements of unmanned cluster networks in complex urban environments, the method of the present invention designs the AODV-EM routing protocol, which can plan appropriate transmission links for data transmission between nodes, reduce the number of times information is forwarded between nodes, and minimize network routing overhead. It not only ensures a lower transmission delay but also improves the success rate of data transmission, and has broad development prospects in the future. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is the network node communication energy loss model of the present invention.

[0046] Figure 2 This is the RREQ data frame format in the AODV-EM protocol of the present invention.

[0047] Figure 3 This is the RREP data frame format in the AODV-EM protocol of the present invention.

[0048] Figure 4 This is a flow chart of route discovery in the AODV-EM protocol of the present invention.

[0049] Figure 5 This is a flow chart of the route reply in the AODV-EM protocol of the present invention.

[0050] Figure 6 This is a curve comparison diagram of the impact of the number of nodes on the data packet delivery rate of the present invention.

[0051] Figure 7 This is a curve comparison diagram of the impact of the number of nodes on the average routing control overhead of the present invention.

[0052] Figure 8 It is a bar chart comparing the average residual energy of nodes of the present invention. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] An unmanned cluster network routing protocol optimization method based on node energy consumption and mobility is applied to the real-time and accurate data transmission task of unmanned clusters in complex urban environments. The method includes the following steps:

[0055] Step 1: In order to accurately transmit data to the destination node, the source node starts the route discovery process and broadcasts the RREQ data frame; Figure 2 As shown, the RREQ data frame includes a data packet ID, a destination node address, a destination node serial number, a source node address, a source node serial number, a node energy loss, a node moving speed along the X-axis and Y-axis directions, and routing cost information. When sending the RREQ data frame, the source node sets the node energy loss and routing cost value in the frame to the initial value 0, and stores the speed information of the source node.

[0056] Step 2: The route discovery process is as follows: Figure 4As shown, when an intermediate node receives a RREQ data frame, it confirms whether it is received for the first time. If it is received for the first time, it checks whether there is a reverse route. If there is a reverse route, it executes step 3. If there is no reverse route, it directly establishes a reverse route and continues to forward the RREQ data frame; if it is not received for the first time, the RREQ data frame is discarded.

[0057] Step 3, the intermediate node calculates its own node energy loss based on node degree balance, extracts the speed information stored in the previous hop node, calculates the relative mobility between the previous hop node, and then calculates the routing cost between the previous hop node by combining the node energy consumption value and the relative mobility between nodes, and adds the calculated routing cost to the routing cost in the RREQ data frame; if the currently calculated total routing cost value is less than the cache value in the routing table, continue to forward the RREQ data frame and update the information in the routing table, otherwise discard the RREQ data frame.

[0058] Step 4: When the destination node receives the RREQ data frame, the route discovery process ends and the route reply process is started. The destination node unicasts the RREP data frame to the source node. Figure 3 As shown, the RREP data frame includes the destination node address, destination node sequence number, source node address, lifetime, node energy loss, node movement speed along the X-axis and Y-axis directions, and routing cost information. When sending the RREP data frame, the destination node sets the node energy loss and routing cost value in the frame to the initial value 0, and stores the speed information of the destination node.

[0059] Step 5: Routing reply process is as follows Figure 5 As shown, when an intermediate node receives a RREP data frame, it first checks whether there is a forward route. If so, it executes step 6. If not, it directly establishes reverse routing information and continues to forward the RREP data frame.

[0060] Step 6: The intermediate node calculates its own node energy loss based on node degree balance, extracts the speed information stored in the previous hop node, calculates the relative mobility between the previous hop node and the previous hop node, and then calculates the routing cost between the previous hop node and the previous hop node, and adds the calculated routing cost to the routing cost in the RREP data frame; if the currently calculated total routing cost value is less than the cache value in the routing table, continue to forward this data frame and update the information in the routing table, otherwise discard the RREP data frame.

[0061] Step 7: When the source node receives the RREP data frame, the routing reply process ends and the source node starts to transmit data to the destination node.

[0062] In the embodiment of the present invention, the calculation process of the node energy loss in step 3 and step 6 is:

[0063] Assume that the initial energy of node i in the network is E i_start , without considering the node being damaged by attack, the life cycle of the network node is only related to its energy consumption. The faster the energy consumption of the network node, the shorter the node's life span. When the residual energy of the network node is 0, it means that the energy of the node is exhausted and it will be separated from the network and cannot participate in subsequent data forwarding. The network link connected to it will also be broken. Then the residual energy E of any node i is i_left The calculation formula is:

[0064]

[0065] In the formula, E i_start represents the initial energy value of node i; P idle represents the power consumption of node i in idle state; t i Represents the current survival time of node i; E i_send represents the energy consumption required for node i to send a message each time; N1 represents the number of times node i sends a message within time period t; E i_recv represents the energy consumption required for node i to receive a message each time; N2 represents the number of times node i receives a message within time period t.

[0066] When calculating the energy loss of network nodes sending and receiving data packets, the node communication energy loss model adopted by the present invention is as follows: Figure 1 The energy loss of node i sending a k-bit data packet is shown as follows:

[0067]

[0068] In the formula, E elec_send represents the energy consumed by node i to send a unit bit of data; ε fs represents the energy loss coefficient under the free space model; ε amp represents the energy loss coefficient under the multipath attenuation model; d represents the distance between the sending node i and the receiving node; d0 represents the distance threshold,

[0069] The energy loss calculation formula for node i receiving a k-bit data packet is:

[0070] E i_recv (k) = k × E elec_recv

[0071] In the formula, E elec_recv Represents the energy consumed by node i to receive a unit bit of data.

[0072] The energy loss rate C of any node i in the networki The calculation formula is:

[0073]

[0074] Where η i Represents the energy surplus rate of node i.

[0075] It can be seen from this that the more times a node participates in message forwarding in the network, the more energy it consumes, and the greater the energy loss rate becomes. However, when measuring the life span of a network node, it is inaccurate to judge only by the energy loss rate of the node. If there is a node with a large current energy loss rate, but it is at the edge of the network, has a small number of neighboring nodes, and participates in message forwarding less frequently, the node's survival time will be longer. Therefore, in order to accurately judge the survival time of a network node, the present invention introduces the concept of node degree. When the node degree of a node in the network is higher than the average degree of the network nodes, it means that the node has more one-hop neighbor nodes, and will subsequently undertake more message forwarding tasks, and the energy loss will show an upward trend; on the contrary, if the node degree of a node is lower than the average degree of the network nodes, it means that the node has fewer one-hop neighbor nodes, and will subsequently undertake fewer message forwarding tasks, and the energy loss will show a downward trend.

[0076] In order to comprehensively consider the current energy loss of network nodes and the subsequent energy loss trend, the present invention proposes a network node energy consumption evaluation index based on node degree balance. The energy loss calculation formula of any node i is:

[0077]

[0078] Where, d i Represents the node degree of node i, and its value is equal to the number of one-hop neighbor nodes of node i.

[0079] In order to balance the energy consumption of each node in the network as much as possible, it is necessary to avoid nodes with large energy consumption from continuing to participate in too much data forwarding services as relay nodes. The two factors of node degree and node energy loss are comprehensively considered, and node energy loss is used as the main influencing factor through exponential amplification, and node degree is used as the secondary influencing factor through logarithmic reduction. The larger the value, the greater the cost for node i to continue to maintain the current data forwarding state and the shorter the survival time. Therefore, this node needs to be avoided as much as possible during subsequent data forwarding.

[0080] In the embodiment of the present invention, the calculation process of the relative mobility is:

[0081] In an unmanned swarm network, each drone node is always moving at high speed, and the relative positions between nodes are changing rapidly. It is very likely that two nodes have just established a route at the last moment, but cannot communicate at the next moment due to the distance between them being too far. Therefore, before establishing a route, the two nodes need to fully consider the relative mobility between each other, and should choose nodes with a similar motion state as much as possible to maximize the reliability and stability of information transmission.

[0082] Since each node in the unmanned cluster network is equipped with multi-source sensors to achieve collaborative positioning, it can calculate its own position information and moving speed in real time during the movement. Therefore, the relative moving speed v between any two nodes i and j in the network i,j , expressed as:

[0083]

[0084] In the formula, v i_x 、v i_y 、v i_z are the velocity components of node i in the x, y, and z axes respectively; v j_x 、v j_y 、v j_z They are the velocity components of node j in the x, y, and z axes respectively; each node is unified in the same reference coordinate system when calculating its own position information and moving speed. When the node flies along the coordinate axis, the velocity component in the coordinate axis direction is positive, otherwise it is negative.

[0085] In order to better measure the relative motion difference between nodes, the present invention introduces the concept of relative mobility, and its specific calculation formula is shown as follows:

[0086]

[0087] In the formula, r i,j represents the relative mobility between nodes i and j; v i,j represents the relative moving speed between nodes i and j; |v i | represents the absolute value of the velocity of node i.

[0088] In order to simplify the subsequent model calculation and network simulation, the present invention focuses on the topological changes of the unmanned cluster network on the two-dimensional plane. Therefore, the velocity component of the node in the z-axis direction will not be considered when calculating the relative mobility between nodes. The relative mobility calculation formula between node i and node j is:

[0089]

[0090] In the formula, r i,jrepresents the relative mobility between nodes i and j; v i,j represents the relative moving speed between nodes i and j; |v i | represents the absolute value of the velocity of node i.

[0091] If the relative mobility between nodes i and j is r i,j The larger the value is, the more different the current movement directions and movement states of the two nodes are, the more unstable the network link between the two nodes is, and it is necessary to avoid this link as much as possible for data transmission; conversely, it means that the movement directions and movement states of the two nodes are similar, the link formed is very stable, and this link can be selected as the communication link.

[0092] In the embodiment of the present invention, the calculation formula of the routing cost is:

[0093]

[0094] In the formula, RC i,j represents the routing cost from node i to node j; represents the energy loss value of node j based on node degree balance; r i,j Represents the relative mobility between node i and node j; α and β represent weight coefficients, the sum of which is always equal to 1. The specific value can be dynamically adjusted according to the network status. If the nodes in the network move slowly, it means that the relative mobility of the nodes has little impact on the routing cost, then the α value is large and the β value is small. Otherwise, the α value is reduced and the β value is increased. In the subsequent simulation process, the present invention sets both the α value and the β value to 0.5.

[0095] When the source node is searching for a path to the destination node, it will pass through multiple intermediate nodes. By calculating and accumulating the routing cost between each two nodes, the total routing cost of the link between the source node and the destination node can be calculated. The calculation formula is as follows:

[0096]

[0097] In the formula, RC total represents the total routing cost between the source node and the destination node; N represents the number of all nodes on the link between the source node and the destination node; RC i,j Represents the routing cost of the link between node i and node j, and node j is always the next hop node of node i.

[0098] In order to verify the performance improvement of the AODV-EM protocol proposed in this paper compared with the traditional AODV protocol in unmanned cluster network applications, a 1km×1km simulation scene was constructed using NS-3 software. 40-80 drone nodes were deployed in the scene. The moving speed of each node was set in the range of 5-50m / s. Data interaction can be carried out between nodes to simulate the real collaborative positioning application scenario. The detailed simulation parameter configuration is shown in Table 1.

[0099] Table 1

[0100]

[0101] The comparison between the AODV-EM protocol proposed in the present invention and the traditional AODV protocol in terms of data packet delivery rate, average routing control overhead and average node residual energy is shown in Figure 2. Figure 6-Figure 8 As shown in the figure, it can be seen that when the AODV-EM protocol is used in unmanned cluster networks with a large number of nodes and fast mobility, compared with the AODV protocol, its packet delivery rate is higher, the average routing control overhead is lower, the average residual energy of the nodes is higher, and the performance is better.

[0102] In summary, the present invention proposes an unmanned cluster network routing protocol optimization method based on node energy consumption and mobility. This method can be applied in unmanned cluster networks, so that it can still achieve real-time and accurate data transmission under high mobility and high load conditions. Through corresponding experimental verification, the experimental results show that the present invention comprehensively considers the balance of node loads and the stability of network links in unmanned cluster networks, and can plan appropriate transmission links for data transmission between nodes, reduce the number of times information is forwarded between nodes, and minimize network routing overhead. It not only ensures a low transmission delay but also improves the success rate of data transmission, and has broad development prospects.

Claims

1. A method for optimizing routing protocols in unmanned cluster networks based on node energy consumption and mobility, characterized in that: The following steps are involved: Step 1: The source node starts the route discovery process and broadcasts a RREQ data frame; wherein the RREQ data frame includes a data packet ID, a destination node address, a destination node serial number, a source node address, a source node serial number, node energy loss, node movement speed along the X-axis and Y-axis directions, and route cost information. When sending the RREQ data frame, the source node sets the node energy loss and route cost value in the frame to an initial value of 0, and stores the speed information of the source node; Step 2: When an intermediate node receives the RREQ data frame, it confirms whether it is the first time to receive it. If it is the first time to receive it, it checks whether there is a reverse route. If there is a reverse route, it executes step 3. If there is no reverse route, it directly establishes the reverse route and continues to forward the RREQ data frame. If it is not the first time to receive it, it discards the RREQ data frame. Step 3: The intermediate node calculates its own node energy loss based on node degree balance, extracts the speed information stored in the previous hop node, calculates the relative mobility between the previous hop node, and then calculates the routing cost between the previous hop node by combining the node energy consumption value and the relative mobility between nodes, and adds the calculated routing cost to the routing cost in the RREQ data frame; if the current calculated total routing cost value is less than the cache value in the routing table, continue to forward the RREQ data frame and update the information in the routing table, otherwise discard the RREQ data frame; Step 4: When the destination node receives the RREQ data frame, the route discovery process ends and the route reply process is started. The destination node unicasts a reply RREP data frame to the source node. The RREP data frame includes the destination node address, the destination node sequence number, the source node address, the lifetime, the node energy loss, the node moving speed along the X-axis and Y-axis directions, and the route cost information. When sending the RREP data frame, the destination node sets the node energy loss and the route cost value in the frame to the initial value 0, and stores the speed information of the destination node. Step 5: When an intermediate node receives a RREP data frame, it first checks whether there is a forward route. If so, it executes step 6. If not, it directly establishes reverse routing information and continues to forward the RREP data frame. Step 6: The intermediate node calculates its own node energy loss based on node degree balance, extracts the speed information stored in the previous hop node, calculates the relative mobility between the previous hop node and the previous hop node, and then calculates the routing cost between the previous hop node and the previous hop node, and adds the calculated routing cost to the routing cost in the RREP data frame; if the current calculated total routing cost value is less than the cache value in the routing table, continue to forward this data frame and update the information in the routing table, otherwise discard the RREP data frame; Step 7: When the source node receives the RREP data frame, the routing reply process ends and the source node starts to transmit data to the destination node.

2. According to claim 1, a method for optimizing routing protocols in unmanned cluster networks based on node energy consumption and mobility, characterized in that: In step 3 and step 6, the calculation process of node energy loss is: The remaining energy E of any node i i_left The calculation formula is: In the formula, E i_start represents the initial energy value of node i; P idle represents the power consumption of node i in idle state; t i Represents the current survival time of node i; E i_send represents the energy consumption required for node i to send a message each time; N1 represents the number of times node i sends a message within time period t; E i_recv represents the energy consumption required by node i each time it receives a message; N2 represents the number of times node i receives a message within time period t; The energy loss of node i sending a k-bit data packet is as follows: In the formula, E elec_send represents the energy consumed by node i to send a unit bit of data; ε fs represents the energy loss coefficient under the free space model; ε amp represents the energy loss coefficient under the multipath attenuation model; d represents the distance between the sending node i and the receiving node; d0 represents the distance threshold, The energy loss calculation formula for node i receiving a k-bit data packet is: E i_recv (k)=k×E elec_recv In the formula, E elec_recv represents the energy consumed by node i to receive a unit bit of data; The energy loss rate C of any node i in the network i The calculation formula is: Where η i represents the energy surplus rate of node i; The energy loss calculation formula for any node i is: Where, d i Represents the node degree of node i, and its value is equal to the number of one-hop neighbor nodes of node i.

3. The unmanned cluster network routing protocol optimization method based on node energy consumption and mobility according to claim 1, characterized in that: In step 3 and step 6, the calculation process of relative mobility is: Calculate the relative movement speed v between any two nodes i and j in the network i,j , expressed as: In the formula, v i_x 、v i_y 、v i_z are the velocity components of node i in the x, y, and z axes respectively; v j_x 、v j_y 、v j_z are the velocity components of node j along the x, y, and z axes respectively; each node is unified in the same reference coordinate system when calculating its own position information and moving speed. When the node flies along the coordinate axis, the velocity component in the coordinate axis direction is positive, otherwise it is negative; Ignoring the velocity component of the node in the z-axis direction, the relative mobility calculation formula between node i and node j is: In the formula, r i,j represents the relative mobility between nodes i and j; v i,j represents the relative moving speed between nodes i and j; |v i | represents the absolute value of the velocity of node i.

4. The unmanned cluster network routing protocol optimization method based on node energy consumption and mobility according to claim 1, characterized in that: In steps 3 and 6, the calculation formula for the routing cost is: In the formula, RC i,j represents the routing cost from node i to node j; represents the energy loss value of node j based on node degree balance; r i,j Represents the relative mobility between node i and node j; α and β represent weight coefficients, the sum of the two is always equal to 1, and the specific value is dynamically adjusted according to the network status.

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