CN101458333B - Three-dimensional test space array node dynamic deploying method based on wireless sensor network - Google Patents
Three-dimensional test space array node dynamic deploying method based on wireless sensor network Download PDFInfo
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Abstract
The invention relates to a dynamic deployment method for three-dimensional test space array nodes based on a wireless sensor network, belonging to the field of the array control of cluster nodes. The method mainly comprises three steps as follows: allocating system test tasks, planning the optimal deployment path of the nodes and deploying the three-dimensional array in the network test space; the atomic model based on 'attract-repel' is adopted to deploy the three-dimensional space array of the nodes. When tracking and testing a test object with motion characteristic in the three-dimensional space, the method has the advantages of high efficiency, high degree of automation, uniform density of nodes, reliable communication quality, three-dimensional character, dynamical and adjustable deployment of nodes and the like.
Description
Technical Field
The invention relates to a dynamic deployment method of three-dimensional test space array nodes, belonging to the cluster type node array form control technology in the technical field of artificial intelligence.
Background
The wireless sensor network is suitable for field signal multipoint information acquisition, and the number of information acquisition nodes is large. How to effectively organize the cooperative work of numerous nodes is an important subject of the wireless sensor network, how to expand the work of the nodes of the wireless sensor network is a basic problem to be faced by each sensor network, and therefore the problem of node deployment is one of the application basic problems of the wireless sensor network. At present, the problem of array deployment based on a wireless sensor network is carried out aiming at a two-dimensional surface or a quasi two-dimensional surface, and the deployment theory and algorithm aiming at the three-dimensional space array are quite incomplete. The existing wireless sensor network-based formation deployment methods basically adopt manual deployment or random automatic throwing deployment (such as shot shooting, air drop throwing and the like), and have the following problems: the method has the advantages of low efficiency, uncontrollable node density, no capability of dynamically adjusting the node position, no capability of deploying in a three-dimensional space, limited automation degree, difficult control of array shape and the like.
In order to realize the tracking test of a moving test object and the test of space field information in a three-dimensional space, a deployment method different from the traditional wireless sensor network is needed to solve the node deployment problem of the mobile three-dimensional space wireless test network.
Disclosure of Invention
The invention aims to overcome the defects of the existing method and provide a three-dimensional test space array node dynamic deployment method based on a wireless sensor network to solve the array configuration deployment problem of test nodes in a three-dimensional space.
In order to realize automatic and dynamic node deployment of a mobile wireless three-dimensional test network, the invention mainly aims at a test object with mobility in a three-dimensional space to carry out tracking test so as to obtain the test area coverage rate with high network efficiency, uniform node density and reliable communication and solve the problem of node array deployment of a three-dimensional space wireless test system.
The invention discloses a three-dimensional test space array node dynamic deployment method based on a wireless sensor network. This platform includes: the system comprises an air flight data acquisition node, a ground data acquisition node, a mobile data processing gateway and a human-computer interaction console. The aerial flight data acquisition node has aerial movement and hovering capacity; the ground data acquisition node has the mobility; the mobile data processing gateway is used for sending, collecting and processing network data.
The method of the invention is adopted to carry out node dynamic deployment on the system, and the steps are as follows:
step one, completing the distribution of system testing tasks.
Firstly, a man-machine interaction console formulates the size, the type and the test location of a test task, and sends the formulated test task to a mobile data processing gateway. And then, after receiving the test task, the mobile data processing gateway decomposes and distributes the task to each participating node. And finally, the mobile data processing gateway issues a test task instruction to each participating node in a wireless communication mode.
Step two, planning out the optimal deployment path of each node
After receiving the test task, each node firstly acquires local GPS information (the current position of the node), and then carries out path planning according to destination GPS information (the position required to be reached in the task). When the node encounters an obstacle or other nodes in the traveling process, the node carries out obstacle avoidance processing.
Step three, deploying a network test space three-dimensional array
And after the second step, all the nodes move to a test site. At the moment, each node is deployed in a matrix according to the calculation result to form a three-dimensional space test matrix. All the nodes are combined into a unit matrix and then are spliced into a complete array. And if the task changes or the test object changes the site and the node array is required to be adjusted, each node will perform three-dimensional array deployment again, thereby realizing dynamic deployment or tracking test.
Advantageous effects
The method solves the problem of dynamic deployment of node space formation of the mobile wireless three-dimensional test network, improves the conditions of low efficiency and low automation degree of manual deployment of the wireless sensor network, and avoids the situations of uncontrollable node density, uncontrollable test range and unadjustable test space and the like caused by the adoption of random deployment methods such as shot blasting, air drop throwing and the like in the traditional method. The invention plays an important supporting role in promoting the practicability of the wireless sensor network. The three-dimensional space dynamic deployment method has the advantages of high efficiency, low energy consumption, high automation degree and controllable node density, forms a three-dimensional test space array with moving characteristics, and can completely meet the test requirements for fixed or moving targets.
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FIG. 1 is a flow chart of the method of the present invention;
fig. 2 is a schematic diagram of the formation of a three-dimensional array based on a three-dimensional unit matrix.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the accompanying drawings.
Fig. 1 is a schematic diagram of dynamic deployment of three-dimensional test space array nodes. In the figure, nodes are basic elements forming a three-dimensional unit matrix; the three-dimensional unit matrix is an element forming a complete three-dimensional test space.
The method mainly comprises three steps of system test task allocation, optimal path planning of node deployment and three-dimensional formation deployment of a network test space.
The system test task allocation and the optimal path planning of node deployment are both prepared for the three-dimensional array deployment of the network test space. The system test task allocation is completed before the optimal path planning of the node deployment is executed; the three-dimensional array deployment of the network test space is executed after the optimal path planning of the node deployment, and is the embodiment of the core content of the three-dimensional array and the final node deployment effect.
Fig. 2 is a flowchart of the mobile three-dimensional spatial wireless test network spatial array deployment, which is specifically described as follows:
the method comprises the following steps: system test task allocation
Firstly, a human-computer interaction console formulates the size and type of a test task and the destination of the task, and sends the formulated test task to a mobile data processing gateway.
And then, the mobile data processing gateway distributes tasks according to the size of the tasks and the number of the nodes and determines the nodes participating in the tasks. The specific mode is as follows: and adopting a contract method, and initiating task bidding by the mobile data processing gateway according to the task completion capability of each node, thereby determining the nodes participating in the task completion.
And finally, the mobile data processing gateway issues a test task instruction to each participating node in a wireless communication mode and informs each winning node to participate in a three-dimensional space array test task.
Step two, planning the optimal path for deploying the nodes
After receiving the test task, each node firstly acquires local GPS information (the current position of the node), and then carries out path planning according to destination GPS information (the position required to be reached in the task). When the node encounters an obstacle or other nodes in the traveling process, the node carries out obstacle avoidance processing.
After receiving the test task, each node firstly acquires local GPS information of the node, and then carries out path planning according to destination GPS information required by the completion task. The specific mode is as follows: and each node adopts an optimization ant colony algorithm, finds a path with the minimum cost required by completing the task as a moving path of the node, and therefore energy consumption of each node is reduced. And environment information is shared among all nodes through a blackboard mechanism, so that navigation is realized.
When the node encounters an obstacle or other nodes in the process of traveling, the node avoids trapping by adopting a wall-winding strategy.
Step three, deploying a network test space three-dimensional array
And after the second step, all the nodes move to a test site. Each node is combined into a three-dimensional unit matrix in a certain three-dimensional geometrical shape, and then, each three-dimensional unit matrix forms a complete three-dimensional space test matrix. And if the task changes or the test object changes the site and the node array is required to be adjusted, each node will perform three-dimensional array deployment again, thereby realizing dynamic deployment or tracking test.
The concrete implementation process of the third step:
first, a stereo cell matrix calculation is performed. And determining the type and size of the three-dimensional unit matrix according to the requirement of the node deployment density and the communication quality condition. Then, by adopting an 'attraction-repulsion' atom model, nodes are freely combined to obtain a three-dimensional unit matrix.
The principle of adopting an 'attraction-repulsion' atom model is as follows: the distance l between node 1 and node 2 is adjusted. And when adjusting l, the communication packet loss rate and the sensor test range are taken as the guideline. When the communication packet loss rate is less than 2%, the communication quality between the two nodes is considered to be reliable, and the nodes should mutually repel each other to increase the communication distance; when the communication packet loss rate is greater than 5%, the communication quality between two nodes is considered to be close to the worst limit, and the nodes should attract each other to reduce the communication distance; and when the communication packet loss rate is between 2% and 5%, determining the communication range as a reliable communication range, and then adjusting the position by taking the detection range of the sensor as a second standard. Assuming that the maximum detection distance of the sensor is s meters, the distance between the nodes is adjusted to be s meters, so that the communication quality between the two nodes can be ensured, and meanwhile, the detection range is maximized. Other nodes are deployed according to the standard, and a wireless test system with reliable communication quality and maximum test space can be obtained.
The regular polygon stereo deployment algorithm process is as follows:
1) and selecting an anchor node and a reference straight line.
One node in the node group is selected as an anchor node b0Selecting a node closest to the anchor node as the node b1Between which a reference straight line l is defined1The rest nodes take the anchor node and the reference straight line as partsAnd deploying the benchmark to perform position calculation in a two-dimensional plane.
Anchor node b0And node b1The distance adjustment is carried out by adopting an 'attraction-repulsion' atomic model method to determine the side length l of the polygon1。
2) And calculating the positions of the rest nodes.
By side length l1For the reference line, distance node b is selected1Nearest node b2. Node b1And node b2The connecting lines of the deployment target position points form a straight line l2The straight line is connected with a reference straight line l1The included angle between the two is the internal angle theta of the regular polygon, and the node deployment is carried out by taking the anticlockwise direction as the forward direction. Node b1And node b2The distance between the first and second sides is adjusted according to an 'attraction-repulsion' atom model method to obtain a second side l of the regular polygon2。
The other vertexes (i.e. nodes) and edges l of the regular polygon solid can be determined by the same methodnAnd side length.
Wherein,
l1＝l2＝...＝ln (1)
3) the height of the regular polygon cube is determined.
By anchor node b1Using the polygon in 2) as the bottom surface as the starting point, and determining the anchor node t of the upper bottom surface according to an 'attraction-repulsion' atomic model criminal method1And a lower floor anchor node b1The distance h (i.e. the height of the cube). Here, ,
h＝l1＝l2＝...＝ln (2)
4) and (5) deploying a cubic unit matrix.
And on the basis of 3), carrying out polygon vertex calculation and deployment in the upper bottom surface according to the method of 2), thereby completing the deployment of the cubic unit matrix.
5) And (4) deploying a complete three-dimensional space test array.
And 4) taking the cubic unit matrix obtained in the step 4) as a deployment unit, splicing the cubic unit matrix by using an attraction-repulsion atom model method, and finally completing the deployment of the whole three-dimensional space test matrix.
And finally, when the node density is required to be adjusted or a new node is added, the spatial array is redeployed according to the method in the third step.
The process of calculating the three-dimensional unit matrix is illustrated by taking a cube as an example:
1) one node in the node group is selected as an anchor node, a node closest to the anchor node is selected as a second node, a reference straight line is determined between the anchor node and the second node, and the rest nodes perform position calculation in a two-dimensional plane by taking the anchor node and the reference straight line as deployment references.
Adjusting the distance l between the anchor node and the second node by adopting an 'attraction-repulsion' atom model1. Adjustment l1And meanwhile, the packet loss rate of the communication and the test range of the sensor are taken as the guideline. When the communication packet loss rate is less than 2%, the communication quality between two nodes is considered to be reliable, and the nodes should be mutually exclusive to increase the communication distance; when the communication packet loss rate is greater than 5%, the communication quality between two nodes is considered to be close to the worst, and the nodes should attract each other to reduce the communication distance; when the packet loss rate of the communication is between 2% and 5%, the communication is considered to be a reliable communication range, and at this time, the detection range of the sensor is taken as a second standard. For example, the maximum detection distance of the sensor is 20 meters, and the distance between the nodes should be adjusted to 20 meters, so that the communication quality between the two nodes can be ensured, and meanwhile, the detection range is also maximized. Other nodes are deployed according to the standard, and a wireless test system with reliable communication quality and maximum test space can be obtained.
2) The node closest to the reference line is preferably selected as the third node. Based on the reference straight line, the thirdThe deployment target position point of the node and the anchor node determine a straight line. An included angle theta formed by the straight line and the reference straight line is 45 degrees, an attraction-repulsion atomic model is adopted, and the distance l between the third node and the anchor node is adjusted2. Wherein l2The following relationship is satisfied:
l2＝l1·sin θ (1)
at this time, it should be ensured that the packet loss rate of the communication between the third node and the anchor node is between 2% and 5%, and if the relation (1) is not satisfied, l is adjusted1And l2To a smaller value to satisfy the equation.
3) And selecting the node closest to the third node as a fourth node in the anticlockwise direction. Determining the position of the fourth node by adopting an 'attraction-repulsion' atom model according to the method 1).
At this time, the deployment is finished with CELL1 deployment as shown in fig. 3, then the upper bottom surface deployment is carried out according to the deployment method of CELL1 by taking CELL1 as a reference surface and the anchor node as a reference, and finally the calculation and deployment of the stereoscopic CELL matrix are finished.
Secondly, by using an 'attraction-repulsion' atom model, taking a regular cubic unit matrix as a deployment unit, calculating and deploying according to a cubic unit matrix method, and finishing the combination of each cubic unit matrix to obtain a complete three-dimensional space array, as shown in fig. 1.
Claims (2)
1. A three-dimensional test space array node dynamic deployment method based on a wireless sensor network is characterized by comprising the following steps:
step one, completing the distribution of system test tasks
Firstly, a man-machine interaction console formulates the size, type and test location of a test task, and sends the formulated test task to a mobile data processing gateway; then, after receiving the test task, the mobile data processing gateway decomposes and distributes the task to each participating node; finally, the mobile data processing gateway issues a test task instruction to each participating node in a wireless communication mode;
step two, planning out the optimal deployment path of each node
After receiving the test task, each node firstly acquires local GPS information of the node and then carries out path planning according to the destination GPS information; when the node encounters an obstacle or other nodes in the traveling process, the node carries out obstacle avoidance processing;
step three, deploying a network test space three-dimensional array
After the second step, all the nodes move to a test site; at the moment, each node is deployed in a form of array to form a three-dimensional space test array; wherein, an 'attraction-repulsion' atom model is adopted, and the principle is as follows: adjusting the distance l between the node 1 and the node 2; when the I is adjusted, the communication packet loss rate and the sensor test range are taken as the guideline, and when the communication packet loss rate is less than 2%, the communication quality between two nodes is considered to be reliable, and the nodes are mutually exclusive to increase the communication distance; when the communication packet loss rate is greater than 5%, the communication quality between two nodes is considered to be close to the worst limit, and the nodes should attract each other to reduce the communication distance; when the packet loss rate of the communication is between 2% and 5%, the communication is considered to be a reliable communication range; at the moment, the position is adjusted by taking the detection range of the sensor as a second standard, the distance between the nodes is adjusted to be s meters under the assumption that the maximum detection distance of the sensor is s meters, and other nodes are deployed according to the standard; all nodes are combined into a unit matrix and then are spliced into a complete array; and if the task changes or the test object changes the site and the node array is required to be adjusted, each node will perform three-dimensional space array deployment again.
2. The method for dynamically deploying the three-dimensional test space array nodes based on the wireless sensor network as claimed in claim 1, wherein the method for deploying the three-dimensional array of the network test space is as follows:
firstly, calculating a three-dimensional unit matrix, and determining the type and size of the three-dimensional unit matrix according to the requirement of node deployment density and the communication quality condition; then, adopting an 'attraction-repulsion' atom model, and carrying out free combination on nodes to obtain a three-dimensional unit matrix;
the regular polygon stereo deployment algorithm process is as follows:
1) selection of anchor node and reference line
One node in the node group is selected as an anchor node boSelecting a node closest to the anchor node as the node b1Determining a reference straight line between the anchor node and the reference straight line, and calculating the positions of the other nodes in the two-dimensional plane by taking the anchor node and the reference straight line as deployment references;
anchor node boAnd node b1The distance adjustment is carried out by adopting the 'attraction-repulsion' atomic model method to determine the side length l of the polygon1；
2) Position calculation of the remaining nodes
Selecting a distance node b by taking the polygon edge as a reference straight line1Nearest node b2Node b1And node b2The connecting lines of the deployment target position points form a straight line l2An included angle between the straight line and the reference straight line is an internal angle theta of the regular polygon, and node deployment is carried out in a direction which is anticlockwise as a forward direction; node b1And node b2The distance between the first and second sides is adjusted according to an 'attraction-repulsion' atom model method to obtain a second side l of the regular polygon2；
Determining the other vertexes and edges l of regular polygon solid by the same methodnAnd length of side, wherein
l1＝l2＝...＝ln
3) Determining height of regular polygon cube
By anchor node b1Taking the polygon in 2) as a bottom surface as a starting point, and determining an anchor node t of the upper bottom surface according to an attraction-repulsion atomic model method1And a lower floor anchor node b1At a distance h therebetween, here
h＝l1＝l2＝...＝ln
4) Deployment of cubic cellular matrices
On the basis of 3), calculating and deploying the polygon vertexes in the upper bottom surface according to the method of 2), thereby completing the deployment of the cubic unit matrix;
5) deployment of complete three-dimensional spatial test array
Splicing the cubic unit matrix by using the cubic unit matrix obtained in the step 4) as a deployment unit by using an attraction-repulsion atomic model method, and finally completing the deployment of the whole three-dimensional space test matrix;
and when the node density is required to be adjusted or a new node is added, the spatial array is redeployed according to the method of the third step.
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| 张东红等.无线传感器网络节点自定位算法.《计算机工程》.2008,第34卷(第12期),100,101,104. * |
| 张东红等.瞬态场信号采集中传感器网络节点的软件设计.《计算机工程》.2008,第34卷(第12期),268-270. * |
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