A method for transmitting burst data in a multi-mobile sink sensor network

Abstract

The present invention provides a method for transmitting burst data in a multi-mobile Sink sensor network. The method obtains data information of mobile Sink sensor nodes adjacent to the current node through the current node, and determines whether the current node is a main cluster head. If so, a corresponding main cluster set is generated; all main cluster sets are non-uniformly merged to establish multiple main cluster areas, and a number of candidate sub-cluster heads are elected; the optimal transmission target and the proposed transmission path are determined according to the several candidate sub-cluster heads; the burst data is transmitted according to the optimal transmission target and the proposed transmission path, which not only solves the problem of multi-mobile Sink mobile path planning, but also makes the burst data of sudden events more effectively and reliably transmitted within time constraints.

Description

Technical Field

[0001] The invention relates to the technical field of wireless sensor networks, and in particular to a method for transmitting burst data in a multi-mobile Sink sensor network. Background Art

[0002] Wireless sensor networks (WSNs) are widely used in smart homes, smart grids, environmental monitoring, and smart transportation due to their low cost, flexibility, and ease of use. The use of mobile elements in sensor networks is conducive to improving network performance, connectivity, and load balancing. The reliability and timeliness of data reception are important indicators of wireless sensor networks. When uncertain emergencies and alarms occur in power equipment, the transmission of emergency data to mobile receivers must meet the network's timeliness and reliability requirements.

[0003] In a sensor network, nodes periodically sense the surrounding environment, collect information, and transmit data to a sent base station or mobile sink in a multi-hop manner. Using the mobility of wireless sensor networks for data collection can effectively improve network performance. Unlike a single mobile sink network, using multiple mobile sinks to collect data can reduce the occurrence of void problems, and analyzing the distribution of network nodes and formulating the mobile path of each mobile sink can effectively balance network energy consumption and increase the reliability of data transmission. For some occasional and sudden events, such as detecting power equipment accidents, alarms, and emergencies, some existing algorithms usually continue to use the normal event processing method, which cannot guarantee that emergency events are quickly and timely received by the base station. Moreover, traditional technologies do not consider the impact of multiple burst data streams stealing the same regular data stream on emergency response and reliability, resulting in data transmission congestion.

[0004] In addition, unreasonable mobile sink trajectory planning in traditional multi-mobile sink networks can cause problems such as uneven energy consumption, repeated traversal of nodes, and even premature node failure. In addition, unreasonable path planning and data transmission routing can lead to uneven network data collection and data loss, affecting the timeliness and reliability of burst data transmission in multi-mobile networks.

[0005] Therefore, a method for transmitting burst data in a multi-mobile Sink sensor network is needed, which can solve the problem of multi-mobile Sink mobile path planning and the problem of effective and reliable transmission of burst data of emergency events within time constraints. Summary of the invention

[0006] 1. Technical issues to be resolved

[0007] In order to solve the above problems in the prior art, the present invention provides a method for transmitting burst data in a multi-mobile Sink sensor network, which can solve the problem of multi-mobile Sink mobile path planning and the problem of effective and reliable transmission of burst data of emergency events within time constraints.

[0008] (II) Technical solution

[0009] In order to achieve the above object, the technical solution adopted by the present invention is:

[0010] A method for transmitting burst data in a multi-mobile Sink sensor network comprises the following steps:

[0011] S1, the current node obtains the data information of the mobile sink sensor nodes adjacent to it, and determines whether the current node is the main cluster head. If so, the corresponding main cluster set is generated;

[0012] S2, non-uniformly merge all main cluster sets, establish multiple main cluster areas, and elect several candidate secondary cluster heads;

[0013] S3, determining the optimal transmission target and the proposed transmission path according to the plurality of candidate secondary cluster heads;

[0014] S4. Transmit the burst data according to the optimal transmission target and the planned transmission path.

[0015] (III) Beneficial effects

[0016] The beneficial effects of the present invention are: obtaining data information of mobile Sink sensor nodes adjacent to the current node, and judging whether the current node is a main cluster head, if so, generating a corresponding main cluster set; performing non-uniform merging on all main cluster sets, establishing multiple main cluster areas, and electing several candidate sub-cluster heads; determining the optimal transmission target and the proposed transmission path according to the several candidate sub-cluster heads; transmitting burst data according to the optimal transmission target and the proposed transmission path, which not only solves the problem of mobile path planning for multiple mobile Sinks, but also makes the transmission of burst data of sudden events more efficient and reliable within time constraints. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flow chart of a method for transmitting burst data in a multi-mobile Sink sensor network according to an embodiment of the present invention;

[0018] Figure 2 Comparison of the network survival time between the method of the present invention (MSBDC) and the EGRPM, MECA, and EEDD algorithms;

[0019] Figure 3Schematic diagram of network survival time comparison between the method of the present invention (MSBDC) and the EGRPM, MECA, and EEDD algorithms. DETAILED DESCRIPTION

[0020] In order to better explain the present invention and facilitate understanding, the present invention is described in detail below through specific implementation modes in conjunction with the accompanying drawings.

[0021] Embodiment 1

[0022] Please refer to Figure 1 , a method for transmitting burst data in a multi-mobile Sink sensor network, comprising the steps of:

[0023] S1, the current node obtains the data information of the mobile sink sensor nodes adjacent to it, and determines whether the current node is the main cluster head. If so, the corresponding main cluster set is generated;

[0024] Step S1 specifically includes:

[0025] S11, current node n i Acquire data information of the mobile Sink sensor nodes adjacent to it, wherein the data information includes node ID, location credit and remaining energy information;

[0026] S12, calculate the current node n according to the data information i Competition radius R i ;

[0027] S13, according to the current node n i Competition radius R i Determine whether the current node is the main cluster head. If so, generate the corresponding main cluster set.

[0028] The current node n i Competition radius R i The calculation formula is as follows:

[0029]

[0030] Among them, α, β, γ, θ, μ are weight coefficients, with values ​​of [0, 1], and satisfying α+β+γ+θ+μ≤1. Indicates the maximum communication distance radius preset by the node, d max ,d min They represent the maximum and minimum distances between the network nodes and the base station S, respectively. i ,S) represents node n i The distance to the base station S, Represents node n i The remaining energy of the node with the largest remaining energy is Indicates the current node n i The distribution density of the network is related to the maximum node distribution density. Indicates the current node n i The average transmission distance of the largest node in the network, nb i Indicates the current node n i The number of neighbor nodes, NB i Indicates the current node n i The set of neighbor nodes that satisfies D(n i ,n j ) <d r Node n j is the current node n i Neighbor node, belonging to NB i , N represents the total number of nodes in the network.

[0031] Specifically, in the main cluster head election phase, the competition radius of each node is obtained by a defined weight calculation function and a preset maximum communication distance radius. The competition radius of the node comprehensively considers the distance from the node to the base station, the remaining energy of the node, the distribution density of the node, the average transmission distance of the node and the number of neighboring nodes of the node, and the weight parameters can be changed and adjusted according to the actual application scenario. The closer the node is to the base station, the less remaining energy, the lower the distribution density, the shorter the average transmission distance and the more neighboring nodes, the smaller its competition radius, and the node with the smallest competition radius is preferentially selected as the candidate main cluster head to form the main cluster set.

[0032] S2, non-uniformly merge all main cluster sets, establish multiple main cluster areas, and elect several candidate secondary cluster heads;

[0033] The step S2 is specifically as follows:

[0034] All main cluster sets are non-uniformly merged to establish multiple main cluster areas, and several candidate secondary cluster heads are selected according to the size of the node splitting coefficient.

[0035] The split coefficient w s Refers to the current node n i The ratio of all possible energy consumption for sending data and receiving data to the remaining energy of the node is calculated as follows:

[0036]

[0037] Among them, E re Indicates the energy consumed by receiving data, It represents the energy consumed by the current node to transmit data to neighboring nodes. Indicates the remaining energy of the current node, nb iIndicates the current node n i The number of neighbor nodes.

[0038] S3, determining the optimal transmission target and the proposed transmission path according to the plurality of candidate secondary cluster heads;

[0039] Step S3 is specifically as follows:

[0040] S31, based on the several candidate sub-cluster heads, a path is constructed by selecting the sub-cluster head with the greatest value as a path node, so that the value of the mobile path of the mobile Sink is maximized, and the total value calculation formula of each mobile Sink mobile path l is as follows:

[0041] W l =w s1 +w s2 +w s3 +w s4 ;

[0042] S32: Determine the optimal transmission target and intended transmission path for the burst data.

[0043] The step S32 is specifically as follows:

[0044] S321, when the current node detects burst data, the recorded tag information is used as the proposed transmission hop number, and the selection weight is calculated in combination with the location information of the mobile Sink node, and the mobile Sink node with the smallest relative hop number and distance is used as the optimal transmission target;

[0045] S322. After determining the optimal transmission target, the greedy rule is used according to the tag information of the current node, and the node with the shortest distance in the two layers of tag information is selected with the mobile Sink as the root node to build a simulated transmission path for the burst data.

[0046] S4. Transmit the burst data according to the optimal transmission target and the planned transmission path.

[0047] Step S4 is specifically as follows:

[0048] Taking the burst data node as the root node, the next-hop relay node is selected, and the data is finally sent to the mobile sink of the optimal transmission target along the intended transmission path.

[0049] Specifically, all nodes within the radius of the burst data node are selected as candidate next-hop nodes, and a next-hop node candidate list is established; the nodes of the proposed transmission path are then added to the next-hop candidate list; and when burst data is transmitted, nodes with overlapping paths are selected and avoided.

[0050] Also includes the steps:

[0051] S5. After the candidate list has been generated, the next hop node of the burst data is further clarified according to the node resource utilization, node residual energy and residual cache and the intended transmission path. The next hop node of the burst data is selected according to the residual energy of the candidate transmission node and the node resource utilization, and the routing path of the burst data is adjusted according to the preemption avoidance mechanism, and the burst data is sent to the mobile sink in the case of non-data fusion. When there is a conflict in the selection of relay nodes for burst data, the burst data with fewer hops or higher priority to be transmitted will occupy more node resources, and the burst data with more hops to be transmitted will avoid changing the transmission path to ensure that the burst data can be sent to the mobile sink under time constraints.

[0052] The specific steps for selecting the next relay node to avoid preemption in step S5 are:

[0053] S51, in the initial stage, all burst data have the same priority level. When the next hop node candidate list of all burst data is generated, the burst data node and path information table is updated. According to the remaining energy of the last hop of the current data flow, the node coordinates, the real-time position of the mobile sink and the cache information of the next hop, the optimal solution of the next hop node is selected.

[0054] S52, determine whether there is overlap in the optimal solution selection of the next hop node of the burst data. If there is overlap, the burst data with the least number of hops and the highest priority to be transmitted will seize the node resources and give priority to ensuring that it completes the sending task. The remaining burst data will avoid the path overlap points according to the intended transmission path, update the candidate list, and reselect the next hop node.

[0055] S53: If the next hop node candidate list is empty during the burst data preemption avoidance process, the burst data enters the buffer of the optimal solution and waits, and the priority of the data is increased and is transmitted preferentially in the next time interval.

[0056] S54, when the optimal solutions for all burst data do not overlap, the next hop optimal solution for all burst data is the next hop relay node in its transmission path. According to the next hop relay node, data is transmitted, and the specific information of the corresponding parameters in the node information table and the path information table is updated at the same time. Repeat this process until the data is sent to the mobile Sink node.

[0057] The present invention is aimed at the burst data when the emergency occurs in the multi-mobile sensor network application scenario, which can be efficiently and reliably sent to the mobile sink or base station. In the case of non-data fusion, different burst data situations can ensure a higher network reception rate. Under the premise of being effective and reliable, the acceptance rate of burst data is improved, and the life cycle of the network can be effectively extended.

[0058] Embodiment 2

[0059] The difference between this embodiment and the first embodiment is that this embodiment will further illustrate how the burst data transmission method in the multi-mobile Sink sensor network is implemented in combination with a specific application scenario:

[0060] A method for transmitting burst data in a multi-mobile Sink sensor network comprises the following steps:

[0061] S1, the current node obtains the data information of the mobile sink sensor nodes adjacent to it, and determines whether the current node is the main cluster head. If so, the corresponding main cluster set is generated;

[0062] Step S1 specifically includes:

[0063] S11, current node n i Acquire data information of the mobile Sink sensor nodes adjacent to it, wherein the data information includes node ID, location credit and remaining energy information;

[0064] S12, calculate the current node n according to the data information i Competition radius R i ;

[0065] S13, according to the current node n i Competition radius R i Determine whether the current node is the main cluster head. If so, generate the corresponding main cluster set.

[0066] The current node n i Competition radius R i The calculation formula is as follows:

[0067]

[0068] Among them, α, β, γ, θ, μ are weight coefficients, with values ​​of [0, 1], and satisfying α+β+γ+θ+μ≤1. Indicates the maximum communication distance radius preset by the node, d max ,d min They represent the maximum and minimum distances between the network nodes and the base station S, respectively. i ,S) represents node n i The distance to the base station S, Represents node n i The remaining energy of the node with the largest remaining energy is Indicates the current node n i The distribution density of the network is related to the maximum node distribution density. Indicates the current node n i The average transmission distance of the largest node in the network, nbi Indicates the current node n i The number of neighbor nodes, NB i Indicates the current node n i The set of neighbor nodes that satisfies D(n i ,n j ) <d r Node n j is the current node n i Neighbor node, belonging to NB i , N represents the total number of nodes in the network.

[0069] Nodes and neighboring nodes send information to each other, including the node's ID, location credit, and remaining energy, so as to calculate the average transmission distance and node density of each node. represents the average transmission distance between the node and the other nodes. The distance between nodes can be calculated using the Euclidean distance formula. i The calculation formula for the average transmission distance is as follows:

[0070]

[0071] Among them, d ij Represented as n i and n j The Euclidean distance of N. num Represents the total number of nodes in the network. Indicates the distribution density of nodes in the network, node n i The calculation formula of the distribution density is as follows:

[0072]

[0073] According to the calculation formula of average transmission distance and distribution density, the smaller the average transmission distance of the selected node and the greater the distribution density, the easier it is to be elected as the main cluster head during the competition process.

[0074] Specifically, in the main cluster head election phase, the competition radius of each node is obtained by a defined weight calculation function and a preset maximum communication distance radius. The competition radius of the node comprehensively considers the distance from the node to the base station, the remaining energy of the node, the distribution density of the node, the average transmission distance of the node and the number of neighboring nodes of the node, and the weight parameters can be changed and adjusted according to the actual application scenario. The closer the node is to the base station, the less remaining energy, the lower the distribution density, the shorter the average transmission distance and the more neighboring nodes, the smaller its competition radius, and the node with the smallest competition radius is preferentially selected as the candidate main cluster head to form the main cluster set.

[0075] S2, non-uniformly merge all main cluster sets, establish multiple main cluster areas, and elect several candidate secondary cluster heads;

[0076] The step S2 is specifically as follows:

[0077] All main cluster sets are non-uniformly merged to establish multiple main cluster areas, and several candidate secondary cluster heads are selected according to the size of the node splitting coefficient.

[0078] The split coefficient w s Refers to the current node n i The ratio of all possible energy consumption for sending data and receiving data to the remaining energy of the node is calculated as follows:

[0079]

[0080] Among them, E re Indicates the energy consumed by receiving data, It represents the energy consumed by the current node to transmit data to neighboring nodes. Indicates the remaining energy of the current node, nb i Indicates the current node n i The number of neighbor nodes.

[0081] The candidate sub-cluster heads are elected in the main cluster set and the main cluster area respectively. The candidate sub-cluster heads need to meet three conditions. First, there must be a large number of neighboring nodes. Because when the node resources of the candidate sub-cluster head are used and cannot bear the extra forwarding tasks during the burst data transmission process, the nodes near the candidate sub-cluster head can replace it as a relay node to ensure the acceptance rate of burst data. Second, the candidate sub-cluster head needs to collect data to the maximum extent while determining the path point. The candidate sub-cluster head should make a large number of nodes near the mobile Sink's moving trajectory as much as possible to ensure the delay requirements of data transmission. Third, after selecting the candidate sub-cluster head, the candidate sub-cluster head should determine the candidate path point of the mobile Sink's mobile collection process based on its own node value. The candidate sub-cluster head as a path point needs to have a high residual energy and relay capability, that is, it can forward data as a relay node for multiple nodes.

[0082] S3, determining the optimal transmission target and the proposed transmission path according to the plurality of candidate secondary cluster heads;

[0083] Step S3 is specifically as follows:

[0084] S31, based on the several candidate sub-cluster heads, a path is constructed by selecting the sub-cluster head with the greatest value as a path node, so that the value of the mobile path of the mobile Sink is maximized, and the total value calculation formula of each mobile Sink mobile path l is as follows:

[0085] W l =w s1 +w s2 +ws3 +w s4 ;

[0086] After selecting the path points, a heuristic algorithm is used to plan the shortest movement trajectory of each mobile Sink.

[0087] When the mobile sink is traveling in the network, it starts from the base station and selects the nearest path point as the starting point. When the mobile sink passes through the path point, the nodes near the path point can replace the deputy cluster head to become the relay node, and directly send data to the mobile sink within the transmission radius, which greatly reduces the energy consumption of the deputy cluster head, reduces the burden of the deputy cluster head when it becomes a relay node, and can also improve the utilization rate of network nodes.

[0088] S32: Determine the optimal transmission target and intended transmission path for the burst data.

[0089] The step S32 is specifically as follows:

[0090] S321, when the current node detects burst data, the recorded tag information is used as the proposed transmission hop number, and the selection weight is calculated in combination with the location information of the mobile Sink node, and the mobile Sink node with the smallest relative hop number and distance is used as the optimal transmission target;

[0091] S322. After determining the optimal transmission target, the greedy rule is used according to the tag information of the current node, and the node with the shortest distance in the two layers of tag information is selected with the mobile Sink as the root node to build a simulated transmission path for the burst data.

[0092] In a multi-mobile sink network, sensor nodes sense information in the monitoring area. When burst data is detected, data is transmitted to the target point. After the sensor nodes are clustered and partitioned, the nodes in each cluster transmit data with the mobile sink in the area as the target point. However, since the transmission distances from the sensor nodes at the boundary of the cluster area to the moving trajectories of the mobile sinks in the area and the adjacent area are similar, and the mobile sink does not stop in the area to collect data, the mobile sink in the adjacent cluster area may be a better transmission target for some nodes, which can reduce the energy consumption and delay of data transmission. Therefore, in order to reduce the transmission delay and shorten the transmission distance, the transmission target of the burst data is reselected to confirm the optimal transmission target for each burst data. According to the distance between the node and the mobile sink, the node information broadcast mechanism is used to determine the number of pseudo-hops for data transmission under the condition of limited resources and energy consumption of the node, and the target point selection is realized.

[0093] S4. Transmit the burst data according to the optimal transmission target and the planned transmission path.

[0094] Step S4 is specifically as follows:

[0095] Taking the burst data node as the root node, the next-hop relay node is selected, and the data is finally sent to the mobile sink of the optimal transmission target along the intended transmission path.

[0096] Specifically, all nodes within the radius of the burst data node are selected as candidate next-hop nodes, and a next-hop node candidate list is established; the nodes of the proposed transmission path are then added to the next-hop candidate list; and when burst data is transmitted, nodes with overlapping paths are selected and avoided.

[0097] S5. After the candidate list has been generated, the next hop node of the burst data is further clarified according to the node resource utilization, node residual energy and residual cache and the intended transmission path. The next hop node of the burst data is selected according to the residual energy of the candidate transmission node and the node resource utilization, and the routing path of the burst data is adjusted according to the preemption avoidance mechanism, and the burst data is sent to the mobile sink in the case of non-data fusion. When there is a conflict in the selection of relay nodes for burst data, the burst data with fewer hops or higher priority to be transmitted will occupy more node resources, and the burst data with more hops to be transmitted will avoid changing the transmission path to ensure that the burst data can be sent to the mobile sink under time constraints.

[0098] The specific steps for selecting the next relay node to avoid preemption in step S5 are:

[0099] S51, in the initial stage, all burst data have the same priority level. When the next hop node candidate list of all burst data is generated, the burst data node and path information table is updated. According to the remaining energy of the last hop of the current data flow, the node coordinates, the real-time position of the mobile sink and the cache information of the next hop, the optimal solution of the next hop node is selected.

[0100] S52, determine whether there is overlap in the optimal solution selection of the next hop node of the burst data. If there is overlap, the burst data with the least number of hops and the highest priority to be transmitted will seize the node resources and give priority to ensuring that it completes the sending task. The remaining burst data will avoid the path overlap points according to the intended transmission path, update the candidate list, and reselect the next hop node.

[0101] S53: If the next hop node candidate list is empty during the burst data preemption avoidance process, the burst data enters the buffer of the optimal solution and waits, and the priority of the data is increased and is transmitted preferentially in the next time interval.

[0102] S54, when the optimal solutions for all burst data do not overlap, the next hop optimal solution for all burst data is the next hop relay node in its transmission path. According to the next hop relay node, data is transmitted, and the specific information of the corresponding parameters in the node information table and the path information table is updated at the same time. Repeat this process until the data is sent to the mobile Sink node.

[0103] In the process of data transmission, the present invention uses the burst data node as the starting node and selects the next hop relay node. All nodes within the radius of the burst data node are candidate next hop nodes, and a next hop node candidate list is established. After the candidate list has been generated, the next hop node of the burst data is further clarified according to the node resource utilization, node residual energy, cache and intended transmission path. According to the next hop selection mechanism of the priority, transmission hop number and preemption avoidance mechanism of the burst data, it is ensured that when the burst data selects a relay node conflict, the burst data with fewer intended transmission hops or higher priority will seize more node resources, and the burst data with more intended transmission hops will avoid changing the transmission path to ensure that the burst data can be sent to the mobile sink under time constraints.

[0104] In order to analyze and compare the performance of routing algorithms, the present invention performs data modeling on the EGRPM, MECA, EEDD algorithms and the routing algorithm proposed in the present invention in the Python environment. 100 and 200 wireless rechargeable sensors are randomly deployed in an area of ​​200m×200m. MS acts as a mobile receiver, moving in the network to collect data without stopping.

[0105] Since the resources of sensor nodes are limited, each node has a certain energy capacity E max With cache capacity B max . And the initial energy of each node is different when the network is initialized. Considering the above situation, the initial energy of all sensor nodes is set to a random value between 0 and 2.00. Other simulation parameters can be set according to the following Table 1:

[0106] Table 1 Simulation parameter settings

[0107] Parameters set up Full battery capacity 2J Cache space capacity 500KB Network length 200m Network Width 200m Number of nodes 150 Transmission radius 30m Burst Packets 512 bits

[0108] The energy consumption model for data reception and transmission is:

[0109]

[0110] The size of each data packet is b bits. i Send b bits to node n j , d ij Represented as n i and n jThe Euclidean distance of .

[0111] Node n j Receive b ij The energy consumption model of bit data is:

[0112]

[0113] Among them, E elec Electron energy, E fs and E mp is the amplified energy of free space and multipath model, E elec =50nJ / bit,E fs =10pJ / bit / m2,E mp =1.3*10-3pJ / bit / m4; d m =87m. In this paper, it is assumed that the energy consumption model of the node is always the free space model, that is, d ij <d m ; b tr bit and b re Bit refers to the amount of data transmitted by a node and the amount of data received by a node.

[0114] Figure 2 The network survival time is compared between the method of the present invention (MSBDC) and the EGRPM, MECA, and EEDD algorithms. The network survival time refers to the time when there are always 20 fixed nodes in the network that collect burst data and perform burst data transmission, and the first sensor node dies during the transmission process when the network size is 100 and each node has different initial energy. Figure 3 It can be seen that MSBDC is the first node in the network to die due to energy exhaustion in the 902nd round. The network survival time of EGRPM, MECA, and EEDD algorithms is slightly greater than that of MSBDC. The algorithm proposed in the present invention has a similar network survival time to that of EGRPM, MECA, and EEDD algorithms, but MSBDC always has a higher acceptance rate in terms of acceptance rate. This proves that the algorithm proposed in the present invention can ensure a higher acceptance rate of burst data in the network and can effectively extend the life cycle of the network.

[0115] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for transmitting burst data in a multi-mobile Sink sensor network, characterized in that: Includes steps: S1, the current node obtains the data information of the mobile sink sensor nodes adjacent to it, and determines whether the current node is the main cluster head. If so, the corresponding main cluster set is generated; S2, non-uniformly merge all main cluster sets, establish multiple main cluster areas, and elect several candidate secondary cluster heads; S3, determining the optimal transmission target and the proposed transmission path according to the plurality of candidate secondary cluster heads; S4, transmitting the burst data according to the optimal transmission target and the proposed transmission path; Step S1 specifically includes: S11, current node n i Acquire data information of the mobile Sink sensor nodes adjacent to it, wherein the data information includes node ID, location credit and remaining energy information; S12, calculate the current node n according to the data information i Competition radius R i ; S13, according to the current node n i Competition radius R i Determine whether the current node is the main cluster head. If so, generate the corresponding main cluster set; The current node n i Competition radius R i The calculation formula is as follows: Among them, α, β, γ, θ, μ are weight coefficients, with values ​​of [0, 1], and satisfying α+β+γ+θ+μ≤1. Indicates the maximum communication distance radius preset by the node, d max ,d min They represent the maximum and minimum distances between the network nodes and the base station S, respectively. i ,S) represents node n i The distance to the base station S, Represents node n i The remaining energy of the node with the largest remaining energy is Indicates the current node n i The distribution density of the network is related to the maximum node distribution density. Indicates the current node n i The average transmission distance of the largest node in the network, nb i Indicates the current node n i The number of neighbor nodes, NB i Indicates the current node n i The set of neighbor nodes that satisfies D(n i ,n j ) <d r Node n j is the current node n i Neighbor node, belonging to NB i , N represents the total number of nodes in the network; The step S2 is specifically as follows: All main cluster sets are non-uniformly merged to establish multiple main cluster areas, and several candidate sub-cluster heads are selected by the size of the node splitting coefficient; The split coefficient w s Refers to the current node n i The ratio of all possible energy consumption for sending data and receiving data to the remaining energy of the node is calculated as follows: Among them, E re Indicates the energy consumed by receiving data, It represents the energy consumed by the current node to transmit data to neighboring nodes. Indicates the remaining energy of the current node, nb i Indicates the current node n i The number of neighbor nodes; Step S3 is specifically as follows: S31, based on the several candidate sub-cluster heads, a path is constructed by selecting the sub-cluster head with the greatest value as a path node, so that the value of the mobile path of the mobile Sink is maximized, and the total value calculation formula of each mobile Sink mobile path l is as follows: IN l =in s1 +in s2 +in s3 +in s4 ; S32, determining the optimal transmission target and intended transmission path for the burst data; The step S32 is specifically as follows: S321, when the current node detects burst data, the recorded tag information is used as the proposed transmission hop number, and the selection weight is calculated in combination with the location information of the mobile Sink node, and the mobile Sink node with the smallest relative hop number and distance is used as the optimal transmission target; S322. After determining the optimal transmission target, the greedy rule is used according to the tag information of the current node, and the node with the shortest distance in the two layers of tag information is selected with the mobile Sink as the root node to build a simulated transmission path for the burst data.

2. The method for transmitting burst data in a multi-mobile Sink sensor network according to claim 1, characterized in that: Step S4 is specifically as follows: Taking the burst data node as the root node, the next-hop relay node is selected, and the data is finally sent to the mobile sink of the optimal transmission target along the intended transmission path.

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