Task-driven distributed multi-functional sensor system resource management method
By designing a task-driven distributed multifunctional sensor system resource management method, the timing of function switching and the number of nodes were determined, which solved the problem of insufficient research on task-driven approaches in sensor resource management and achieved efficient resource allocation and performance improvement.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SOUTHWEST CHINA RES INST OF ELECTRONICS EQUIP
- Filing Date
- 2023-03-24
- Publication Date
- 2026-05-12
AI Technical Summary
In the existing technology, there is a lack of research on task-driven sensor resource management, and it has failed to effectively optimize sensor resource configuration to meet task requirements.
A task-driven distributed multifunctional sensor system resource management method is adopted. By acquiring task information, designing function switching timing, determining the minimum number of nodes, and optimizing resource configuration to meet task performance requirements.
It enables efficient allocation of sensor resources based on task information, meeting task performance requirements while reducing resource consumption and improving system performance.
Smart Images
Figure CN116489026B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of multifunctional sensor system technology, and in particular to a task-driven distributed multifunctional sensor system resource management method and system. Background Technology
[0002] Distributed multifunctional sensor systems possess numerous advantages and have become a research hotspot both domestically and internationally in recent years. In practice, sensors often face multi-tasking scenarios, where resource management techniques can be used to optimize the configuration and scheduling of sensor resources, thereby improving their performance. Sensor resource management can be categorized into two types based on its purpose: resource-driven and task-driven.
[0003] Resource-driven sensor resource management refers to optimizing the configuration and scheduling of sensor resources, given their types and quantities, and combining this with task information, to maximize system performance. Task-driven management, on the other hand, involves given task information and corresponding expected performance metrics, and then optimizing the design to find the minimum resource consumption required to achieve the desired performance and its specific configuration and scheduling scheme.
[0004] Existing research findings, both domestically and internationally, can generally be categorized as resource-driven. This involves optimizing resource allocation given a total amount of resources (including the number of nodes, their locations, transmission power, and the number of beams) to maximize the system's resource potential and improve sensor performance (e.g., coverage of the monitored area, target tracking accuracy, and positioning error of radiation sources). However, task-driven sensor resource management has received less attention, and related research is still in its early stages. A search of relevant patent databases has not revealed any other solutions to this problem. Summary of the Invention
[0005] To address the aforementioned shortcomings, this invention proposes a distributed multi-functional sensor resource management method based on function switching timing. This method can quantitatively calculate the minimum resource consumption required to meet the expected performance of a task, based on specific task information and performance requirements.
[0006] To achieve the above objectives, the present invention employs a task-driven distributed multifunctional sensor system resource management method, the method comprising the following steps:
[0007] S1: Initial stage, obtain task information, and determine the task type and quantity;
[0008] S2: Compress the number of tasks based on sensor capabilities;
[0009] S3: Based on the task parameter information compressed in S2 and combined with the target time performance preference, design the function switching timing using the cycle expansion method;
[0010] S4: Determine the minimum number of nodes required based on the timing design in S3;
[0011] S5: If changes in the environment or situational information lead to changes in the task, return to S1; if the task information remains unchanged, continue executing S4.
[0012] Optionally, in step S1, the task type specifically includes one or more of the following: reconnaissance of key frequency bands, detection of key areas, reconnaissance of non-key frequency bands, detection of non-key areas, and communication.
[0013] Optionally, step S2 specifically includes: if the sensor has sufficient transmission power and multi-beam capability, it can simultaneously detect multiple key areas, and then the detection tasks of multiple key areas are merged into one task.
[0014] Optionally, step S2 can also be used for other reconnaissance, target tracking, communication, and navigation missions.
[0015] Optionally, in step S3, the target time performance preference specifically includes one or more of the following: different task execution time duty cycles and situation information refresh rates.
[0016] Optionally, step S4 specifically includes:
[0017] The number of nodes starts from 1 and increments sequentially;
[0018] For the Nth accumulation, there are N nodes. The first node starts working according to the function switching sequence from time 0. The second node works according to the function switching sequence after a delay of 1 dwell time. The third node works after a delay of 2 dwell times, and so on.
[0019] The sum of the timings of all nodes is the overall system timing. Based on the overall timing, the execution time ratio of different tasks is calculated to see if it meets the requirements. If it does, the current number of nodes, their numbers, and the function switching timing are output. Otherwise, the number of nodes is increased until the requirements are met.
[0020] To achieve the above objectives, this application also provides a task-driven distributed multifunctional sensor system resource management system, the system comprising:
[0021] The acquisition module is used in the initial stage to acquire task information and determine the task type and quantity.
[0022] The compression module is used to compress the number of tasks based on the sensor's capabilities;
[0023] The design module is used to design the function switching timing based on the compressed task parameter information and the target time performance preference using the cycle expansion method.
[0024] The determination module is used to determine the minimum number of nodes required based on the design timing.
[0025] The loop module is used to reacquire task information if changes in environment or situational information lead to changes in the task; otherwise, it continuously determines the minimum number of nodes required.
[0026] Compared with existing technologies, the present invention offers the following advantages: a task-driven resource management method for distributed multifunctional sensor systems. The distributed sensor system consists of nodes with a unified time reference (achieved through atomic clocks, navigation satellite timing, etc.) and identical parameters; all nodes have the same system performance indicators. This method designs function switching sequences based on task information, then determines the minimum number of nodes required to meet the task's duty cycle requirements. Each node then collaborates in a staggered manner according to the unified timing sequence, satisfying task requirements while minimizing node resource consumption. Attached Figure Description
[0027] Figure 1 This is a flowchart of a task-driven, distributed, multi-functional sensor system resource management method.
[0028] Figure 2 This is a schematic diagram of a resource management scheme for a situation where N=1, 25% duty cycle node performance is insufficient, and tasks cannot be merged.
[0029] Figure 3 This is a schematic diagram of a resource management scheme for a situation where N=2, 50% duty cycle, node performance is insufficient, and tasks cannot be merged.
[0030] Figure 4 This is a schematic diagram of a resource management scheme for a situation where N=3 nodes have insufficient performance and tasks cannot be merged due to 75% duty cycle.
[0031] Figure 5 This is a schematic diagram of a resource management scheme for a situation where N=4, 100% duty cycle, node performance is insufficient, and tasks cannot be merged.
[0032] Figure 6 This is a schematic diagram of the task merging process;
[0033] Figure 7 This is a schematic diagram of a system resource management scheme that ensures 100% duty cycle for tasks in key areas and frequency bands.
[0034] Figure 8 This is a schematic diagram of a system resource management scheme that ensures 100% duty cycle for three types of tasks: key areas, key frequency bands, and sharing situational information.
[0035] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation
[0036] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
[0037] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.
[0038] A distributed sensor system consists of nodes with a unified time reference (achieved through technologies such as atomic clocks and navigation satellite timing) and identical parameters. All nodes have the same system performance parameters. Nodes can switch between different functions in a time-sharing manner, and each node can independently choose to perform transmit and receive operations simultaneously (for example, when node N-1 is in the receiving state, node N can freely choose to receive or transmit as needed without interference). It is assumed that the dwell time for each function is the same, Td.
[0039] Furthermore, in practice, the performance of any sensor is based on whether it meets requirements in two dimensions: spatial and temporal. Spatially, this means the detected environment or target must be within the sensor's effective range; otherwise, the sensor fails. Temporally, any task requires a certain amount of time to execute; tasks that don't consume any time are simply unexecuted tasks, and therefore have no performance implications. This patent focuses on the temporal dimension, using the task execution time duty cycle as the expected performance indicator to configure node resources in a distributed sensor system. The definition of this indicator is given below:
[0040]
[0041] Generally speaking, the longer the duty cycle of a task execution time, the more time it consumes, and the better the importance of the task and the corresponding performance indicators (for example, when radar detects a target, the longer the echo accumulation time, the higher the signal-to-noise ratio and the farther the detection range; when tracking a target, the more frequent the revisit, the more even the track and the higher the accuracy).
[0042] Based on this definition, task-driven distributed multifunctional sensor system resource management mainly includes the following five steps for ease of understanding. Figure 1 A flowchart of the steps is provided:
[0043] Step 1: Initial stage, obtain mission information and determine mission type and quantity (e.g., reconnaissance of key frequency bands, detection of key areas, reconnaissance of non-key frequency bands, detection of non-key areas, communication, etc.).
[0044] Step 2: Based on sensor capabilities, reduce the number of tasks (for example, if the sensor has sufficient transmission power and multi-beam capability, it can detect multiple key areas simultaneously, so the detection tasks of multiple key areas can be combined into one task; other reconnaissance, target tracking, communication, navigation and other tasks can be deduced by analogy).
[0045] Step 3: Based on the compressed task parameter information from Step 2, and combined with our time performance preferences (such as the duty cycle of different task execution times, situation information refresh rate, etc.), design the function switching timing using the periodic expansion method. The periodic expansion method is referenced from "Yang Yichuan, Wang Haoru, et al. Optimization Algorithm for Electronic Reconnaissance Time-Frequency Scanning Scheme Oriented to Resource Saturation [J]. Modern Radar, 2022".
[0046] Step 4: Determine the minimum number of nodes required based on the timing sequence designed in Step 3. Specifically, the number of nodes starts from 1 and increments sequentially. For the Nth increment, there are N nodes. The first node starts working according to the function switching timing sequence from time 0, the second node works according to the function switching timing sequence after a delay of 1 dwell time, the third node works after a delay of 2 dwell times, and so on. The timing sequences of all nodes are superimposed to form the overall system timing sequence. Based on the overall timing sequence, calculate whether the execution time ratio of different tasks meets the requirements. If the requirements are met, output the current number of nodes, their numbers, and the function switching timing sequence; otherwise, continue to increase the number of nodes until the requirements are met.
[0047] Step 5: If changes in the environment or situational information lead to changes in the task, return to step 1; if the task information remains unchanged, continue executing step 4.
[0048] In a specific example, suppose the system needs to perform six tasks simultaneously: detection of key area 1, detection of key area 2, reconnaissance of key frequency bands, detection of non-key areas, reconnaissance of non-key frequency bands, and reporting and sharing situational data via wireless communication.
[0049] First, assume that the sensor node has limited capabilities and can only execute one of the six tasks mentioned above at any given time. The current situation requires that the duty cycle of the three tasks—detection of key area 1, detection of key area 2, and reconnaissance of key frequency bands—must reach 100%, while the duty cycle of the other tasks is not required. At this point, from... Figures 2-5 As can be seen from the function switching sequence, when the number of nodes is 1, the system's multi-function timing is the same as that of node 1, and the task duty cycle is only 25%. When the number of nodes is 2, the system's multi-function timing is the superposition of the timing of node 1 and node 2, and the task duty cycle increases to 50%. The same logic applies to nodes 3 and 4. Only when the number of nodes increases to 4 can the execution time duty cycle of the two key area detection tasks be increased to 100%.
[0050] And inFigures 6-7 In this scenario, assuming the node has strong capabilities (possessing multi-beam capability and sufficient transmission power), it can simultaneously perform detection tasks on key areas 1 and 2. In this case, the two tasks can be combined into one task, and only 3 nodes are needed to meet the requirement of 100% duty cycle for the execution of key area detection and key frequency band reconnaissance tasks.
[0051] Finally, assuming that situational data obtained from key area detection and key frequency band reconnaissance needs to be reported / shared in real time, the duty cycle of the communication task execution time must also be 100%. At this point, from... Figure 8 It can be seen that after redesigning the functional timing and merging the two key area detection tasks (assuming that the system nodes can simultaneously execute the detection tasks of key areas 1 and 2), the entire system requires 4 nodes to achieve a 100% duty cycle for the execution time of key area detection, key frequency band reconnaissance, and communication tasks (reporting / distributing situational data).
[0052] This embodiment targets a distributed multi-functional sensor system composed of multiple equipment nodes with identical functions and parameters (each node utilizes technologies such as atomic clocks and navigation satellite timing to have a unified time reference). First, based on the mission information, a multi-functional switching sequence is designed. Then, the minimum number of sensor nodes required to meet performance requirements is calculated. Finally, a sensor node resource configuration scheme with minimal resource consumption is output to support operators or users in configuring sensor resources.
[0053] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.
[0054] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.
[0055] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.
[0056] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.
Claims
1. A task-driven resource management method for a distributed multifunctional sensor system, characterized in that, The method includes the following steps: S1: Initial stage, obtain task information, and determine the task type and quantity; S2: Compress the number of tasks based on sensor capabilities; S3: Based on the task parameter information compressed in S2 and combined with the target time performance preference, design the function switching timing using the cycle expansion method; S4: Determine the minimum number of nodes required based on the timing design in S3; S5: If changes in the environment or situational information lead to changes in the task, return to S1; if the task information remains unchanged, continue executing S4. Specifically, S4 includes: The number of nodes starts from 1 and increments sequentially; For the Nth accumulation, there are N nodes. The first node starts working according to the function switching sequence from time 0. The second node works according to the function switching sequence after a delay of 1 dwell time. The third node works after a delay of 2 dwell times, and so on. The sum of the timings of all nodes is the overall system timing. Based on the overall timing, the execution time ratio of different tasks is calculated to see if it meets the requirements. If it does, the current number of nodes, their numbers, and the function switching timing are output. Otherwise, the number of nodes is increased until the requirements are met.
2. The task-driven distributed multifunctional sensor system resource management method as described in claim 1, characterized in that, In step S1, the specific task types include one or more of the following: reconnaissance of key frequency bands, detection of key areas, reconnaissance of non-key frequency bands, detection of non-key areas, and communication.
3. The task-driven distributed multifunctional sensor system resource management method as described in claim 1, characterized in that, Step S2 specifically includes: when the sensor has sufficient transmission power and multi-beam capability, it can simultaneously detect multiple key areas, and then the detection tasks of multiple key areas are merged into one task.
4. The task-driven distributed multifunctional sensor system resource management method as described in claim 1, characterized in that, Step S2 is also used for other reconnaissance, target tracking, communication, and navigation missions.
5. The task-driven distributed multifunctional sensor system resource management method as described in claim 1, characterized in that, In step S3, the target time performance preference specifically includes one or more of the following: duty cycle of different task execution times and situation information refresh rate.
6. A task-driven distributed multi-functional sensor system resource management system, characterized in that, The system includes: The acquisition module is used in the initial stage to acquire task information and determine the task type and quantity. The compression module is used to compress the number of tasks based on the sensor's capabilities; The design module is used to design the function switching timing based on the compressed task parameter information and the target time performance preference using the cycle expansion method. The determination module is used to determine the minimum number of nodes required based on the design timing. The loop module is used to reacquire task information if changes in environment or situational information lead to changes in the task; otherwise, it continuously determines the minimum number of nodes required. Determining the minimum number of nodes required based on the design timing includes: The number of nodes starts from 1 and increments sequentially; For the Nth accumulation, there are N nodes. The first node starts working according to the function switching sequence from time 0. The second node works according to the function switching sequence after a delay of 1 dwell time. The third node works after a delay of 2 dwell times, and so on. The sum of the timings of all nodes is the overall system timing. Based on the overall timing, the execution time ratio of different tasks is calculated to see if it meets the requirements. If it does, the current number of nodes, their numbers, and the function switching timing are output. Otherwise, the number of nodes is increased until the requirements are met.