Collaborative task node allocation method based on network topology and preference sorting algorithm

Abstract

The invention discloses a collaborative task node allocation method based on network topology and a preference sorting algorithm, which converts a task node allocation problem into an optimization problem which enables task execution income to be maximum and participates in the minimum total node number, and then solves the optimization problem by using a heuristic method. According to the optimization problem, task requirements of different priorities are considered, space topology and network topology constraints between nodes are considered at the same time, and reasonable modeling is conducted on a real multi-task node distribution scene. The heuristic solution process fully considers the requirements of tasks on nodes, avoids tedious iteration trial and error, is good in effectiveness, and can meet the requirements of actual formation node distribution.

Description

Technical Field

[0001] The invention relates to a task node allocation method. Background Art

[0002] Collaborative task allocation is an important part of complex environment tasks and is of great significance for the efficient execution of multi-node tasks. The key points of collaborative task allocation are the modeling of task allocation problems and the optimization solution of task allocation problems. Establishing a reasonable model is a description of the real task scenario and has an important impact on the efficiency of task execution. Among them, the mixed integer linear programming model is the most commonly used model, which expresses the task allocation problem in the form of an optimization problem as a multi-objective and multi-constrained optimization problem. The task allocation problem is an NP-complete problem, and the heuristic algorithm is an effective way to solve it. However, the existing task allocation method does not consider the original working mode of the node and the remaining bandwidth of the link between nodes, resulting in low node resource utilization and low task scheduling success rate.

[0003] Although existing research has proposed a variety of algorithms and models to optimize task allocation and resource scheduling, most methods mainly focus on specific scenarios and simplified network models, and the problem of building a general task allocation model still needs to be solved; although some algorithms can provide theoretical optimal solutions, they may be difficult to implement in practical applications due to their high computational complexity, especially when the network scale is growing rapidly; in addition, existing task allocation methods rarely consider the original working mode of the nodes and the remaining bandwidth of the links between nodes, resulting in a low task scheduling success rate and low node resource utilization. Therefore, in an environment with complex and diverse tasks, it is particularly important to fully explore and utilize the detection resources between nodes. Summary of the invention

[0004] In view of the fact that the existing task allocation method does not consider the original working mode of the node and the remaining bandwidth of the link between the nodes, there are low node resource utilization and low task scheduling success rate. The present invention proposes a collaborative task node allocation method based on network topology and preference sorting algorithm. The method considers the node working mode and the remaining bandwidth of the link between the nodes to allocate task nodes, so as to maximize the task execution benefit and minimize the number of occupied nodes, and includes the following steps:

[0005] Step 1: Based on the strategy of maximizing the task execution benefit and minimizing the total number of participating nodes, M tasks T1, T2, …, T M Assign tasks to nodes Node1, Node2, …, Node N The problem is converted into solving the participating task T m The node set S m Optimization problem, where M ≥ 1, N ≥ 2;

[0006] Step 2: Solve the optimization problem described in step 1 using a heuristic method based on satisfying the maximum number of tasks with the minimum number of nodes.

[0007] Furthermore, the optimization problem in step 1 above is in the form of:

[0008]

[0009] The node conditions and task requirements involved in the above optimization problem are as follows 1)-10):

[0010] 1) Node n The current working mode is w n , w n ∈{1,2};

[0011] 2) Node n The current working radius is r n ;

[0012] 3) Node n The spatial position of And assume that the position changes slowly over a period of time;

[0013] 4) Any two nodes i With Node j , whose spatial distance is D i,j ;

[0014] 5) Any two nodes i With Node j At most two communication links can be established simultaneously, that is, l∈{1,2}, where l=1 indicates a common link with a bandwidth of L. i,j , when l = 2, it indicates a high-speed link, and the allocated bandwidth is H i,j , if L i,j =0 or H i,j =0, it means that the corresponding link cannot be established;

[0015] 6) Task T m Priority is P m , the mission point or mission area center is Requirements: The minimum number of participating nodes is N m , N m =2; the working mode of each node is W m , W m ∈{0,1,2}, if W m = 0 means no requirement for the working mode; the working radius of each node covers the task point or the center of the task area; the spatial distance between any two nodes does not exceed D m ; The type of communication link between any two nodes is l m, l m ∈{1,2}, and link bandwidth B is required m ;

[0016] 7) The task execution benefit ε is defined as the sum of the priorities of all tasks that are successfully assigned enough nodes, that is, where 1(condition) is an indicator function and

[0017]

[0018] 8) The total number of participating nodes is

[0019] 9) Constraint C1 represents the set S m Node n Need to meet: working mode w n =W m ,if W m ≠0; the distance between the task point or the center of the task area and the node satisfies D n,m <r n ; Any two nodes Node i With Node j The distance between them satisfies D i,j <D m ;

[0020] 10) Constraints C2 and C3 represent the set S m Any two nodes in i With Node j The cumulative link bandwidth used during the period cannot exceed the link budget. m =1, requirement If l m =2, then the requirement Where η l and η h Indicates the overload level that the communication link can tolerate, η l =1.1,η h =1.1.

[0021] Furthermore, the steps of using the heuristic method based on the minimum number of nodes to meet the maximum task requirements in step 2 above are: first sort all tasks from high to low priority, and then take the current priority as P m Task T m , process it sequentially according to step 2-1 to step 2-2, and finally obtain the participating node set S of the current task m :

[0022] Step 2-1: Determine the candidate node set C for the current task D and candidate node pair sequence Q P , if successful, proceed to the next step, otherwise, skip the current task and continue to process the next priority task;

[0023] Step 2-2: Q P The first node pair in the i ,Node j ) as the candidate node pair for the current task, that is, S m ={Node i ,Node j}, and then update the link bandwidth margin between the two points to the remaining value after deducting the bandwidth required by the current task.

[0024] Furthermore, in step 2-1 above, a candidate node set C of the current priority task is constructed. D and candidate node pair sequence Q P The method specifically comprises the following steps:

[0025] Step 2-1-1: Set the working mode W m The mission point or mission area center must fall within the working radius r. n The required nodes are put into the candidate node set C W ; If the set C W If it is empty, then construct a set C D and candidate node pair sequence Q P fail;

[0026] Step 2-1-2: Traverse C W Node i With Node j , calculate the distance D i,j Does it satisfy D? i,j <D m , if satisfied, then (Node i ,Node j ) into set C D ; Otherwise, no processing;

[0027] Step 2-1-3: Determine set C D Is it empty: If it is not empty, continue with step 2-1-4; otherwise, build set C D and candidate node pair sequence Q P fail;

[0028] Step 2-1-4: Traverse C D For the node pairs in the table, check whether the link margin between the nodes meets the link type l m Required bandwidth B m:If not satisfied, remove the node pair from set C D Delete from;

[0029] Step 2-1-5: Determine set C D Is it empty? If not, continue with step 2-1-6; otherwise, build set C D and candidate node pair sequence Q P fail;

[0030] Step 2-1-6: Set C D Sort the node pairs in the middle to form a candidate node pair sequence Q P :If l m =1, C D The node pairs are classified by the type of link between nodes. m The remaining bandwidth is sorted in ascending order; if l m =2, C D Midpoint pairs are sorted by position preference.

[0031] Furthermore, in the above step 2-1-6, C D The method for sorting midpoint pairs by position preference includes the following steps:

[0032] Step 2-1-6-1: Take C D In a node pair, Node i Node j , calculate the center position (x ij ,y ij ,z ij )=((x i ,y i ,z i )+(x j ,y j ,z j )) / 2, calculate the center position of this position and other node pairs (x mn ,y mn ,z mn ) ij→mn And sum in Represents C D The complement of (i,j) in ;

[0033] Step 2-1-6-2: Traverse C according to the calculation process in step 2-1-6-1 D All elements in and calculate Σ ij , then all Σ ij Sort by size and get each order Σ ij The corresponding node pairs constitute the candidate node pair sequence Q P .

[0034] Compared with the prior art, the present invention has the following beneficial effects: the present invention transforms the task node allocation problem into an optimization problem that maximizes the task execution benefit and minimizes the total number of participating nodes, and then uses a heuristic method to solve the optimization problem; the present invention considers the task requirements of different priorities, and at the same time considers the spatial topology and network topology constraints between nodes, which is a reasonable modeling of the realistic multi-task node allocation scenario; the present invention fully considers the task requirements for nodes through heuristic solution, avoids tedious iterative trial and error, has good effectiveness, and the obtained solution can meet the actual formation node allocation needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic diagram of an embodiment of the present invention.

[0036] Figure 2 is a flow chart of using the heuristic solution of the present invention.

[0037] Figure 3 It is the result of task node allocation. DETAILED DESCRIPTION

[0038] To facilitate the implementation of the present invention, the present invention is further described below in conjunction with preferred embodiments.

[0039] The present invention proposes a collaborative task node allocation method based on network topology and preference sorting algorithm, which transforms the task node allocation problem into an optimization problem that maximizes the task execution benefit and minimizes the total number of participating nodes, and then uses a heuristic method to solve the optimization problem, eliminating tedious iterative trial and error, with good effectiveness, and the solution obtained can meet the actual formation node allocation needs.

[0040] Reference Figure 1 The processing flow in the preferred embodiment of the present invention is as follows:

[0041] Input task parameters, node parameters, and network parameters, and first execute step 1: Based on the strategy of maximizing the task execution benefit and minimizing the total number of participating nodes, M tasks T1, T2, …, T M Assign tasks to nodes Node1, Node2, …, Node N The problem is converted into solving the participating task T m The node set S m , where M≥1, N≥2; the preferred form of the optimization problem is:

[0042]

[0043] The node conditions and task requirements involved in the above optimization problem are as follows 1)-10):

[0044] 1) Node n The current working mode is w n , w n ∈{1,2};

[0045] 2) Node n The current working radius is r n ;

[0046] 3) Node n The spatial position of And assume that the position changes slowly over a period of time;

[0047] 4) Any two nodes i With Node j , whose spatial distance is D i,j ;

[0048] 5) Any two nodes i With Node j At most two communication links can be established simultaneously, that is, l∈{1,2}, where l=1 indicates a common link with a bandwidth of L. i,j , when l = 2, it indicates a high-speed link, and the allocated bandwidth is H i,j , if L i,j =0 or H i,j =0, it means that the corresponding link cannot be established;

[0049] 6) Task T m Priority is P m , the mission point or mission area center is Requirements: The minimum number of participating nodes is N m , N m =2; the working mode of each node is W m , W m ∈{0,1,2}, if W m = 0 means no requirement for the working mode; the working radius of each node covers the task point or the center of the task area; the spatial distance between any two nodes does not exceed D m ; The type of communication link between any two nodes is l m , l m ∈{1,2}, and link bandwidth B is required m ;

[0050] 7) The task execution benefit ε is defined as the sum of the priorities of all tasks that are successfully assigned enough nodes, that is,

[0051]

[0052] where 1(condition) is an indicator function and

[0053]

[0054] 8) The total number of participating nodes is

[0055] 9) Constraint C1 represents the set S m Node n Need to meet: working mode w n =W m ,if W m ≠0; the distance between the task point or the center of the task area and the node satisfies D n,m <r n ; Any two nodes Node i With Node j The distance between them satisfies D i,j <D m ;

[0056] 10) Constraints C2 and C3 represent the set S m Any two nodes in i With Node j The cumulative link bandwidth used during the period cannot exceed the link budget. m =1, requirement If l m =2, then the requirement Where η l and η h Indicates the overload level that the communication link can tolerate, η l =1.1,η h =1.1.

[0057] Then, step 2 is performed: the optimization problem described in step 1 is solved using a heuristic method based on the minimum number of nodes to meet the maximum number of task requirements. The preferred process includes: first, all tasks are sorted from high to low in priority, and then the current priority is P. m Task T m , process it sequentially according to step 2-1 to step 2-2, and finally obtain the participating node set S of the current task m :

[0058] Step 2-1: Determine the candidate node set C for the current task D and candidate node pair sequence Q P , if successful, proceed to the next step, otherwise, skip the current task and continue to process the next priority task;

[0059] Step 2-2: Q P The first node pair in thei ,Node j ) as the candidate node pair for the current task, that is, S m ={Node i ,Node j}, and then update the link bandwidth margin between the two points to the remaining value after deducting the bandwidth required by the current task.

[0060] In the above step 2-1, the candidate node set C of the current priority task is constructed D and candidate node pair sequence Q P The method specifically comprises the following steps:

[0061] Step 2-1-1: Set the working mode W m The mission point or mission area center must fall within the working radius r. n The required nodes are put into the candidate node set C W ; If the set C W If it is empty, then construct a set C D and candidate node pair sequence Q P fail;

[0062] Step 2-1-2: Traverse C W Node i With Node j , calculate the distance D i,j Does it satisfy D? i,j <D m , if satisfied, then (Node i ,Node j ) into set C D ; Otherwise, no processing;

[0063] Step 2-1-3: Determine set C D Is it empty: If it is not empty, continue with step 2-1-4; otherwise, build set C D and candidate node pair sequence Q P fail;

[0064] Step 2-1-4: Traverse C D For the node pairs in the table, check whether the link margin between the nodes meets the link type l m Required bandwidth B m :If not satisfied, remove the node pair from set C D Delete from;

[0065] Step 2-1-5: Determine set C D Is it empty? If not, continue with step 2-1-6; otherwise, build set C D and candidate node pair sequence Q P fail;

[0066] Step 2-1-6: Set C D Sort the node pairs in the middle to form a candidate node pair sequence Q P :If l m =1, C D The node pairs are classified by the type of link between nodes. m The remaining bandwidth is sorted in ascending order; if l m =2, C D Midpoint pairs are sorted by position preference.

[0067] In the above step 2-1-6, C D The method for sorting midpoint pairs by position preference includes the following steps:

[0068] Step 2-1-6-1: Take C D In a node pair, Node i Node j , calculate the center position (x ij ,y ij ,z ij )=((x i ,y i ,z i )+(x j ,y j ,z j )) / 2, calculate the center position of this position and other node pairs (x mn ,y mn ,z mn ) ij→mn And sum in Represents C D The complement of (i,j) in ;

[0069] Step 2-1-6-2: Traverse C according to the calculation process in step 2-1-6-1 D All elements in and calculate Σ ij , then all Σ ij Sort by size and get each order Σ ij The corresponding node pairs constitute the candidate node pair sequence Q P .

[0070] In order to more comprehensively evaluate the performance of the heuristic solution of the present invention, the following simulation scenario is set: the area is in the range of x to [0, 100 km], y to [0, 100 km], and 5 tasks uniformly distributed in the range of x to [50, 100 km], y to [0, 100 km] are randomly generated. The specific parameters are shown in Table 1 below, where working mode 0 means that there is no requirement for this item.

[0071] Table 1 Description of random generation task parameters

[0072]

[0073]

[0074] Five nodes are randomly generated and evenly distributed in the range of x~[0,50km] and y~[0,100km]. The specific parameters are shown in Table 2. The maximum power of working mode 1 is 300km, the maximum power of working mode 2 is 300km, and the maximum power of working mode 3 is 100km.

[0075] Table 2 Random node parameter description

[0076]

[0077] The bandwidth matrix of common links (link type 1) between nodes is randomly generated, as shown in Table 3 below, where “-” indicates invalid.

[0078] Table 3. Random node common link bandwidth parameter table (unit: MHz)

[0079]

[0080] The bandwidth matrix of high-speed links (link type 2) between nodes is randomly generated, as shown in Table 4 below.

[0081] Table 4 Random node high-speed link bandwidth parameter table (unit: MHz)

[0082]

[0083] The present invention is implemented using Matlab language, and the above parameters are simulated and verified. The results are as follows: Figure 3 As shown in the figure, according to the order of node distribution from top to bottom, node 2 is assigned to perform tasks 1, 3, and 4; node 1 is assigned to perform tasks 1 and 4; node 5 is assigned to perform tasks 2 and 3; node 3 is assigned to perform tasks 2 and 5; node 4 is assigned to perform task 5. It can be seen that node 2 has the largest number of tasks, which is 3, and the bandwidth utilization rate of the link between it and other nodes is the highest. Node 4 has the least number of tasks, which is only 1 task. At this time, the bandwidth utilization rates of the ordinary links and high-speed links between nodes are shown in Tables 5 and 6 below respectively.

[0084] Table 5. Inter-node common link bandwidth utilization (percentage)

[0085]

[0086] Table 6 Inter-node high-speed link bandwidth utilization (percentage)

[0087]

[0088] From the results in Table 5 and Table 6 above, we can see that the bandwidth utilization of the ordinary links between Node 2 and Node 1, and Node 2 and Node 5 is relatively high; the bandwidth utilization of the high-speed links between Node 3 and Node 4, and Node 3 and Node 5 is relatively high; this is consistent with the centralized allocation of tasks shown in the figure.

[0089] Based on the above test results, the present invention is a method for autonomously allocating collaborative detection tasks for multiple nodes. It takes into account the node working mode and the remaining bandwidth of the link between nodes to allocate task nodes, thereby achieving the maximum task execution benefit and the minimum number of participating nodes. At the same time, the heuristic solution process adopted avoids tedious iterative trial and error, and the obtained real-time solution can meet the actual formation task allocation requirements.

[0090] It is worth noting that the above preferred embodiments and related descriptions are not intended to limit the scope of rights of the present invention; further, any deformation and improvement that conforms to the technical features of the present invention are within the scope of protection of the present invention.

Claims

1. A collaborative task node allocation method based on network topology and preference sorting algorithm, characterized by: Step 1: Based on the strategy of maximizing the task execution benefit and minimizing the total number of participating nodes, M tasks T1, T2, …, T M Assign tasks to nodes Node1, Node2, …, Node N The problem is converted into solving the participating task T m The node set S m Optimization problem, where M ≥ 1, N ≥ 2; Step 2: Solve the optimization problem described in step 1 using a heuristic method based on satisfying the maximum number of tasks with the minimum number of nodes.

2. The collaborative task node allocation method based on network topology and preference sorting algorithm according to claim 1 is characterized in that: The optimization problem in step 1 includes: The node conditions and task requirements involved in the above optimization problem are as follows 1)-10): 1) Node n The current working mode is w n , w n ∈{1,2}; 2) Node n The current working radius is r n ; 3) Node n The spatial position of And assume that the position changes slowly over a period of time; 4) Any two nodes i With Node j , whose spatial distance is D i,j ; 5) Any two nodes i With Node j At most two communication links can be established simultaneously, that is, l∈[1,2}, when l=1, it indicates a common link, and the allocated bandwidth is L i,j , when l = 2, it indicates a high-speed link, and the allocated bandwidth is H i,j , if L i,j =0 or H i,j =0, it means that the corresponding link cannot be established; 6) Task T m Priority is P m , the mission point or mission area center is Requirements: The minimum number of participating nodes is N m , N m =2; the working mode of each node is W m , W m ∈{0,1,2}, if W m = 0 means no requirement for the working mode; the working radius of each node covers the task point or the center of the task area; the spatial distance between any two nodes does not exceed D m ; The type of communication link between any two nodes is l m , l m ∈{1,2}, and link bandwidth B is required m ; 7) The task execution benefit ε is defined as the sum of the priorities of all tasks that are successfully assigned enough nodes, that is: Where 1(condition) is an indicator function, and: 8) The total number of participating nodes is 9) Constraint C1 represents the set S m Node n Need to meet: working mode w n =W m ,if W m ≠0; the distance between the task point or the center of the task area and the node satisfies D n,m <r n ; Any two nodes Node i With Node j The distance between them satisfies D i,j <D m ; 10) Constraints C2 and C3 represent the set S m Any two nodes in i With Node j The cumulative link bandwidth used during the period cannot exceed the link budget. m =1, requirements: If l m =2, then the requirement is: Where η l and η h Indicates the overload level that the communication link can tolerate, η l =1.1,η h =1.

1.

3. The collaborative task node allocation method based on network topology and preference sorting algorithm according to claim 2 is characterized in that: The heuristic method used in step 2 to meet the maximum task requirements based on the minimum number of nodes includes: First, sort all tasks from high to low priority, and then take the current priority as P. m Task T m , process it sequentially from step 2-1 to step 2-2, and finally obtain the participating node set S of the current task m : Step 2-1: Determine the candidate node set C for the current task D and candidate node pair sequence Q P , if successful, proceed to the next step, otherwise, skip the current task and continue to process the next priority task; Step 2-2: Q P The first node pair in the i ,Node j ) as the candidate node pair for the current task, that is, S m ={Node i ,Node j }, and then update the link bandwidth margin between the two points to the remaining value after deducting the bandwidth required by the current task.

4. The collaborative task node allocation method based on network topology and preference sorting algorithm according to claim 3 is characterized by: In step 2-1, a candidate node set C of the current priority task is constructed. D and candidate node pair sequence Q P The method comprises the following steps: Step 2-1-1: Set the working mode W m The mission point or mission area center must fall within the working radius r. n The required nodes are put into the candidate node set C W ; If the set C W If it is empty, then construct a set C D and candidate node pair sequence Q P fail; Step 2-1-2: Traverse C W Node i With Node j , calculate the distance D i,j Does it satisfy D? i,j <D m , if satisfied, then (Node i ,Node j ) into set C D ; Otherwise, no processing; Step 2-1-3: Determine set C D Is it empty: If it is not empty, continue with step 2-1-4; otherwise, build set C D and candidate node pair sequence Q P fail; Step 2-1-4: Traverse C D For the node pairs in the table, check whether the link margin between the nodes meets the link type l m Required bandwidth B m : If not satisfied, remove the node pair from set C D Delete from; Step 2-1-5: Determine set C D Is it empty? If not, continue with step 2-1-6; otherwise, build set C D and candidate node pair sequence Q P fail; Step 2-1-6: Set C D Sort the node pairs in the middle to form a candidate node pair sequence Q P :If l m =1, C D The node pairs are classified by the type of link between nodes. m The remaining bandwidth is sorted in ascending order; if l m =2, C D Midpoint pairs are sorted by position preference.

5. The collaborative task node allocation method based on network topology and preference sorting algorithm according to claim 4 is characterized in that: In step 2-1-6, C D The method for sorting midpoint pairs by position preference includes the following steps: Step 2-1-6-1: Take C D In a node pair, Node i 、Node j , calculate the center position of the two: (x ij ,y ij ,z ij )=((x i ,y i ,z i )+(x j ,y j ,z j )) / 2; Calculate the center position (x mn ,y mn ,z mn ) ij→mn And sum: in Represents C D The complement of (i,j) in ; Step 2-1-6-2: Traverse C according to the calculation process in step 2-1-6-1 D All elements in and calculate Σ ij , then all Σ ij Sort by size and get each order Σ ij The corresponding node pairs constitute the sorted candidate node pair sequence Q P .

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