CN113746681A - Detection method, device and equipment for perception hole and storage medium - Google Patents

Detection method, device and equipment for perception hole and storage medium Download PDF

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CN113746681A
CN113746681A CN202111037058.XA CN202111037058A CN113746681A CN 113746681 A CN113746681 A CN 113746681A CN 202111037058 A CN202111037058 A CN 202111037058A CN 113746681 A CN113746681 A CN 113746681A
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樊学宝
黄智勇
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China United Network Communications Group Co Ltd
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Abstract

The invention provides a detection method, a device, equipment and a storage medium for perception holes, wherein the method comprises the following steps: the method comprises the steps of firstly determining at least one sub-network contained in the Internet of things according to the network topological relation of a plurality of sensor nodes in the Internet of things, then determining the gravity center of the sub-network, simulating gas diffusion by taking the gravity center of the sub-network as a central point, then obtaining gas values detected by all the sensor nodes in the sub-network, and finally determining whether a sensing cavity exists in the sub-network according to all the gas values. According to the method, according to a perception boundary theory, gas diffusion is simulated by starting from the gravity center of an irregular polygon through the topological relation of the sensor nodes, and whether a perception cavity exists is determined.

Description

Detection method, device and equipment for perception hole and storage medium
Technical Field
The present invention relates to the field of mobile communications, and in particular, to a method, an apparatus, a device, and a storage medium for detecting a perceptual hole.
Background
In recent years, with the development of communication technology and sensor technology, the technology of internet of things has been rapidly developed and has gradually entered various industries. The Internet of things can greatly change the current life style of people, becomes another driver for promoting economic development, and develops another development opportunity with endless potential for the industry. In the planning deployment of the nodes of the internet of things, various objective reasons such as faults of sensors and communication transceivers exist, so that a perception hole of the internet of things is inevitably caused, and how to detect and find the perception hole of the internet of things becomes very important.
In the prior art, a mobile sensor is usually used to detect a perception hole of the internet of things. The detection method has low detection efficiency and high energy consumption.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a detection method, a detection device and a storage medium for a perception hole.
In a first aspect, the present invention provides a method for detecting a perceived hole, which is applied to the internet of things, where the internet of things includes a plurality of sensor nodes, and the method includes:
determining at least one sub-network contained in the Internet of things according to the network topological relation of the plurality of sensor nodes;
the following operations are performed for each sub-network:
determining a center of gravity of the subnetwork;
simulating gas diffusion by taking the gravity center of the subnetwork as a central point;
acquiring gas values detected by all sensor nodes in a sub-network;
based on the respective gas values, it is determined whether a sensing void exists in the subnetwork.
In a possible implementation manner, determining a sub-network included in the internet of things according to a network topology relationship of a plurality of sensor nodes includes: determining gateway equipment contained in the Internet of things; and determining sub-networks included in the Internet of things according to the network topological relations of the sensor nodes and the gateway equipment, wherein the sensor nodes in the sub-networks are connected to the same gateway equipment.
In one possible embodiment, determining the center of gravity of a subnetwork comprises: connecting the outermost sensor nodes in the sub-network to form a polygon; the center of gravity of the polygon is determined as the center of gravity of the sub-network.
In one possible embodiment, determining whether a perceived void exists in the subnetwork based on the respective gas values comprises: if the gas values are larger than or equal to a preset threshold value, determining that no sensing cavity exists in the sub-network; and if the gas values corresponding to the sensor nodes in the sub-network have the gas values smaller than the preset threshold value, determining that the sensing holes exist in the sub-network.
In a possible embodiment, the method further comprises: after determining that a perceived hole exists in the subnetwork, determining a location of the perceived hole based on: for the sensor nodes with the gas numerical value larger than or equal to the preset threshold value, determining the sensor nodes positioned at the outermost layer as inner boundary nodes of the perception cavity; for the sensor nodes with the gas values smaller than the preset threshold value, determining the sensor nodes positioned on the innermost layer as outer boundary nodes of the sensing cavity; connecting the inner boundary nodes, and determining an inner boundary area of the perception cavity; and connecting the outer boundary nodes to determine the outer boundary area of the perception cavity.
In a possible embodiment, the method further comprises: after determining the position of the perception hole, refining and positioning the perception hole according to the following modes: determining an interpolation point between the outer boundary region and the inner boundary region according to a radial base point interpolation method; and connecting the interpolation points and determining a refined boundary line.
In a possible embodiment, the method further comprises: and determining whether the sensing holes exist in the Internet of things or not according to the detection result of whether the sensing holes exist in at least one sub-network contained in the Internet of things or not.
In a second aspect, the present invention provides a device for detecting a perceived void, which is applied to the internet of things, where the internet of things includes a plurality of sensor nodes, and includes:
the determining module is used for determining at least one sub-network contained in the Internet of things according to the network topological relation of the plurality of sensor nodes; and determining a center of gravity of the subnetwork;
the simulation module is used for simulating gas diffusion by taking the gravity center of the sub-network as a central point;
the acquisition module is used for acquiring the gas values detected by all the sensor nodes in the sub-network;
and the determining module is also used for determining whether a perception hole exists in the sub-network according to each gas value.
In a possible implementation, the determining module is specifically configured to: determining gateway equipment contained in the Internet of things; and determining sub-networks included in the Internet of things according to the network topological relations of the sensor nodes and the gateway equipment, wherein the sensor nodes in the sub-networks are connected to the same gateway equipment.
In a possible implementation, the determining module is specifically configured to: connecting the outermost sensor nodes in the sub-network to form a polygon; the center of gravity of the polygon is determined as the center of gravity of the sub-network.
In a possible implementation, the determining module is specifically configured to: if the gas values are larger than or equal to a preset threshold value, determining that no sensing cavity exists in the sub-network; and if the gas values corresponding to the sensor nodes in the sub-network have the gas values smaller than the preset threshold value, determining that the sensing holes exist in the sub-network.
In one possible embodiment, the determining module is further configured to: after determining that a perceived hole exists in the subnetwork, determining a location of the perceived hole based on: for the sensor nodes with the gas numerical value larger than or equal to the preset threshold value, determining the sensor nodes positioned at the outermost layer as inner boundary nodes of the perception cavity; for the sensor nodes with the gas values smaller than the preset threshold value, determining the sensor nodes positioned on the innermost layer as outer boundary nodes of the sensing cavity; connecting the inner boundary nodes, and determining an inner boundary area of the perception cavity; and connecting the outer boundary nodes to determine the outer boundary area of the perception cavity.
In one possible embodiment, the determining module is further configured to: after determining the position of the perception hole, refining and positioning the perception hole according to the following modes: determining an interpolation point between the outer boundary region and the inner boundary region according to a radial base point interpolation method; and connecting the interpolation points and determining a refined boundary line.
In one possible embodiment, the determining module is further configured to: and determining whether the sensing holes exist in the Internet of things or not according to the detection result of whether the sensing holes exist in at least one sub-network contained in the Internet of things or not.
In a third aspect, the present invention provides an electronic device comprising:
a memory and a processor;
the memory is used for storing program instructions;
the processor is configured to invoke program instructions in the memory to perform the method for detecting perceptual holes of the first aspect.
In a fourth aspect, the present invention is a computer-readable storage medium, in which computer program instructions are stored, and when the computer program instructions are executed, the method for detecting a perceptual void according to the first aspect is implemented.
The invention provides a detection method, a device, equipment and a storage medium for perception holes, wherein at least one sub-network included in the Internet of things is determined according to the network topological relation of a plurality of sensor nodes in the Internet of things; then determining the center of gravity of the sub-network; simulating gas diffusion by taking the gravity center of the subnetwork as a central point; then, acquiring gas values detected by all sensor nodes in the sub-network; and finally, determining whether a sensing hole exists in the sub-network according to the gas values. According to the method, according to a perception boundary theory, gas diffusion is simulated by starting from the gravity center of an irregular polygon through the topological relation of the sensor nodes, and whether a perception cavity exists is determined.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic view of an application scenario provided in an embodiment of the present invention;
FIG. 2 is a flowchart of a method for detecting a perceived void according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating an exemplary structure of a subnetwork of the hole-aware detection method according to an embodiment of the present invention;
FIG. 4 is an exemplary illustration of the location of the center of gravity of the subnetwork structure shown in FIG. 3;
FIG. 5 is an exemplary diagram of inner and outer boundary regions of the sub-network structure shown in FIG. 3;
FIG. 6 is an exemplary diagram of refined boundary lines for the sub-network structure shown in FIG. 3;
fig. 7 is a schematic structural diagram of a device for detecting a perceived void according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
First, some technical terms related to the present invention are explained:
the perception hole is a hole of signal transmission, and in a hole area, a signal received by a receiver has the problems of distortion, low signal-to-noise ratio, low gain and the like. Meanwhile, signals transmitted by the transmitter in the cavity area also have the problems of low signal gain, short transmission distance and incapability of being transmitted to a target antenna.
At present, in the prior art, a mobile sensor is often used for detecting the position of a sensing cavity, and the detection method needs manpower and long detection time, so that the detection efficiency is low. Meanwhile, the method has larger energy consumption.
Based on the above problems, embodiments of the present invention provide a method, an apparatus, a device, and a storage medium for detecting a sensing void, which determine whether a sensing void exists by simulating gas diffusion from the center of gravity of an irregular polygon through a topological relation of sensor nodes according to a sensing boundary theory.
Fig. 1 is a schematic view of an application scenario provided in an embodiment of the present invention. As shown in fig. 1, in this application scenario. Firstly, a topological network of sensor nodes in the internet of things is input into the computer 100, at least one sub-network included in the internet of things is determined according to the network topological relation of a plurality of sensor nodes in the computer 100, then the gravity center of the sub-network is determined, gas diffusion is simulated by taking the gravity center of the sub-network as a central point, then gas values detected by the sensor nodes in the sub-network are obtained, and finally whether a sensing hole exists in the sub-network is determined according to the gas values. If the existence of the perception hole is determined, taking the area where the perception hole exists as an output result; and if the sensing holes do not exist, outputting the result that the sensing holes do not exist in the topological network.
It should be noted that fig. 1 is only a schematic diagram of an application scenario provided in an embodiment of the present invention, and the embodiment of the present invention does not limit the devices included in fig. 1, and does not limit the positional relationship between the devices in fig. 1. For example, in the application scenario shown in fig. 1, a data storage device may be further included, and the data storage device may be an external memory with respect to the computer 100, or an internal memory integrated in the computer 100. The computer 100 may be a PC, i.e., a computer, a terminal device such as a mobile phone or a notebook, or a mainframe computer such as a server or a server cluster.
Next, a method for detecting a perceived hole is described with reference to a specific embodiment.
Fig. 2 is a flowchart of a detection method for sensing holes according to an embodiment of the present invention, where the method is applied to an internet of things, where the internet of things includes a plurality of sensor nodes, as shown in fig. 2:
s201, determining at least one sub-network included in the Internet of things according to the network topology relation of the plurality of sensor nodes.
The method comprises the steps of firstly processing a topological network formed by sensor nodes in the Internet of things, and dividing the whole topological network into a plurality of sub-networks before processing because a perception boundary theory is needed. Alternatively, the division rule is decided by each sensor node.
Steps S202 to S205 are executed for each sub-network.
It can be understood that if the area corresponding to the internet of things is small, the following operations may be performed for the internet of things without performing the process of dividing the area into a plurality of sub-networks.
S202, determining the gravity center of the sub-network.
Because the position of the sensing cavity needs to be determined according to the sensing boundary theory and a mode of simulating gas diffusion, in the method, the center of the gas diffusion is the gravity center of the sub-network. Therefore, when performing the simulation calculation, it is necessary to determine the position of the center of gravity of the sub-network first.
And S203, simulating gas diffusion by taking the gravity center of the sub-network as a central point.
And S204, acquiring the gas values detected by the sensor nodes in the sub-network.
In a subnetwork, the individual sensor nodes differ in their distance from the center of gravity. Specifically, when simulating gas diffusion, the gas value detected by the sensor node closer to the center of gravity is relatively higher; the sensor nodes farther from the center of gravity detect relatively low gas values.
Furthermore, simulating that gas diffusion corresponds to a perception cavity of the Internet of things, wherein the lower the detected gas value is, the lower the intensity of the transmitted and received signals is, and the more serious the shielded degree of the signals is; conversely, the higher the gas value, the higher the intensity of the transmitted and received signal, and the less the signal is shielded.
And S205, determining whether a sensing cavity exists in the sub-network according to each gas value.
After each gas value is obtained, the area where the cavity is located needs to be determined.
For example, for the definition of perceptual holes, it is, in a broad sense, an area where signals are masked or where signals cannot be emitted or received. In the present invention, it may be the area where the signal under a certain area is shielded or the signal cannot be sent or received, in other words, when the distance is far enough from the center of gravity, the value of the detected gas must be small enough, so that the sensing hole is theoretically infinite from the above-mentioned reasoning, but since the sub-network is not infinite and no longer meaningful for the hole research beyond a certain distance, the main purpose of the present invention is to determine the sensing hole at the boundary area. Further, after a perceived hole in a certain region has been determined, a region other than the perceived hole (a region far from the center of gravity) necessarily belongs to the perceived hole region of the sub-network.
In the embodiment of the invention, at least one sub-network contained in the Internet of things is determined according to the network topological relation of a plurality of sensor nodes in the Internet of things; then determining the center of gravity of the sub-network; simulating gas diffusion by taking the gravity center of the subnetwork as a central point; then, acquiring gas values detected by all sensor nodes in the sub-network; and finally, determining whether a sensing hole exists in the sub-network according to the gas values. According to the method, according to a perception boundary theory, gas diffusion is simulated by starting from the gravity center of an irregular polygon through the topological relation of the sensor nodes, and whether a perception cavity exists is determined.
Optionally, on the basis of the foregoing embodiment, for determining at least one sub-network included in the internet of things according to the network topology relationship of the plurality of sensor nodes in step S201, the determining may include: determining gateway equipment contained in the Internet of things; and determining sub-networks included in the Internet of things according to the network topological relations of the sensor nodes and the gateway equipment, wherein the sensor nodes in the sub-networks are connected to the same gateway equipment.
When the topological network of the Internet of things is divided, the sensor nodes connected with the same gateway are divided into the same sub-network according to the relationship between the sensor nodes and the gateway, and the division method meets the perception boundary theory and also meets the definition of perception holes.
Illustratively, the method is: firstly, determining the positions and information of all gateways in a topological network of the whole Internet of things; then according to each sensor node, finding out a gateway connected with the sensor node; therefore, the sensor nodes and the gateways are in one-to-one correspondence, and finally all the sensor nodes connected with the same gateway are divided into a sub-network. After the method is executed, the whole topological network is divided into a plurality of sub-networks, further, whether a perception hole exists in each sub-network is determined, and if the perception hole exists, the specific area of the perception hole is determined.
Based on the above embodiments, further, determining the barycenter of the sub-network may include: connecting the outermost sensor nodes in the sub-network to form a polygon; the center of gravity of the polygon is determined as the center of gravity of the sub-network.
Since the sub-network is only a range concept, if it is necessary to simulate gas diffusion at the center of gravity, a closed pattern needs to be determined first, and therefore, it is necessary to connect the sensor nodes at the outermost periphery of the sub-network in sequence. After a closed figure is determined, the position of its center of gravity is determined according to geometric methods.
For example, when determining the center of gravity, according to the theorem, for any two polygons, after determining the positions of the centers of gravity of the two polygons, the center of gravity of the combined graph may also be determined. Specifically, the position of the center of gravity thereof is necessarily on a line segment connecting the centers of gravity of the two polygons. Further, when the area of the polygon a is Sa, the area of the polygon B is Sb, the center of gravity of the polygon a is point a, the center of gravity of the polygon B is point B, and the center of gravity of a polygon formed by combining two polygons is point c, the following relationship exists: sa × ac — Sb × bc, and by this formula, the position of the center of gravity c can be obtained, where ac is used to indicate the distance between the point a and the point c; bc is used to represent the distance between point b and point c.
In the invention, for a complex sub-network, the complex sub-network can be an irregular concave polygon, in order to determine the position of the center of gravity according to the method, the irregular polygon can be firstly divided into a plurality of triangles, the triangles are combined step by step through the method, the center of gravity of the combined graph is determined, and finally the center of gravity of the whole irregular polygon can be calculated.
In some embodiments, the determining whether a sensing hole exists in the subnetwork according to the gas values may include: if the gas values are larger than or equal to a preset threshold value, determining that no sensing cavity exists in the sub-network; and if the gas values corresponding to the sensor nodes in the sub-network have the gas values smaller than the preset threshold value, determining that the sensing holes exist in the sub-network.
Before simulating gas simulation by the gravity center, a threshold value is required to be preset, the threshold value has no significance in gas simulation, but in signal transmission corresponding to the Internet of things, the threshold value represents signal strength which can just meet the signal receiving and transmitting conditions. If the signal is smaller than the threshold, the transmission and the reception of the signal will be affected, and the area smaller than the threshold cannot well realize the signal transmission and the signal coverage, and can be used as a perception hole area. Specifically, if the gas values detected by all the sensor nodes in the sub-network are greater than the preset threshold, that is, there is no area that cannot be covered by the signal in the sub-network, and therefore, there is no sensing hole area in the sub-network; if the gas value of part of the sensor nodes (outer sensor nodes) of the sub-network is smaller than the preset threshold value, it can be determined that the sensing holes exist in the sub-network, and then the area where the sensing holes are located is specifically determined.
In the embodiment of the invention, the covering mode of the signal is reflected by a mode of simulating gas diffusion, so that the accuracy of the calculation result can be ensured while the calculation mode is simplified.
On the basis of the above embodiment, the method for detecting a perceptual void of the present invention may further include: after determining that a perceived hole exists in the subnetwork, determining a location of the perceived hole based on: for the sensor nodes with the gas numerical value larger than or equal to the preset threshold value, determining the sensor nodes positioned at the outermost layer as inner boundary nodes of the perception cavity; for the sensor nodes with the gas values smaller than the preset threshold value, determining the sensor nodes positioned on the innermost layer as outer boundary nodes of the sensing cavity; connecting the inner boundary nodes, and determining an inner boundary area of the perception cavity; and connecting the outer boundary nodes to determine the outer boundary area of the perception cavity.
For a sub-network with a sensing cavity, the method aims to roughly determine an approximate area where the sensing cavity is located according to a gas value provided by an existing sensor node, specifically, when an inner boundary and an outer boundary are determined, firstly, the sensor node with the gas value larger than or equal to a preset threshold value and the sensor node with the gas value smaller than the preset threshold value are distinguished, and then, the outermost sensor node is determined to be an inner boundary node in the sensor nodes with the gas value larger than or equal to the preset threshold value, so that the sensing cavity can be determined to be located outside the inner boundary node (at a position farther from the center of gravity); and determining the sensor node at the innermost layer as an outer boundary node from the sensor nodes with the gas value smaller than the preset threshold, and determining that the sensing cavity is positioned inside the outer boundary node (at a position closer to the gravity center). Since the sensor nodes are distributed discretely, in order to determine the closed region where the sensing cavity is located, all inner boundary nodes need to be connected, and all outer boundary nodes need to be connected, so as to determine the inner boundary region and the outer boundary region respectively. At this time, the sensing cavity is located in a ring-like region surrounded by the inner boundary region and the outer boundary region.
Still further, the detection method for sensing the hole may further include: after determining the position of the perception hole, refining and positioning the perception hole according to the following modes: determining an interpolation point between the outer boundary region and the inner boundary region according to a radial base point interpolation method; and connecting the interpolation points and determining a refined boundary line. And determining the areas contained by the refined boundary lines and the outer boundary areas as the perception holes.
In order to refine the boundary line and further accurately determine the position of the sensing cavity, the method cannot be met only by adopting the existing sensor node. Therefore, the invention adopts a radial base point interpolation method, and determines the position of an interpolation point through a radial interpolation function, wherein the interpolation point is used as a critical point of the perception cavity, and the region outside the critical point is the perception cavity.
Illustratively, the interpolation function employed by the present invention is:
Figure BDA0003247636180000091
wherein, X refers to the distance from the gravity center point of the position needing interpolation at present. Xi is the distance of the location of the known sensor from the center of gravity point. (x) represents a gas value to be determined.
Wherein the content of the first and second substances,
Figure BDA0003247636180000092
in respect of c0And c1The method can be determined by a least square method according to the existing sensor nodes and gas values, and specifically, a regression linear equation of the least square method can be written as follows:
f(X1)＝c0+c1X1
f(X2)＝c0+c1X2
。。。
f(Xn)＝c0+c1Xn
in the above expression, the values of X and f (X) of a plurality of sensor nodes are substituted; at the same time, the known X is also calculated1To XnAverage value of (2)
Figure BDA0003247636180000093
And f (X)1) To f (X)n) Average value of (2)
Figure BDA0003247636180000094
Is provided with
Figure BDA0003247636180000095
The value of (a) is c,
Figure BDA0003247636180000096
if d, then:
Figure BDA0003247636180000097
in the formula, n is the number of the sensing nodes.
C is calculated1After the value of (c), by the expression:
Figure BDA0003247636180000101
c can be further determined0The value of (c).
In addition, in the interpolation function,
Figure BDA0003247636180000102
xclongitude, y, representing the center of gravity pointcRepresenting the latitude of the center of gravity point; x is the number ofiLongitude, y, representing the interpolation pointiRepresenting the latitude of the interpolation point;
when the interpolation point is calculated by the radial base point interpolation method, the sub-network is also subjected to grid division, and the grid division is performed, wherein firstly, the sensor nodes of the sub-network are required to be quantized so as to obtain the horizontal and vertical coordinates of the sensor nodes; secondly, interpolation can be performed only after the grid division is performed, and the interpolation function is discrete, so that the grid is more suitable for the interpolation function relative to a coordinate system. Further, the finer the meshing is, the more interpolation points are, and the more accurate the final result is.
The previous embodiments have discussed that, when the interpolation point is located, the gas value is exactly at the point of the preset threshold, so when calculating the interpolation point, f (x) needs to be equal to the preset threshold, and on this basis, the interpolation points are determined according to the above function, and theoretically, there are numerous interpolation points, and when the number of the interpolation points is larger, the refined boundary line is more accurate, and the finally determined sensing cavity is more accurate. In addition, when the interpolation points are connected to determine the refined boundary line, the connection mode may be line segment connection or smooth curve connection, and when the number of the interpolation points is large enough, the curves drawn by the interpolation points and the curve drawn by the interpolation points are the same.
After the refined boundary line is determined, the position of the perception cavity is accurately determined, the determination method is that an annular area formed by the refined boundary line and an outer boundary area is smaller than an annular area formed by the outer boundary area and an inner boundary area.
In the embodiment of the invention, the irregularity of the boundary region is considered, the radial base point interpolation method is adopted to realize the nonlinear interpolation, and the spatial characteristics (c0, c1 and c 1) of a plurality of known values of the interpolation function are combined at the same time
Figure BDA0003247636180000103
) Also takes into account the distance lambda between the position to be interpolated and the center of gravityiTherefore, the obtained interpolation result is closer to a real numerical value, and compared with the method of determining a cavity region by adopting a mobile sensor, the method greatly reduces the energy consumption and improves the efficiency.
In some implementations, further, the method for detecting a perceptual void in the present invention may further include: and determining whether the sensing holes exist in the Internet of things or not according to the detection result of whether the sensing holes exist in at least one sub-network contained in the Internet of things or not.
In the actual processing, the final output result is whether the sensing holes exist in the whole internet of things or not and the positions of the sensing holes, so after the positions of the sensing holes in each sub-network are determined, the sensing holes existing in the internet of things are finally determined through integration.
Next, the method for detecting perceived holes provided by the present invention is described by specific images, and fig. 3, 4, 5, and 6 are diagrams illustrating relevant structures of sub-networks of the method for detecting perceived holes in an embodiment of the present invention.
Firstly, dividing a sub-network into a plurality of sub-networks, wherein the principle of dividing the sub-networks is as follows: if each sensor node can be connected to the same gateway in a certain area, the network topology formed by the sensor nodes is divided into a sub-network. Fig. 3 is a diagram illustrating a structure of a sub-network of the detection method for sensing holes according to the embodiment of the present invention, and as shown in fig. 3, a circle represents a sensor node, and outermost sensor nodes (S2, S3, O1 to O15) are connected to form an irregular polygon.
And secondly, determining the gravity centers of the sub-networks, and finding the gravity centers in the irregular polygons. The method for determining the network gravity center of the irregular polygon is more, and the method for finding the gravity center of the irregular polygon can be as follows: the intersection point of the three central lines of the triangle is the gravity center of the triangle, and for any polygon, the gravity center of the polygon can be found out by a ruler-drawing method through the following theorem, and the sub-network behind the gravity center is determined. Fig. 4 is an exemplary diagram of the center of gravity of the subnetwork structure shown in fig. 3, and as shown in fig. 4, Xc is the center of gravity in the diagram.
And thirdly, finding out a boundary area of the sub-network, simulating gas diffusion into the sub-network area by taking the gravity center of the irregular polygon of the sub-network as a central point, wherein the simulated gas diffusion can be toxic gas diffusion, and then detecting and acquiring the gas value detected by each sensor node. Sensor nodes with gas values smaller than a preset threshold value exist in the sub-network, namely, sensing holes exist. At the moment, setting the sensor node with the outermost layer larger than the preset threshold as an inner boundary node under the condition that the gas value is larger than the preset threshold; and for the condition that the gas value is smaller than the preset threshold value, setting the sensor node of which the innermost layer is smaller than the preset threshold value as an outer boundary node. FIG. 5 is an exemplary diagram of the inner and outer boundary regions of the sub-network structure shown in FIG. 3, where the sensor nodes labeled I1, I2, I3, I4, and I5 are the inner boundary nodes, as shown in FIG. 5; the sensor nodes marked as S1-S12 are outer boundary nodes; o1 to O15, S12 and S13 are the outermost peripheral sensor nodes of the sub-network. Connecting the sensor nodes of the inner boundary node to determine an inner boundary area; and connecting the sensor nodes of the outer boundary nodes to determine an outer boundary area. The connection mode of the sensor nodes can be a line connection mode.
And fourthly, refining the boundary line, drawing the boundary line and determining the perception cavity. Interpolation is carried out at the position where the detected gas value is just the preset threshold value through a radial base point interpolation method, and interpolation points are connected to obtain a refined boundary line. And after the refined boundary line is determined, the area enclosed by the refined boundary line and the outer boundary area is the perception hole of the sub-network. Fig. 6 is an exemplary diagram of a refined boundary line of the sub-network structure shown in fig. 3, where as shown in fig. 6, the sensor nodes labeled I1, I2, I3, I4, and I5 are inner boundary nodes; the sensor nodes marked as S1-S12 are outer boundary nodes; o1 to O15, S12 and S13 are the outermost peripheral sensor nodes of the sub-network. And a closed area surrounded by the refined boundary line and the outer boundary area is a sensing cavity. By the method, the area where the perception hole in each sub-network is located can be determined, and then the perception hole of the whole Internet of things is determined.
Fig. 7 is a schematic structural diagram of a device for detecting a perceived void according to an embodiment of the present invention. The detection device for the sensing hole is applied to the Internet of things, and the Internet of things comprises a plurality of sensor nodes. As shown in fig. 7, the apparatus 700 for detecting a perceived hole includes:
a determining module 701, configured to determine at least one sub-network included in the internet of things according to a network topology relationship of the plurality of sensor nodes; and determining a center of gravity of the subnetwork.
A simulation module 702, configured to simulate gas diffusion with the center of gravity of the subnetwork as a center point;
an obtaining module 703, configured to obtain a gas value detected by each sensor node in the sub-network;
the determining module 701 is further configured to determine whether a sensing hole exists in the subnetwork according to each gas value.
In some embodiments, the determining module 701 is specifically configured to: determining gateway equipment contained in the Internet of things; and determining sub-networks included in the Internet of things according to the network topological relations of the sensor nodes and the gateway equipment, wherein the sensor nodes in the sub-networks are connected to the same gateway equipment.
In some embodiments, the determining module 701 is specifically configured to: connecting the outermost sensor nodes in the sub-network to form a polygon; the center of gravity of the polygon is determined as the center of gravity of the sub-network.
In some embodiments, the determining module 701 is specifically configured to: if the gas values are larger than or equal to a preset threshold value, determining that no sensing cavity exists in the sub-network; and if the gas values corresponding to the sensor nodes in the sub-network have the gas values smaller than the preset threshold value, determining that the sensing holes exist in the sub-network.
In some embodiments, the determining module 701 is further configured to: after determining that a perceived hole exists in the subnetwork, determining a location of the perceived hole based on: for the sensor nodes with the gas numerical value larger than or equal to the preset threshold value, determining the sensor nodes positioned at the outermost layer as inner boundary nodes of the perception cavity; for the sensor nodes with the gas values smaller than the preset threshold value, determining the sensor nodes positioned on the innermost layer as outer boundary nodes of the sensing cavity; connecting the inner boundary nodes, and determining an inner boundary area of the perception cavity; and connecting the outer boundary nodes to determine the outer boundary area of the perception cavity.
In some embodiments, the determining module 701 is further configured to: after determining the position of the perception hole, refining and positioning the perception hole according to the following modes: determining an interpolation point between the outer boundary region and the inner boundary region according to a radial base point interpolation method; and connecting the interpolation points and determining a refined boundary line.
In some embodiments, the determining module 701 is further configured to: and determining whether the sensing holes exist in the Internet of things or not according to the detection result of whether the sensing holes exist in at least one sub-network contained in the Internet of things or not.
The apparatus provided in the embodiments of the present invention may be used to execute the method of the embodiments described above, and the implementation principle and the technical effect are similar, which are not described herein again.
It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the processing module may be a processing element separately set up, or may be implemented by being integrated in a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and a function of the processing module may be called and executed by a processing element of the apparatus. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.
For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when some of the above modules are implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can call program code. As another example, these modules may be integrated together, implemented in the form of a system-on-a-chip (SOC).
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. Illustratively, the electronic device may be provided as a server or a computer. Referring to fig. 8, an electronic device 800 includes a processing component 801 that further includes one or more processors, and memory resources, represented by memory 802, for storing instructions, such as application programs, that are executable by the processing component 801. The application programs stored in memory 802 may include one or more modules that each correspond to a set of instructions. Furthermore, the processing component 801 is configured to execute instructions to perform any of the method embodiments described above.
The electronic device 800 may also include a power component 803 configured to perform power management of the electronic device 800, a wired or wireless network interface 804 configured to connect the electronic device 800 to a network, and an input/output (I/O) interface 805. The electronic device 800 may operate based on an operating system stored in memory 802, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, or the like.
The invention also provides a computer-readable storage medium, in which computer-executable instructions are stored, and when a processor executes the computer-executable instructions, the scheme of the detection method for sensing the holes is realized.
The present invention also provides a computer program product comprising a computer program which, when executed by a processor, implements the solution of the method for detecting perceived holes as above.
The computer-readable storage medium may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. Readable storage media can be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary readable storage medium is coupled to the processor such the processor can read information from, and write information to, the readable storage medium. Of course, the readable storage medium may also be an integral part of the processor. The processor and the readable storage medium may reside in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the readable storage medium may also reside as discrete components in the detection apparatus for sensing holes.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments,
those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A detection method for a perception hole is applied to the Internet of things, the Internet of things comprises a plurality of sensor nodes, and the detection method for the perception hole comprises the following steps:
determining at least one sub-network included in the Internet of things according to the network topological relation of the plurality of sensor nodes;
performing the following for each of the sub-networks:
determining a center of gravity of the subnetwork;
simulating gas diffusion by taking the gravity center of the sub-network as a central point;
acquiring gas values detected by all sensor nodes in the sub-network;
determining whether a sensing void exists in the subnetwork based on each of the gas values.
2. The method for detecting perceived holes as claimed in claim 1, wherein said determining the sub-networks included in the internet of things according to the network topology relationship of the plurality of sensor nodes comprises:
determining gateway equipment contained in the Internet of things;
and determining a sub-network included in the Internet of things according to the network topological relation between the plurality of sensor nodes and the gateway equipment, wherein the sensor nodes in the sub-network are connected to the same gateway equipment.
3. The method for perceptual hole detection as defined in claim 1, wherein said determining a center of gravity of the sub-network comprises:
connecting the outermost sensor nodes in the sub-network to form a polygon;
determining the center of gravity of the polygon as the center of gravity of the sub-network.
4. The method for detecting a perceived hole as claimed in any one of claims 1 to 3, wherein said determining whether a perceived hole exists in said sub-network based on each of said gas values comprises:
if the gas values are larger than or equal to a preset threshold value, determining that no sensing cavity exists in the sub-network;
and if the gas values corresponding to the sensor nodes in the sub-network have gas values smaller than a preset threshold value, determining that a sensing hole exists in the sub-network.
5. The method for detecting perceptual holes according to claim 4, further comprising:
after determining that a perceived hole exists in the subnetwork, determining a location of the perceived hole based on:
for the sensor nodes with the gas numerical value larger than or equal to the preset threshold value, determining the sensor nodes positioned at the outermost layer as inner boundary nodes of the perception cavity;
for the sensor nodes with the gas values smaller than the preset threshold value, determining the sensor nodes positioned at the innermost layer as outer boundary nodes of the perception cavity;
connecting each inner boundary node, and determining an inner boundary area of the perception cavity;
and connecting the outer boundary nodes, and determining the outer boundary area of the perception cavity.
6. The method for detecting perceptual holes of claim 5, further comprising:
after determining the position of the perceptual hole, refining and positioning the perceptual hole according to the following modes:
determining an interpolation point between the outer boundary region and the inner boundary region according to a radial basis point interpolation method;
connecting the interpolation points and determining the refined boundary line;
determining an area included by the refined boundary line and the outer boundary area as the perceived hole.
7. The method for detecting a perceptual hole according to any one of claims 1 to 3, further comprising:
and determining whether a perception hole exists in the Internet of things according to the detection result of whether the perception hole exists in at least one sub-network contained in the Internet of things.
8. The utility model provides a detection device in perception hole, its characterized in that is applied to the thing networking, the thing networking contains a plurality of sensor nodes, detection device in perception hole includes:
the determining module is used for determining at least one sub-network contained in the Internet of things according to the network topological relation of the plurality of sensor nodes; and determining a center of gravity of the subnetwork;
the simulation module is used for simulating gas diffusion by taking the gravity center of the sub-network as a central point;
the acquisition module is used for acquiring the gas values detected by all the sensor nodes in the sub-network;
the determining module is further configured to determine whether a sensing hole exists in the subnetwork according to each of the gas values.
9. An electronic device, comprising: a memory and a processor;
the memory is to store program instructions;
the processor is configured to invoke program instructions in the memory to perform the method for perceived hole detection of any of claims 1 to 7.
10. A computer-readable storage medium having computer program instructions stored therein, which when executed, implement the method for detecting perceptual holes as defined in any one of claims 1 to 7.
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