A data transmission method and device based on heat perception and electronic equipment

Abstract

Embodiments of the present application disclose a data transmission method and device based on heat perception and electronic equipment, comprising: acquiring a current network node bearing a to-be-transmitted task, and acquiring each neighbor network node corresponding to the current network node when the current network node only bears a single to-be-transmitted task; determining a current heat index corresponding to each neighbor network node according to a multi-dimensional state parameter corresponding to each neighbor network node; determining a plurality of multi-point relay nodes in each neighbor network node according to the current heat index corresponding to each neighbor network node; determining a next hop node corresponding to the current network node in each multi-point relay node according to a priority of a to-be-forwarded data stream corresponding to the to-be-transmitted task; and sending the to-be-forwarded data stream to the next hop node to complete the to-be-transmitted task, thereby improving the selection accuracy of the multi-point relay node, avoiding network congestion, and ensuring the data transmission efficiency between network nodes.

Description

Technical Field

[0001] This invention relates to the field of communication networks and information transmission technology, and in particular to a data transmission method, apparatus and electronic device based on heat sensing. Background Technology

[0002] In typical low-quality-of-service (QoS) network application scenarios such as air traffic control information and shore-to-ship data transmission, the network generally suffers from prominent problems such as dynamic and ever-changing topology, limited bandwidth resources, and poor transmission link stability.

[0003] Currently, in order to adapt to complex and low-quality network transmission environments, the mainstream active routing protocol, Optimized Link State Routing (OLSR), is often adopted, which effectively reduces network control message overhead by relying on multi-point relay mechanisms.

[0004] However, existing multi-point relay selection algorithms mainly rely on node connectivity indicators, which makes core network nodes prone to becoming "hot spots" due to excessive relay tasks, leading to buffer overflows and loss of critical data. Summary of the Invention

[0005] This invention provides a data transmission method, apparatus, and electronic device based on heat perception, which solves the problem that existing technologies rely solely on node connectivity indicators to select multi-point relay nodes, leading to hotspots formed on core network nodes due to excessive relay tasks, resulting in buffer overflows and loss of critical data. This invention improves the selection accuracy of multi-point relay nodes, avoids network congestion, and ensures data transmission efficiency between network nodes.

[0006] In a first aspect, embodiments of the present invention provide a data transmission method based on heat perception, comprising: acquiring a current network node carrying a task to be transmitted; and when the current network node carries only a single task to be transmitted, acquiring each neighboring network node corresponding to the current network node; determining a current heat index corresponding to each neighboring network node based on multi-dimensional state parameters corresponding to each neighboring network node; determining multiple multi-point relay nodes among each neighboring network node based on the current heat index corresponding to each neighboring network node; determining a next-hop node corresponding to the current network node among each multi-point relay node based on the priority of the data stream to be forwarded corresponding to the task to be transmitted; and sending the data stream to be forwarded to the next-hop node to complete the task to be transmitted.

[0007] Secondly, embodiments of the present invention also provide a data transmission device based on heat perception, comprising: a neighbor node acquisition module, configured to acquire the current network node carrying the task to be transmitted, and when the current network node carries only a single task to be transmitted, acquire each neighbor network node corresponding to the current network node; a heat index determination module, configured to determine the current heat index corresponding to each neighbor network node according to the multi-dimensional state parameters corresponding to each neighbor network node; a relay node determination module, configured to determine multiple multi-point relay nodes among each neighbor network node according to the current heat index corresponding to each neighbor network node; a next-hop node determination module, configured to determine the next-hop node corresponding to the current network node among each multi-point relay node according to the priority of the data stream to be forwarded corresponding to the task to be transmitted; and a task execution module, configured to send the data stream to be forwarded to the next-hop node to complete the task to be transmitted.

[0008] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to execute the heat-sensing-based data transmission method provided in any embodiment of the present invention.

[0009] The technical solution of this invention solves the problem that existing technologies rely solely on node connectivity indicators to select multi-point relay nodes, which can easily lead to hotspots in core network nodes due to excessive relay tasks, resulting in buffer overflows and loss of critical data. This improves the selection accuracy of multi-point relay nodes, avoids network congestion, and ensures efficient data transmission between network nodes. Specifically, when a current network node carries only a single task to be transmitted, the invention determines the current heat index corresponding to each neighboring network node based on multi-dimensional state parameters; determines multiple multi-point relay nodes among each neighboring network node based on the current heat index; determines the next-hop node among each multi-point relay node based on the priority of the data stream to be forwarded corresponding to the task; and sends the data stream to be forwarded to the next-hop node to complete the task.

[0010] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a flowchart of a data transmission method based on heat sensing according to Embodiment 1 of the present invention.

[0013] Figure 2 This is a flowchart of another heat-sensing-based data transmission method provided in Embodiment 2 of the present invention.

[0014] Figure 3 This is a schematic diagram of a data transmission device based on heat sensing according to Embodiment 3 of the present invention.

[0015] Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0016] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0017] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0018] Example 1 Figure 1This is a flowchart of a heat-sensing-based data transmission method according to Embodiment 1 of the present invention. This embodiment is applicable to the situation of data transmission between multiple network nodes. The method can be executed by a heat-sensing-based data transmission device, which can be implemented in hardware and / or software and can be configured in an electronic device such as a computer.

[0019] like Figure 1 As shown, this embodiment discloses a data transmission method based on heat sensing, including: S110-S150.

[0020] S110. Obtain the current network node carrying the task to be transmitted, and when the current network node only carries a single task to be transmitted, obtain each neighboring network node corresponding to the current network node.

[0021] Here, the task to be transmitted can be understood as the task of transmitting the data stream to be forwarded to the target node. The neighboring network node can be understood as the network node that is one hop away from the current network node.

[0022] In this step, specifically, the current network node can be controlled to send neighbor probe messages via link-local broadcast to obtain information about its neighboring network nodes.

[0023] S120. Determine the current heat index corresponding to each neighboring network node based on the multi-dimensional state parameters corresponding to each neighboring network node.

[0024] In this embodiment, the multidimensional state parameters can cover various types of parameters such as the length of the task queue to be transmitted, CPU utilization, link quality indicator value, and remaining energy attenuation rate. The current heat index can be used to reflect the real-time busy level of neighboring network nodes.

[0025] In this step, specifically, the multi-dimensional performance cost value corresponding to each neighboring network node can be determined based on the multi-dimensional state parameters corresponding to each neighboring network node. This multi-dimensional performance cost value can include various costs such as queue congestion, CPU load, link quality, and energy attenuation. Then, based on the multi-dimensional performance cost value corresponding to each neighboring network node, the current popularity index corresponding to each neighboring network node can be determined.

[0026] The advantage of this setup is that by using multi-dimensional state parameters corresponding to each neighboring network node, the current popularity index corresponding to each neighboring network node can be determined. This takes into account the real-time load (such as queue backlog and CPU usage) and link quality fluctuations of each neighboring network node, quantifies the current congestion risk and link instability of the node, and provides a basis for data routing and transmission scheduling.

[0027] S130. Based on the current popularity index corresponding to each neighboring network node, determine multiple multi-point relay nodes among each neighboring network node.

[0028] In this embodiment, a multi-point relay node can be understood as a neighbor network node that can cover a large number of two-hop neighbor nodes and has a low current popularity index.

[0029] In this step, specifically, the fitness value corresponding to each neighboring network node can be determined based on the current popularity index and the number of two-hop neighboring nodes. Then, based on the fitness values ​​corresponding to each neighboring network node, multiple multi-point relay nodes can be determined among each neighboring network node.

[0030] S140. Based on the priority of the data stream to be forwarded corresponding to the task to be transmitted, determine the next-hop node corresponding to the current network node among the multi-point relay nodes.

[0031] The priority of the data stream to be forwarded can be used to reflect the importance of the data stream to be forwarded.

[0032] In this step, specifically, based on the priority of the data stream to be forwarded corresponding to the task to be transmitted, the multi-point relay node with the lowest current popularity index can be used as the next-hop node, or the multi-point relay node that meets the preset load balancing strategy can be used as the next-hop node.

[0033] S150. Send the data stream to be forwarded to the next hop node to complete the transmission task.

[0034] The technical solution of this embodiment obtains the current network node carrying the task to be transmitted, and when the current network node only carries a single task to be transmitted, obtains each neighboring network node corresponding to the current network node; determines the current heat index corresponding to each neighboring network node according to the multi-dimensional state parameters corresponding to each neighboring network node; determines multiple multi-point relay nodes among each neighboring network node according to the current heat index corresponding to each neighboring network node; determines the next-hop node corresponding to the current network node among each multi-point relay node according to the priority of the data stream to be forwarded corresponding to the task to be transmitted; and sends the data stream to be forwarded to the next-hop node to complete the task to be transmitted. This solves the problem that the existing technology relies solely on node connectivity indicators to select multi-point relay nodes, which easily leads to hotspots in the core network nodes due to excessive relay tasks, thereby causing buffer overflow and loss of critical data. This improves the selection accuracy of multi-point relay nodes, avoids network congestion, and ensures the data transmission efficiency between network nodes.

[0035] Example 2 Figure 2This is a flowchart of another heat-sensing-based data transmission method according to Embodiment 2 of the present invention. This embodiment is a further optimization and extension of the above embodiments and can be combined with various optional technical solutions in the above embodiments.

[0036] like Figure 2 As shown, this embodiment discloses a data transmission method based on heat sensing, including: S210-S290.

[0037] S210. Obtain the current network node carrying the task to be transmitted.

[0038] S220. When the current network node only carries a single task to be transmitted, obtain each neighboring network node corresponding to the current network node.

[0039] S230. Determine the current heat index corresponding to each neighboring network node based on the multi-dimensional state parameters corresponding to each neighboring network node.

[0040] Optionally, based on the multi-dimensional state parameters corresponding to each neighboring network node, the current popularity index corresponding to each neighboring network node is determined, including: based on the multi-dimensional state parameters corresponding to each neighboring network node, determining the queue congestion cost, CPU load cost, link quality cost, and energy attenuation cost corresponding to each neighboring network node; and based on the queue congestion cost, CPU load cost, link quality cost, and energy attenuation cost corresponding to each neighboring network node, determining the current popularity index corresponding to each neighboring network node.

[0041] The multidimensional state parameters include the length of the task queue to be transmitted, CPU utilization, link quality indicator, and remaining energy decay rate. The length of the task queue to be transmitted can be understood as the number of tasks waiting to be processed in the node's buffer; a longer queue indicates a higher risk of congestion. CPU utilization reflects the real-time busyness of the node's CPU; higher utilization indicates a weaker ability to process new tasks. The link quality indicator reflects the transmission communication quality of the wireless link between the current network node and its neighboring nodes; a lower indicator indicates a less reliable wireless link. The remaining energy decay rate reflects the rate at which the node's energy is consumed; a higher rate indicates a more unstable node.

[0042] Specifically, multiple state parameters corresponding to each neighboring network node can be normalized to obtain multiple normalized state parameters for each neighboring network node. Then, the entropy weight method can be used to determine the weight coefficients corresponding to each normalized state parameter. It is worth noting that the higher the information entropy of a state parameter, the higher the uncertainty of that state parameter, the greater the amount of information it provides, and the higher its weight coefficient will be. Finally, based on the normalized state parameters corresponding to each neighboring network node and the weight coefficients corresponding to each normalized state parameter, the current popularity index corresponding to each neighboring network node can be determined.

[0043] Furthermore, based on the normalized state parameters corresponding to each neighboring network node and the weight coefficients corresponding to each normalized state parameter, the current heat index corresponding to each neighboring network node is determined. This may include: obtaining the maximum queue length, maximum CPU utilization, and maximum link quality indicator value corresponding to each neighboring network node; determining the queue congestion cost value corresponding to each neighboring network node based on the normalized queue length of pending transmission tasks, the maximum queue length, and the queue length weight coefficients corresponding to each neighboring network node; and determining the normalized CPU utilization, maximum CPU utilization, and utilization weights corresponding to each neighboring network node. The coefficients are used to determine the CPU load cost value corresponding to each neighboring network node; the link quality cost value corresponding to each neighboring network node is determined based on the normalized link quality indicator value, maximum link quality indicator value, and link quality weight coefficient; the energy decay cost value corresponding to each neighboring network node is determined based on the normalized remaining energy decay rate and energy decay rate weight coefficient; and the current heat index corresponding to each neighboring network node is determined based on the queue congestion cost value, CPU load cost value, link quality cost value, and energy decay cost value.

[0044] For example, the current popularity index corresponding to each neighboring network node can be determined using the following specific calculation formula: .

[0045] in, This represents the current popularity index. , The larger the value, the closer the node is to a congested or unstable state; This represents the normalized length of the queue of tasks awaiting transmission. The maximum queue length, This is the queue length weighting coefficient. Cost of queue congestion; This represents the normalized CPU utilization rate. To maximize CPU utilization, This is the utilization rate weighting coefficient. Cost of CPU load; This is the normalized link quality indicator value. This is the maximum link quality indicator value. This is the link quality weighting coefficient. Cost of link quality; The normalized residual energy decay rate, This is the weighting coefficient for energy decay rate. The cost of energy decay; .

[0046] By implementing the above settings, the limitations of traditional OLSR protocols, which rely solely on connectivity for multi-point relay node selection, are overcome. Node load, energy, and link quality are integrated into a "heat" indicator, enabling precise quantitative perception of network congestion status and thus improving data transmission efficiency.

[0047] Optionally, a sliding time window mechanism can be used to dynamically update the weight coefficients to adapt to the dynamic changes in the network state, making it more timely.

[0048] S240. Based on the current popularity index corresponding to each neighboring network node, determine multiple multi-point relay nodes among each neighboring network node.

[0049] Optionally, based on the current popularity index corresponding to each neighboring network node, multiple multi-point relay nodes are determined among each neighboring network node, including: determining the number of two-hop neighbor nodes corresponding to each neighboring network node based on the two-hop neighbor set corresponding to each neighboring network node; sorting the number of two-hop neighbor nodes to obtain the maximum number of two-hop neighbor nodes; determining the fitness value corresponding to each neighboring network node based on the current popularity index, the number of two-hop neighbor nodes, and the maximum number of two-hop neighbor nodes corresponding to each neighboring network node; and determining multiple multi-point relay nodes among each neighboring network node based on the fitness value corresponding to each neighboring network node.

[0050] For example, the fitness value corresponding to each neighboring network node can be determined using the following specific calculation formula: .

[0051] in, Neighbor network nodes fitness value; Neighbor network nodes The set of two-hop neighbors; The number of two-hop neighbor nodes contained in the two-hop neighbor set; This represents the maximum number of two-hop neighbor nodes, which is the maximum number of two-hop neighbor nodes among all neighbor network nodes. It can be used to normalize the coverage of two-hop neighbor nodes. Neighbor network nodes The current popularity index; and For a predefined balance coefficient, , and It can be used to adjust the relative importance of two-hop neighbor node coverage and current heat index in the fitness function.

[0052] After determining the fitness values ​​corresponding to each neighboring network node, neighboring network nodes with fitness values ​​greater than the preset fitness threshold can be used as multi-point relay nodes to ensure that the selected multi-point relay nodes can effectively spread routing information and are not prone to congestion.

[0053] Optionally, a dynamic threshold mechanism can be introduced to adaptively adjust the threshold value in the fitness function based on the overall network load. and .

[0054] S250. Based on the priority of the data stream to be forwarded corresponding to the task to be transmitted, determine the next-hop node corresponding to the current network node in each multi-point relay node, and send the data stream to be forwarded to the next-hop node to complete the task to be transmitted.

[0055] Optionally, based on the priority of the data stream to be forwarded corresponding to the task to be transmitted, the next-hop node corresponding to the current network node is determined among the multi-point relay nodes, including: when the priority of the data stream to be forwarded is the first priority, the multi-point relay node with the lowest current popularity index is taken as the next-hop node; when the priority of the data stream to be forwarded is the second priority, a preset load balancing strategy is adopted to determine multiple next-hop nodes among the multi-point relay nodes; the second priority is lower than the first priority.

[0056] Specifically, when the priority of the data stream to be forwarded is the second priority, a preset load balancing strategy can be adopted to distribute the data stream to be forwarded to multiple next-hop nodes, so as to avoid all traffic from flooding to a few "cold" nodes and thus creating new "hot spots".

[0057] S260. When a current network node carries multiple tasks to be transmitted, construct an objective function that aims to minimize the latency load cost of each task to be transmitted.

[0058] In this step, specifically, in order to achieve lower latency for high-priority tasks and to avoid forwarding data packets to congested paths as much as possible, we can comprehensively consider the transmission latency, maximum heat index, and congestion penalty coefficient of the tasks to be transmitted on each data transmission path, and construct an objective function with the goal of minimizing the latency load cost of each task to be transmitted.

[0059] Optionally, an objective function is constructed to minimize the latency load cost of each task to be transmitted, including: constructing an objective function based on the following formula to minimize the latency load cost of each task to be transmitted: .

[0060] in, Let be the objective function. for At this moment The task priority of each pending transmission task. for At this moment The task to be transmitted is in the first Transmission delay on each data transmission path for At this moment The task to be transmitted is in the first The maximum heat index on each data transmission path This is a predefined congestion penalty coefficient.

[0061] S270. Obtain multiple data transmission paths corresponding to the current network node, as well as the task priority of each task to be transmitted, and determine the transmission delay of each task to be transmitted on each data transmission path, and the maximum heat index corresponding to each data transmission path.

[0062] Specifically, in this step, the transmission latency of each task to be transmitted on each data transmission path can be predicted at future times based on multiple sets of historical transmission latency over historical time periods. Simultaneously, an Autoregressive Moving Average (ARMA) model can be used to predict the future popularity index of each network node on each data transmission path at future times, and the largest of these future popularity indices corresponding to each data transmission path can be selected as the maximum popularity index for each data transmission path.

[0063] Optionally, the task priority of each task to be transmitted is obtained, including: determining the update priority corresponding to each task to be transmitted based on the initial priority, queue dwell time and task urgency corresponding to each task to be transmitted; and using the update priority corresponding to each task to be transmitted as the task priority corresponding to each task to be transmitted.

[0064] Specifically, the remaining time before each task to be transmitted can be determined based on its respective deadline. Then, the urgency of each task can be determined based on its remaining time before the deadline. A shorter remaining time indicates higher urgency. Finally, the initial priority of each task can be adjusted based on its queue dwell time and urgency, resulting in an updated priority. The queue dwell time can be understood as the duration a task resides in the task queue.

[0065] Optionally, based on the initial priority, queue dwell time, and task urgency corresponding to each task to be transmitted, the update priority corresponding to each task to be transmitted is determined, including: determining the update priority corresponding to each task to be transmitted based on the following formula: .

[0066] in, For the first One pending transmission task Update priority at any time For the first One pending transmission task Initial priority of time, For the first The deadline for pending transmission tasks is [date / time]. The queue dwell time at any given moment. For the first One pending transmission task The urgency of the task at any moment For the first The deadline for the pending transmission tasks is... The number of retransmissions at any given moment. and This is a predefined adjustment coefficient.

[0067] The advantages of this setup are twofold: First, compared to existing technologies that use first-in-first-out (FIFO) or fixed-priority strategies to determine the priority of tasks to be transmitted, this approach exponentially increases the priority of tasks when their dwell time is too long. It allows for differentiated path selection based on the urgency of the service content, thus ensuring the timeliness of data transmission. Second, by increasing the weight of continuously unscheduled low-priority data packets using a logarithmic function, it prevents low-priority tasks from being unable to obtain channel resources for extended periods. This effectively solves the starvation problem of low-priority services under sustained high load, ensuring fairness in network services.

[0068] Optionally, it can be dynamically adjusted based on the type of business (such as real-time control and batch transmission). , and To optimize fairness in different scenarios.

[0069] S280. Substitute the task priority of each task to be transmitted, the transmission delay of each task to be transmitted on each data transmission path, and the maximum heat index corresponding to each data transmission path into the objective function to obtain the delay load cost of each task to be transmitted on each data transmission path.

[0070] In this step, specifically, the task priority of each task to be transmitted, the transmission delay of each task to be transmitted on each data transmission path, and the maximum heat index corresponding to each data transmission path can be substituted into the objective function. Then, integer programming or heuristic algorithms can be used to solve the objective function to obtain the delay load cost of each task to be transmitted on each data transmission path.

[0071] S290. Based on the latency load cost of each task to be transmitted on each data transmission path, determine the optimal transmission path corresponding to each task to be transmitted, and execute each task to be transmitted according to the optimal transmission path corresponding to each task to be transmitted.

[0072] In this step, specifically, a task allocation matrix corresponding to each task to be transmitted can be generated based on the latency load cost of each task on each data transmission path, so as to ensure that high-priority tasks are preferentially allocated to low-load paths.

[0073] The advantage of this setup is that it uses the ARMA model to predict network load trends and breaks down a single task flow and distributes it in parallel to multiple available paths, which not only improves throughput but also effectively avoids local node overheating.

[0074] Optionally, a distributed scheduling strategy can be adopted, in which each network node independently calculates the task allocation scheme, thereby reducing the communication overhead caused by centralized scheduling.

[0075] The technical solution of this embodiment constructs an objective function aimed at minimizing the latency load cost of each task when the current network node carries multiple tasks to be transmitted; obtains multiple data transmission paths corresponding to the current network node, as well as the task priorities of each task to be transmitted, and determines the transmission latency of each task on each data transmission path, and the maximum heat index corresponding to each data transmission path; substitutes the task priorities of each task, the transmission latency of each task on each data transmission path, and the maximum heat index corresponding to each data transmission path into the objective function to obtain the latency load cost of each task on each data transmission path; determines the optimal transmission path corresponding to each task based on the latency load cost of each task on each data transmission path, and executes each task according to the optimal transmission path corresponding to each task. This can decompose a single task flow and distribute it in parallel to multiple available paths, thereby achieving highly reliable and low-latency data transmission in a low-quality-of-service network environment.

[0076] Example 3 Figure 3 This is a schematic diagram of a heat-sensing-based data transmission device according to Embodiment 3 of the present invention. This embodiment is applicable to the situation of data transmission between multiple network nodes. The heat-sensing-based data transmission device can be implemented in hardware and / or software and can be configured in electronic devices such as computers.

[0077] like Figure 3 As shown, the heat-sensing-based data transmission device disclosed in this embodiment includes: a neighbor node acquisition module 31, a heat index determination module 32, a relay node determination module 33, a next-hop node determination module 34, and a task execution module 35.

[0078] The neighbor node acquisition module 31 is used to acquire the current network node that carries the task to be transmitted, and when the current network node carries only a single task to be transmitted, acquire each neighbor network node corresponding to the current network node.

[0079] The heat index determination module 32 is used to determine the current heat index corresponding to each neighboring network node based on the multi-dimensional state parameters corresponding to each neighboring network node.

[0080] The relay node determination module 33 is used to determine multiple multi-point relay nodes among the neighboring network nodes based on the current popularity index corresponding to each neighboring network node.

[0081] The next-hop node determination module 34 is used to determine the next-hop node corresponding to the current network node among the multi-point relay nodes according to the priority of the data stream to be forwarded corresponding to the task to be transmitted.

[0082] The task execution module 35 is used to send the data stream to be forwarded to the next hop node to complete the transmission task.

[0083] The technical solution in this embodiment, through the cooperation of the neighbor node acquisition module 31, the heat index determination module 32, the relay node determination module 33, the next-hop node determination module 34, and the task execution module 35, solves the problem that the existing technology relies solely on the node connectivity index to select multiple relay nodes, which easily leads to hotspots in the network core nodes due to excessive relay tasks, thereby causing buffer overflow and loss of critical data. The solution improves the selection accuracy of multiple relay nodes, avoids network congestion, and ensures the data transmission efficiency between network nodes.

[0084] Optionally, the heat index determination module 32 is specifically used to: determine the queue congestion cost, CPU load cost, link quality cost, and energy attenuation cost corresponding to each neighboring network node based on the multi-dimensional state parameters corresponding to each neighboring network node; wherein, the multi-dimensional state parameters include the queue length of the task to be transmitted, CPU utilization, link quality indicator value, and remaining energy attenuation rate; and determine the current heat index corresponding to each neighboring network node based on the queue congestion cost, CPU load cost, link quality cost, and energy attenuation cost corresponding to each neighboring network node.

[0085] Optionally, the relay node determination module 33 is specifically used for: determining the number of two-hop neighbor nodes corresponding to each neighbor network node based on the two-hop neighbor set corresponding to each neighbor network node; sorting the number of two-hop neighbor nodes to obtain the maximum number of two-hop neighbor nodes; determining the fitness value corresponding to each neighbor network node based on the current popularity index, the number of two-hop neighbor nodes, and the maximum number of two-hop neighbor nodes corresponding to each neighbor network node; and determining multiple multi-point relay nodes among each neighbor network node based on the fitness value corresponding to each neighbor network node.

[0086] Optionally, the next-hop node determination module 34 is specifically used for: when the priority of the data stream to be forwarded is the first priority, taking the multi-point relay node with the lowest current popularity index as the next-hop node; when the priority of the data stream to be forwarded is the second priority, adopting a preset load balancing strategy to determine multiple next-hop nodes among the multi-point relay nodes; the second priority is lower than the first priority.

[0087] Optionally, the device further includes a task parallelization module, which comprises: a function construction unit, used to construct an objective function aimed at minimizing the latency load cost of each task to be transmitted when the current network node carries multiple tasks to be transmitted; a parameter acquisition unit, used to acquire multiple data transmission paths corresponding to the current network node, as well as the task priority of each task to be transmitted, and determine the transmission latency of each task to be transmitted on each data transmission path, and the maximum heat index corresponding to each data transmission path; a cost determination unit, used to substitute the task priority of each task to be transmitted, the transmission latency of each task to be transmitted on each data transmission path, and the maximum heat index corresponding to each data transmission path into the objective function to obtain the latency load cost of each task to be transmitted on each data transmission path; an optimal path determination unit, used to determine the optimal transmission path corresponding to each task to be transmitted based on the latency load cost of each task to be transmitted on each data transmission path; and a task execution unit, used to execute each task to be transmitted based on the optimal transmission path corresponding to each task to be transmitted.

[0088] Optionally, the function building unit is specifically used to: construct an objective function based on the following formula, with the goal of minimizing the latency load cost of each task to be transmitted: .

[0089] in, Let be the objective function. For the first The task priority of each pending transmission task. For the first The task to be transmitted is in the first Transmission delay on each data transmission path For the first The task to be transmitted is in the first The maximum heat index on each data transmission path This is a predefined congestion penalty coefficient.

[0090] Optionally, the parameter acquisition unit includes: an update priority determination subunit, used to determine the update priority corresponding to each task to be transmitted based on the initial priority, queue dwell time and task urgency corresponding to each task to be transmitted; and a task priority determination subunit, used to use the update priority corresponding to each task to be transmitted as the task priority corresponding to each task to be transmitted.

[0091] Optionally, the update priority determination subunit is used to: determine the update priority corresponding to each task to be transmitted based on the following formula: .

[0092] in, For the first One pending transmission task Update priority at any time For the first One pending transmission task Initial priority of time, For the first The deadline for the pending transmission tasks is... The queue dwell time at any given moment. For the first The urgency of each pending transmission task For the first The deadline for the pending transmission tasks is... The number of retransmissions at any given moment. and This is a predefined adjustment coefficient.

[0093] The heat-sensing-based data transmission device provided in this embodiment of the invention can execute the heat-sensing-based data transmission method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method execution. Content not described in detail in this embodiment can be referred to the description in any method embodiment of this application.

[0094] Example 4 Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement embodiments of the present invention is shown. For example... Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory 12 or a random access memory 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the read-only memory 12 or loaded from storage unit 18 into the random access memory 13. The random access memory 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, read-only memory 12, and random access memory 13 are interconnected via a bus 14. An input / output interface 15 is also connected to the bus 14.

[0095] Multiple components in electronic device 10 are connected to input / output interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of monitors, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0096] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as heat-aware data transfer methods.

[0097] In some embodiments, the heat-aware data transfer method can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via read-only memory 12 and / or communication unit 19. When the computer program is loaded into random access memory 13 and executed by processor 11, one or more steps of the heat-aware data transfer method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the heat-aware data transfer method by any other suitable means (e.g., by means of firmware).

[0098] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0099] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0100] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0101] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0102] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0103] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0104] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0105] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A data transmission method based on heat sensing, characterized in that, The heat-sensing-based data transmission method includes: Obtain the current network node carrying the task to be transmitted, and when the current network node only carries a single task to be transmitted, obtain each neighboring network node corresponding to the current network node; Based on the multi-dimensional state parameters corresponding to each of the neighboring network nodes, determine the current popularity index corresponding to each of the neighboring network nodes. Based on the current popularity index corresponding to each of the neighboring network nodes, a number of multi-point relay nodes are determined among the neighboring network nodes. Based on the priority of the data stream to be forwarded corresponding to the task to be transmitted, the next hop node corresponding to the current network node is determined among the multi-point relay nodes; The data stream to be forwarded is sent to the next-hop node to complete the transmission task.

2. The data transmission method based on heat sensing according to claim 1, characterized in that, Based on the multi-dimensional state parameters corresponding to each of the neighboring network nodes, the current popularity index corresponding to each of the neighboring network nodes is determined, including: Based on the multi-dimensional state parameters corresponding to each of the neighboring network nodes, determine the queue congestion cost, CPU load cost, link quality cost, and energy attenuation cost corresponding to each of the neighboring network nodes. The multidimensional state parameters include the length of the task queue to be transmitted, CPU utilization, link quality indicator value, and remaining energy attenuation rate. Based on the queue congestion cost, CPU load cost, link quality cost, and energy attenuation cost corresponding to each of the neighboring network nodes, the current popularity index corresponding to each of the neighboring network nodes is determined.

3. The data transmission method based on heat sensing according to claim 1, characterized in that, Based on the current popularity index corresponding to each of the neighboring network nodes, multiple multi-point relay nodes are determined among the neighboring network nodes, including: The number of two-hop neighbor nodes corresponding to each of the neighbor network nodes is determined based on the two-hop neighbor set corresponding to each of the neighbor network nodes. Sort the number of two-hop neighbor nodes for each of the above methods to obtain the maximum number of two-hop neighbor nodes; Based on the current popularity index, the number of two-hop neighbor nodes, and the maximum number of two-hop neighbor nodes corresponding to each of the neighbor network nodes, determine the fitness value corresponding to each of the neighbor network nodes; Based on the fitness values ​​corresponding to each of the neighboring network nodes, multiple multipoint relay nodes are determined among the neighboring network nodes.

4. The data transmission method based on heat sensing according to claim 1, characterized in that, Based on the priority of the data stream to be forwarded corresponding to the task to be transmitted, the next-hop node corresponding to the current network node is determined among the multi-point relay nodes, including: When the priority of the data stream to be forwarded is the first priority, the multi-point relay node with the lowest current popularity index is taken as the next hop node. When the priority of the data stream to be forwarded is the second priority, a preset load balancing strategy is adopted to determine multiple next-hop nodes in each of the multi-point relay nodes; the second priority is lower than the first priority.

5. The data transmission method based on heat sensing according to claim 1, characterized in that, After obtaining the current network node carrying the task to be transmitted, the process also includes: When the current network node carries multiple tasks to be transmitted, an objective function is constructed with the goal of minimizing the latency load cost of each task to be transmitted. Obtain multiple data transmission paths corresponding to the current network node, as well as the task priority of each task to be transmitted, and determine the transmission delay of each task to be transmitted on each data transmission path, and the maximum heat index corresponding to each data transmission path respectively. Substituting the task priority of each task to be transmitted, the transmission delay of each task to be transmitted on each data transmission path, and the maximum heat index corresponding to each data transmission path into the objective function, the latency load cost of each task to be transmitted on each data transmission path is obtained. Based on the latency load cost of each of the tasks to be transmitted on each of the data transmission paths, determine the optimal transmission path corresponding to each of the tasks to be transmitted. Each of the tasks to be transmitted is executed according to the optimal transmission path corresponding to each of the tasks to be transmitted.

6. The data transmission method based on heat sensing according to claim 5, characterized in that, Construct an objective function that minimizes the latency load cost of each of the tasks to be transmitted, including: The objective function is constructed based on the following formula, with the goal of minimizing the latency load cost of each of the tasks to be transmitted: ； in, Let be the objective function. For the first The task priority of each pending transmission task. For the first The task to be transmitted is in the first Transmission delay on each data transmission path For the first The task to be transmitted is in the first The maximum heat index on each data transmission path This is a predefined congestion penalty coefficient.

7. The data transmission method based on heat sensing according to claim 5, characterized in that, Obtaining the task priority of each of the tasks to be transmitted includes: Based on the initial priority, queue dwell time, and task urgency corresponding to each of the tasks to be transmitted, the update priority corresponding to each of the tasks to be transmitted is determined. The update priority corresponding to each of the tasks to be transmitted is used as the task priority corresponding to each of the tasks to be transmitted.

8. The data transmission method based on heat sensing according to claim 7, characterized in that, Based on the initial priority, queue dwell time, and task urgency corresponding to each of the tasks to be transmitted, the update priority corresponding to each of the tasks to be transmitted is determined, including: The update priority corresponding to each of the tasks to be transmitted is determined based on the following formula: ； in, For the first One pending transmission task Update priority at any time For the first One pending transmission task Initial priority of time, For the first The deadline for the pending transmission tasks is... The queue dwell time at any given moment. For the first The urgency of each pending transmission task For the first The deadline for the pending transmission tasks is... The number of retransmissions at any given moment. and This is a predefined adjustment coefficient.

9. A data transmission device based on heat sensing, characterized in that, The heat-sensing-based data transmission device includes: The neighbor node acquisition module is used to acquire the current network node that carries the task to be transmitted, and when the current network node carries only a single task to be transmitted, acquire each neighbor network node corresponding to the current network node. The heat index determination module is used to determine the current heat index corresponding to each of the neighboring network nodes based on the multi-dimensional state parameters corresponding to each of the neighboring network nodes. The relay node determination module is used to determine multiple multi-point relay nodes among the neighboring network nodes based on the current heat index corresponding to each of the neighboring network nodes. The next-hop node determination module is used to determine the next-hop node corresponding to the current network node among the multi-point relay nodes according to the priority of the data stream to be forwarded corresponding to the task to be transmitted; The task execution module is used to send the data stream to be forwarded to the next hop node to complete the transmission task.

10. An electronic device, characterized in that, The electronic device includes: At least one processor, and a memory communicatively connected to said at least one processor; The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the heat-sensing-based data transmission method according to any one of claims 1-8.

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