CN109640332B - Three-dimensional monitoring topology system of Internet of things and reliability quantitative analysis method - Google Patents
Three-dimensional monitoring topology system of Internet of things and reliability quantitative analysis method Download PDFInfo
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Abstract
The invention relates to an Internet of things three-dimensional monitoring topology system and a reliability quantitative analysis method, which are characterized in that: the system comprises a factory monitoring area node, factory surrounding monitoring area nodes, a monitoring party gateway, a receiving party gateway and a monitoring server; the factory monitoring area node is arranged in a factory area range to be monitored, and is used for monitoring the haze condition in the factory area range to be monitored and sending the haze condition to the monitoring side gateway; the monitoring area nodes around the plant area are arranged at the periphery of the plant area to be monitored and used for monitoring the haze condition around the plant area to be monitored and sending the haze condition to the monitoring gateway; the monitoring side gateway is arranged in the range of a factory area to be monitored and is used for sending monitoring data to the receiving side gateway through a remote GPRS/3G technology, a remote Internet technology or a remote Beidou/satellite technology and receiving feedback information of the receiving side gateway; and the gateway of the receiving party uploads the received monitoring data to the monitoring server. The invention can be widely applied to the field of monitoring of the Internet of things.
Description
Technical Field
The invention relates to the technical field of Internet of things, in particular to a three-dimensional monitoring topological system of the Internet of things and a reliability quantitative analysis method.
Background
The technology of the internet of things is a new field in information technology, and more industries use the internet of things to realize remote monitoring tasks. Apply internet of things to haze heavy point pollution source monitoring, its advantage has: deploying the sensor nodes at the sewage discharge positions of the enterprises can monitor whether the sewage discharge amount of the enterprises exceeds the standard or not in real time; deploying the fine granularity of the sensor in a monitoring enterprise to detect whether the enterprise has unorganized emission or not, whether a sudden pollution source or not and the like; the characteristics of low cost and wide coverage of the sensor nodes of the Internet of things are utilized, the sensor nodes are deployed at the periphery of the detected enterprise to monitor the influence on the surrounding air quality in real time, and whether the monitored enterprise has phenomena of stealing, disordering and the like can be inverted only from the monitoring pollution result; the Internet of things can be effectively combined with GPRS, 3G, satellite communication, wireless communication and China Beidou satellite communication, and the independence of remote communication is achieved; the wireless sensor network of the Internet of things can flexibly arrange the network and track and monitor a new pollution source in time, people can timely scatter wireless sensor nodes in an environment needing to be monitored according to requirements to form a monitoring network in a dynamic self-organizing manner without special network equipment and professional maintenance, more importantly, the distance between sensors can be reduced by increasing the density of the sensors with low cost, the accuracy of monitoring information can be improved, and the reliability of monitoring data is solved.
Node deployment of a sensor network in the internet of things mainly studies how to deploy a certain number of nodes at appropriate positions of a monitoring area according to application requirements and deployment modes allowed by an application environment so as to realize coverage of a sensing range on the whole monitoring area and meet requirements of network application on deployment time cost, network connectivity, reliability, energy efficiency and the like. The deployment mode of the sensor nodes in the internet of things is generally determined by a specific application environment, and the common deployment modes include two types: deterministic deployment and random shedding deployment. The reliability of the network, the coverage and connectivity of the network, the cost of node deployment, and energy holes are all constraints and pursuits to be considered when the nodes are deployed. The existing research results show that the two-dimensional space node deployment method is relatively mature, but the research results for node deployment in a three-dimensional space are few. In the aspect of research on data transmission reliability of the internet of things, retransmission redundancy is often adopted to ensure reliability, and real-time performance of data transmission is inevitably reduced.
Disclosure of Invention
In view of the above problems, the present invention aims to provide an internet of things three-dimensional monitoring topology system and a reliability quantitative analysis method, which improve reliability of internet of things data transmission and real-time performance of data transmission by reliable topological deployment of fine-grained three-dimensional internet of things nodes in and around a plant to be monitored.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides an Internet of things three-dimensional monitoring topology system, which comprises plant area monitoring area nodes, plant area surrounding monitoring area nodes, a monitoring party gateway, a receiving party gateway and a monitoring server, wherein the monitoring area nodes are distributed on the periphery of a plant area; the plant area monitoring area node is arranged in a plant area range to be monitored, and is used for monitoring the haze condition in the plant area range to be monitored and sending the haze condition to the monitoring side gateway; the monitoring area nodes around the plant area are arranged at the periphery of the plant area to be monitored and are used for monitoring the haze condition around the plant area to be monitored and sending the haze condition to the monitoring side gateway; the monitoring side gateway is arranged in the range of a factory area to be monitored and used for sending monitoring data to the receiving side gateway through a remote GPRS/3G technology, a remote Internet technology or a remote Beidou/satellite technology and receiving feedback information of the receiving side gateway; and the gateway of the receiving party uploads the received monitoring data to the monitoring server for a supervisor to monitor and receive alarm in real time through the Internet or a mobile terminal, or performs related configuration and management on a monitoring network, issues task actions and updates monitoring frequency.
Furthermore, the node deployment of the plant area monitoring area adopts a single Sink multilevel cluster structure, the basic monitoring bodies on the innermost layer are deployed by taking the center of gravity of the pollution source of the plant area to be monitored as the center of a circle, and other layers of basic monitoring bodies are sequentially deployed until the whole plant area to be monitored is covered; a coordinator node is configured in the innermost basic monitoring body and serves as a Sink node of the whole plant area monitoring area, and the coordinator node is responsible for communication with the monitoring party gateway and is called a primary cluster head; each node with a routing function in the basic monitoring bodies of the second layer nearest to the coordinator node is used as a secondary cluster head; and the nodes with the routing function in the basic monitoring bodies of other layers from inside to outside are sequentially used as three-level cluster heads, four-level cluster heads to N-level cluster head nodes.
Furthermore, the basic monitoring body is composed of one data monitoring forwarding node and six data monitoring nodes deployed around the data monitoring forwarding node, distances between the data monitoring nodes and the data monitoring forwarding node are equal, and all the nodes form a regular hexagon monitoring body together.
Furthermore, the monitoring area nodes around the plant area comprise strip-shaped rectangular area monitoring bodies deployed around the plant area to be monitored, the sensor nodes in the rectangular area monitoring bodies are placed on two long sides of the strip-shaped rectangular area in a staggered mode, and the centers of every two adjacent three nodes form an isosceles triangle.
In another aspect of the invention, a reliability quantitative analysis method for a three-dimensional monitoring topology system of the internet of things is provided, which includes the following steps: 1) deploying plant area monitoring area nodes in a plant area range to be monitored, and determining related parameters of a plant area monitoring area node topological structure; 2) deploying monitoring area nodes around a factory area to be monitored, and determining related parameters of a topological structure of the monitoring area nodes around the factory area; 3) carrying out quantitative analysis on the reliability of the multilevel cluster structure of the plant monitoring area nodes in the range of the plant to be monitored to obtain the reliability of the multilevel cluster structure; 4) and carrying out quantitative analysis on the reliability of the remote transmission backbones with different redundancy structures.
Further, in the step 1), the method for deploying the plant area monitoring area nodes in the plant area range to be monitored and determining the relevant parameters of the topological structure of the plant area monitoring area nodes includes the following steps:
1.1) determining the relation between the distance between adjacent cluster heads and the sampling radius of a regular hexagon basic monitoring body in the adopted single Sink multilevel cluster structure:
in the formula, d is the sampling radius of the regular hexagon basic monitoring body;
1.2) determining the relation between the sampling radius of the regular hexagon basic monitoring body and the sensing radius of the sensor node according to the relation between the obtained distance between the adjacent cluster heads and the sampling radius of the regular hexagon basic monitoring body:
in the formula, RsThe sensing radius of the sensor node;
1.3) calculating the relation between the total layer number N of the plant area monitoring area node topological structure, the sensing radius of the sensor and the ideal monitoring area according to the relation between the sampling radius of the regular hexagon basic monitoring body and the sensing radius of the sensor node:
in the formula, S is the area of an ideal monitoring area;
1.4) calculating to obtain the total number N of layers of the topological structure in the monitoring area and the total number N of cluster head nodes in the monitoring area according to the relationship between the total number N of layers of the topological structure in the monitoring area and the sensing radius of the sensor and the area of the ideal monitoring areakeyThe relationship of (1):
Nkey＝3N(N-1)+1。
further, in the step 2), the method for deploying the nodes of the monitoring area around the factory area to be monitored and determining the relevant parameters of the topological structure of the nodes of the monitoring area around the factory area comprises the following steps:
2.1) calculating the relation between the adjacent distance of the rectangular area and the sensing radius of the sensor according to the width of the rectangular area and the sensing radius of the sensor node:
wherein W is the width of the rectangular region, RsThe sensing radius of the sensor node is d, and the adjacent distance of the strip rectangular area is d;
2.2) calculating the total node number N required by the rectangular area with the length of L according to the relationship between the adjacent distance of the rectangular area with the strip shape and the sensing radius of the sensorexRelationship to the sensing radius of the sensor:
in the formula, L is the length of a long strip-shaped rectangular area;
2.3) calculating to obtain the relation between the adjacent distance meeting the 1-fold coverage condition and the sensing radius of the sensor node according to the relation between the coverage density of the strip rectangular area and the total node number:
d＝1.5Rs。
further, in the step 4), the method for quantitatively analyzing the reliability of the remote transmission backbone with different redundancy structures includes the following steps:
4.1) carrying out quantitative analysis on the reliability of the system with the parallel redundancy to obtain the reliability and the average fault interval time;
the reliability of the system is:
where n is the number of components of the parallel redundant system, Ri(t), i ═ 1, 2.., n is the reliability of each component;
when in use
Then
The mean time between failure of the system is:
4.2) carrying out quantitative analysis on the reliability of the voting redundancy system taking k from n to obtain the reliability and the average fault interval time of the voting redundancy system;
if all the components start to work at the same time at the initial moment, the reliability of the system is
In the formula, X1,X2,...,XnIs the lifetime X of n components in the systemi；
When R is0(t)＝e-λtWhen it is, then there are
In the formula, λ is a failure rate.
Due to the adoption of the technical scheme, the invention has the following advantages: 1. the method takes the center of gravity of a pollution source as the center to deploy a monitoring area inside a plant area, provides a uniformly clustered modular node deployment method under the condition of meeting the requirements of network coverage and connectivity, provides a calculation formula for mutual relation and quantification of parameters such as the area of the monitoring area, the sensing radius of the monitoring node, the total number of layers of a topological structure, the number of monitoring key nodes and the like, and lays a solid theoretical foundation for practical deployment application; 2. in order to solve the problem of interruption of a monitoring system or abnormal monitoring data, a rectangle is taken as a basic monitoring area at the periphery of the monitoring area, and a principle of minimizing the number of deployed nodes, namely minimizing the cost, is adopted, an isosceles triangle one-time coverage deployment scheme is provided, and a quantitative formula of the width, the adjacent distance between nodes and the sensing radius of the monitoring nodes under rectangular deployment is provided; 3. the reliability quantitative analysis formula of the uniform clustering topological structure is given by a reliability block model; 4. in the aspect of a reliability guarantee mechanism of a remote transmission backbone, a quantitative calculation formula of system reliability and mean fault interval time under a parallel redundancy and voting redundancy system is provided, characteristics of four different redundancy modes are compared, and a 3-parallel redundancy mode is provided, so that mean fault interval can be prolonged, reliability of a backbone transmission part of an Internet of things remote monitoring system can be improved, and theoretical reference is provided for practical application.
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FIG. 1 is a schematic overall architecture diagram of a three-dimensional monitoring topology structure of the Internet of things;
FIG. 2 is a schematic view of a three-dimensional monitoring network consisting of basic monitoring areas, FIG. 2(a) is an abstract view of three-dimensional deployment, and FIG. 2(b) is a top view of three-dimensional deployment according to the present invention;
FIG. 3 is a diagram of a secondary cluster head configuration of the present invention;
FIG. 4 is a multi-stage cluster head architecture of the present invention;
FIG. 5 is a diagram illustrating the structure of a basic monitoring body BA defined in the present invention;
FIG. 6 is a plan view of a rectangular area of the present invention;
FIG. 7 is a diagram of an isosceles triangle 1-fold full coverage node deployment of the present invention;
FIG. 8(a) is a block diagram of the reliability of the multilevel cluster structure of the present invention;
FIG. 8(b) is a block diagram of the reliability of a single cluster structure of the present invention;
FIG. 9 is a block diagram of the parallel redundancy reliability of the present invention;
FIG. 10 is a block diagram of the reliability of the voting system of the present invention;
FIG. 11 is a graph of reliability of different redundant systems of the present invention as a function of failure rate;
FIG. 12 is a graph of mean time between failure versus failure rate for different redundant systems of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and examples.
As shown in fig. 1, the three-dimensional monitoring topology system of the internet of things provided by the invention comprises plant area monitoring area nodes, plant area surrounding monitoring area nodes, a monitoring party gateway, a receiving party gateway and a monitoring server. The factory monitoring area node is arranged in a factory range to be monitored, and is used for monitoring the haze condition in the factory range and sending the haze condition to the monitoring side gateway; the monitoring area nodes around the factory area are arranged at the periphery of the factory area to be monitored and are used for monitoring the haze condition around the factory area and sending the haze condition to the monitoring gateway; the monitoring side gateway is arranged in the range of a factory area to be monitored and is used for sending monitoring data to the receiving side gateway through a remote GPRS/3G technology, a remote Internet technology or a remote Beidou/satellite technology and receiving feedback information of the receiving side gateway; and the gateway of the receiving party uploads the received monitoring data to a monitoring server for monitoring and receiving alarm by a monitoring person in real time through the Internet or a mobile terminal, or performs related configuration and management on a monitoring network, issues task actions, updates monitoring frequency and the like.
As shown in fig. 2(a) and 2(b), a plant area monitoring area node includes a plurality of basic monitoring bodies arranged in sequence from inside to outside, and the innermost basic monitoring body is deployed with the center of gravity of a plant area pollution source to be monitored as the center of a circle, and the basic monitoring bodies are recombined according to the radius of the monitoring area and are deployed in sequence until the whole plant area monitoring area is covered; the monitoring area nodes around the plant area take a rectangle as a basic unit and are deployed by adopting an isosceles triangle to form a three-dimensional monitoring network.
As shown in fig. 3 and 4, the entire plant area monitoring area node deployment adopts a single Sink multi-level cluster structure, and a coordinator node is uniquely configured to serve as the Sink node of the entire plant area monitoring area and is responsible for communication with a monitoring gateway, which is called a first-level cluster head, and a node having a routing function and closest to the coordinator node serves as a second-level cluster head, which sequentially serves as a third-level cluster head, a fourth-level cluster head, … … and an N-level cluster head node from inside to outside. The cluster head node and the coordinator node have the functions of aggregation and forwarding, are more important than the common monitoring node in function, and are called as key nodes. In practical monitoring application, the basic monitoring bodies can be reasonably recombined according to the radius of a monitoring area, and meanwhile, the topological structure of the regular hexagon is ensured not to change.
As shown in fig. 5, each basic monitoring body is composed of one data monitoring forwarding node (black node in the figure) and six data monitoring nodes (white nodes in the figure) disposed around the data monitoring forwarding node, distances between the data monitoring nodes and the data monitoring forwarding node are equal, and all the nodes together form a regular hexagon monitoring body. In the invention, 6 data monitoring nodes are common nodes for monitoring data, and data forwarding is not carried out, so that the service life of the nodes can be prolonged; the distance between the 1 data monitoring forwarding node and the other 6 data monitoring nodes is equal, the routing function is achieved, the data monitoring forwarding node can monitor data and forward the data, the function of a cluster head is achieved, and the data monitored by the surrounding nodes are received and forwarded. Firstly, because the monitoring nodes of the basic monitoring body are uniformly distributed, a good foundation is laid for the accurate fusion of the data of the basic monitoring body and even the whole monitoring area; secondly, the basic monitoring body is provided with a sink node which has the relatively equal distance with other nodes and bears the cluster head function, so that the energy consumption is balanced and the whole system is energy-saving; and thirdly, the monitoring nodes which do not need to be routed and only bear the monitoring function adopt a static routing mode to directly communicate with the sink node so as to reduce energy consumption, and because the monitoring nodes do not communicate with each other, the transmission function of the whole monitoring system cannot be interrupted due to the failure of any monitoring node.
The basic monitoring body can be adjusted according to the area needing to be monitored actually, if the area needing to be monitored actually is smaller than the area of the basic monitoring body, the distance between the central node of the basic monitoring body and the peripheral nodes is adjusted to achieve the purpose of being equal to the actual monitoring radius, if the area needing to be monitored actually is larger than the monitoring area of the basic monitoring body, the basic monitoring body is used for being densely paved, and meanwhile, the regular hexagon topological structure is kept unchanged.
As shown in fig. 6 and 7, the plant area surrounding monitoring area nodes include strip-shaped rectangular area monitoring bodies deployed around the plant area to be monitored, the sensor nodes in the monitoring bodies are placed on two long sides of the strip-shaped rectangular area in a staggered manner, and the centers of every two adjacent nodes form an isosceles triangle.
Based on the three-dimensional monitoring topological system of the internet of things, the invention also provides a reliability quantitative analysis method of the three-dimensional monitoring topological system of the internet of things, which comprises the following steps:
1) and deploying factory monitoring area nodes in a factory range to be monitored, and determining related parameters of a topological structure of the factory monitoring area nodes.
Specifically, the method comprises the following steps:
1.1) determining the relation between the distance between adjacent cluster heads and the sampling radius of a regular hexagon basic monitoring body in the adopted single Sink multilevel cluster structure.
To ensure that any two nodes can communicate with each other, a single Sink multi-level cluster structure is adopted, a sensor in a single cluster transmits information to a cluster head node, meanwhile, sensing data are transmitted to an i-1 layer of cluster heads from an i-layer of cluster heads, wherein i is 2, 3 …, k, and a first-level cluster structure represents a regular hexagon unit located in the center of the center, namely a unit where a coordinator node Sink is located.
In the single Sink multilevel cluster structure, the distance between adjacent cluster heads is as follows:
wherein d is the sampling radius of the regular hexagonal basic monitoring body.
1.2) determining the relation between the sampling radius of the regular hexagon basic monitoring body and the sensing radius of the sensor node according to the relation between the obtained distance between the adjacent cluster heads and the sampling radius of the regular hexagon basic monitoring body.
In the whole structure, in order to ensure that the sensor nodes cover the whole hexagonal area, the sensing radius of the sensor nodes is required to be larger than the sampling radius of the basic monitoring body, namely
RS≥d (2)
In the formula, RsIs the sensing radius of the sensor node, which can be obtained according to the product specification.
Meanwhile, in order to meet connectivity and ensure normal communication between adjacent layer cluster head nodes, the sensing radius of the sensor node is required to be larger than the distance between two adjacent cluster heads at the same time, namely:
combining the formula (2) and the formula (3) to obtain the sensing radius R of the sensor nodeSComprises the following steps:
that is, in order to ensure the coverage and connectivity of the network, the relation between the sampling radius of the regular hexagon basic monitoring body and the sensing radius of the sensor is as follows:
1.3) calculating the relation between the total layer number N of the plant area monitoring area node topological structure, the sensing radius of the sensor and the ideal monitoring area according to the relation between the sampling radius of the regular hexagon basic monitoring body and the sensing radius of the sensor node.
As can be obtained from fig. 4, the relationship between the total number N of layers of the plant area monitoring area node topology structure and the sampling radius of the regular hexagon basic monitoring body is shown in table 1 below:
TABLE 1 layer number vs. sampling radius Table
| Number of layers (N) | Radius of sampling |
| 1 | |
| 2 | 3d |
| 3 | 5d |
| 4 | 7d |
| … | … |
| i | (2*i-1)*d |
As can be seen from table 1, the number of layers N and the ideal monitoring area S satisfy:
S＝π*[(2*N-1)*d]2 (6)
the number of layers can be calculated from equation (6):
substituting the formula (5) into the formula (7) to obtain the relation between the total layer number N of the plant area monitoring area node topological structure, the sensing radius of the sensor and the ideal monitoring area:
1.4) according to the total number N of layers of the topological structure in the monitoring area and the sensing half of the sensorCalculating the relation between the diameter and the area of the ideal monitoring area to obtain the total number N of layers of the topological structure in the monitoring area and the total number N of cluster head nodes in the monitoring areakeyThe relationship (2) of (c).
Let the number of cluster head nodes of the ith layer be Nkey(i)
Then:
Nkey＝6(N-1)+3(N-1)(N-2)+1,(N>＝1) (10)
reduction of equation (10)
Nkey＝3N(N-1)+1 (11)
2) And deploying monitoring area nodes around the plant area to be monitored, and determining related parameters of a topological structure of the monitoring area nodes around the plant area.
In order to improve the monitoring reliability, the characteristics of low cost, wide coverage range and the like of the sensor nodes of the Internet of things are utilized, the sensor nodes are deployed at the periphery of the monitored enterprise, the influence on the surrounding air quality is monitored in real time, and whether the monitored enterprise has phenomena of stealing, disordering and the like can be inverted only from the monitoring pollution result. Firstly, monitoring a peripheral area, wherein the characteristic of full coverage is required to be met; secondly, the cost is saved, so that the number of nodes in the peripheral monitoring area is minimum; on the premise of meeting the above requirements, the peripheral region is equivalent to be composed of four substantially rectangular regions, and a model of the substantially rectangular regions is as shown in fig. 6 below. Defining the rectangular area as L in length, W in width, S in area, S ═ L × W, and L > W, and assuming a sensing radius R of the sensors>W。
2.1) calculating the relation between the adjacent distance of the rectangular area and the sensing radius of the sensor according to the width of the rectangular area and the sensing radius of the sensor node.
In the invention, the adjacent distance refers to the horizontal distance between two circle centers of two adjacent nodes along the length direction of the rectangular region; "1-covering isosceles triangle deployment" means that the array is composed of a set of sensing radii RsThe nodes are alternately arranged at two sides of the strip-shaped rectangular area, and the centers of every three adjacent nodes form a triangle (as shown in fig. 7).
To ensure 1-fold full coverage of the rectangular region
2.2) calculating the total node number N required by the rectangular area with the length of L according to the relationship between the adjacent distance of the rectangular area with the strip shape and the sensing radius of the sensorexRelationship to the sensing radius of the sensor:
Nex＝L/d (13)
and 2.3) calculating to obtain the relation between the adjacent distance meeting the 1-fold coverage condition and the sensing radius of the sensor node according to the relation between the coverage density of the strip rectangular region and the total node number.
In the present invention, the Coverage Density (Coverage Density) of the rectangular strip region refers to the ratio of the sum of the Coverage areas of all nodes to the area of the region to be covered, and is expressed as ρ:
namely:
as can be seen from equation (16), N is requiredexThe minimum value of (c) is obtained by finding ρ, and substituting equation (14) into equation (16) to simplify:
the derivative is obtained, ρ is the minimum value, then
Substituting equation (19) into equation (12) yields
d＝1.5Rs (20)
That is, let the sensing radius of the sensor in the detection area be RsThe number of nodes is NexWhen the length of the rectangular region is L and the width is W, the adjacent distance d is 1.5Rs，
In time, 1-fold full coverage of isosceles triangle can be realized, and the number of nodes is NexGet the minimum value, and the total number of nodes NexComprises the following steps: 2L/3Rs。
3) And carrying out quantitative analysis on the reliability of the multilevel cluster structure of the plant monitoring area nodes in the range of the plant to be monitored to obtain the reliability of the multilevel cluster.
As shown in fig. 8(a), the reliability block diagram of the multi-level cluster structure is shown, the entire monitoring area is a multi-level cluster structure, and the reliability analysis of the multi-level cluster structure can be performed by decomposing a complex system into subsystems, then determining the reliability of each subsystem, and finally combining the subsystems. The multilevel cluster structure can be abstracted from the point of view of data aggregation into k basic monitoring bodies Ci(i is more than or equal to 1 and less than or equal to k).
As shown in FIG. 8(b), for each basic monitoring body, each basic monitoring body CiFrom 1 cluster head node CHiAnd m sensing nodes Si(i is more than or equal to 1 and less than or equal to m).
As can be seen from fig. 8(b), each cluster structure is formed by connecting m sensing nodes and 1 cluster head node in parallel, and the reliability of the basic monitoring body is as follows:
the whole internal monitoring area is composed of k basic monitoring bodies, and when the k basic monitoring bodies are effective at the same time, the whole internal monitoring area is reliable, so that the reliability of the multilevel cluster structure is as follows:
4) and carrying out quantitative analysis on the reliability of the remote transmission backbones with different redundancy structures.
The current remote transmission modes of the Internet of things comprise GPRS, 3G, Internet, satellite communication, microwave, Beidou satellite short message transmission and the like. The communication modes have advantages and disadvantages in the aspects of cost, transmission content, performance, bandwidth and the like, and when the monitoring system of the internet of things is actually deployed, different transmission modes are selected for transmission according to the actual communication condition of a monitoring area, so that the reliability of backbone transmission is improved. For example, a remote satellite/Beidou or a remote GPRS/3G can be adopted for transmission.
4.1) carrying out quantitative analysis on the reliability of the system with the parallel redundancy to obtain the reliability and the average fault interval time.
FIG. 9 shows a backbone transport architecture diagram for remote monitoring, where GW isMIs a monitoring area gateway, GWCIs a gateway of a monitoring center, Rs1，Rs2，…，RsnThe monitoring system is a main transmission link which is connected in parallel and is responsible for bidirectional information transmission between a monitoring area gateway and a monitoring center gateway. The system is formed by connecting n components in parallel, namely the system fails only when all the n components fail. Let the i-th component have a lifetime of XiWith a reliability of Ri(t), i ═ 1,2,. and n1,X2,...,XnIndependent of each other, the reliability of the systemThe method comprises the following steps:
when in use
Then
The Mean Time Between Failure (MTBF) of the system is
When n is 2 and Ri(t)＝e-λtWhen the parallel dual redundancy is used, the formula (24) and the formula (25) are substituted
When n is 3 and Ri(t)＝e-λt3-parallel redundancy, then
4.2) carrying out quantitative analysis on the reliability of the voting redundancy system taking k out of n to obtain the reliability and the average fault interval time.
Fig. 10 shows a reliability block diagram of the voting redundancy system. The voting redundancy system consists of n parts, and when k or more than k parts in the n parts work normally, the system works normally (1)<k<n). I.e., when the failed component is greater than or equal to n-k +1, the system fails. Suppose X1,X2,...,XnIs the lifetime of the n parts, which are independent of each other and reliable per partDegree is all R0(t)。
If all the components start to work at the same time at the initial moment, the reliability of the system is
When R is0(t)＝e-λtWhen it is, then there are
When n is 3 and k is 2, the formula (29) is substituted into the voting system
Examples
In this embodiment, the reliability of four different redundant systems is compared, which is: (1)1 unit of system; (2) a parallel system consisting of two units; (3) a parallel system consisting of three units; (4) the "2 out of 3" system.
As shown in fig. 11 and 12, the reliability of different redundant systems and the mean time between failures are plotted against the failure rate λ.
As can be seen from fig. 11, the single system reliability is lower in the case of a lower failure rate, but increases as the failure rate increases, followed by a 3-parallel redundant system, a 3-2 voting redundant system, and finally a 2-parallel redundant system. As can be seen in FIG. 12, the mean time between failures MTBF for the 3-parallel redundant system is highest, followed by the 2-parallel redundant system, the single system, and finally the 3-2 voting redundant system. Therefore, the influence of factors such as external weather and interference on reliability is fully considered for the remote transmission backbone, and when the remote transmission backbone is selected, a 3-parallel redundancy mode is selected as much as possible, so that the mean time fault interval can be prolonged, and the reliability of the transmission part of the backbone of the Internet of things remote monitoring system can be improved.
The above embodiments are only used for illustrating the present invention, and the structure, connection mode, manufacturing process, etc. of the components may be changed, and all equivalent changes and modifications performed on the basis of the technical solution of the present invention should not be excluded from the protection scope of the present invention.
Claims (4)
1. The three-dimensional monitoring topology system of the Internet of things is characterized in that: the system comprises a factory monitoring area node, factory surrounding monitoring area nodes, a monitoring party gateway, a receiving party gateway and a monitoring server;
the plant area monitoring area node is arranged in a plant area range to be monitored, and is used for monitoring the haze condition in the plant area range to be monitored and sending the haze condition to the monitoring side gateway;
the monitoring area nodes around the plant area are arranged at the periphery of the plant area to be monitored and are used for monitoring the haze condition around the plant area to be monitored and sending the haze condition to the monitoring side gateway;
the monitoring side gateway is arranged in the range of a factory area to be monitored and used for sending monitoring data to the receiving side gateway through a remote GPRS/3G technology, a remote Internet technology or a remote Beidou/satellite technology and receiving feedback information of the receiving side gateway;
the receiving party gateway uploads the received monitoring data to the monitoring server for a supervisor to monitor and receive alarm in real time through the Internet or a mobile terminal, or performs related configuration and management on a monitoring network, issues task actions and updates monitoring frequency;
the plant area monitoring area node deployment adopts a single Sink multilevel cluster structure, and comprises a plurality of basic monitoring bodies which are sequentially arranged from inside to outside, wherein the innermost basic monitoring body is deployed by taking the center of gravity of a plant area pollution source to be monitored as the center of a circle, and the recombination of the basic monitoring bodies is carried out according to the radius of a monitoring area and is sequentially deployed until the whole plant area monitoring area is covered; the monitoring area nodes around the plant area take a rectangle as a basic unit and are deployed by adopting an isosceles triangle to form a three-dimensional monitoring network;
the basic monitoring body consists of a data monitoring forwarding node and six data monitoring nodes arranged around the data monitoring forwarding node, the distances between the data monitoring nodes and the data monitoring forwarding node are equal, and all the nodes form a regular hexagon monitoring body together;
the monitoring area nodes around the plant area comprise strip-shaped rectangular area monitoring bodies arranged around the plant area to be monitored, all sensor nodes in the rectangular area monitoring bodies are placed on two long sides of a strip-shaped rectangular area in a staggered mode, and the centers of every two adjacent three nodes form an isosceles triangle.
2. The three-dimensional monitoring topology system of the internet of things according to claim 1, wherein: a coordinator node is configured in the innermost basic monitoring body and serves as a Sink node of the whole plant area monitoring area, and the coordinator node is responsible for communication with the monitoring party gateway and is called a primary cluster head; each node with a routing function in the basic monitoring bodies of the second layer nearest to the coordinator node is used as a secondary cluster head; and the nodes with the routing function in the basic monitoring bodies of other layers from inside to outside are sequentially used as three-level cluster heads, four-level cluster heads to N-level cluster head nodes.
3. The reliability quantitative analysis method of the three-dimensional monitoring topological system of the Internet of things according to any one of claims 1 to 2, characterized by comprising the following steps:
1) deploying plant area monitoring area nodes in a plant area range to be monitored, and determining related parameters of a plant area monitoring area node topological structure;
in the step 1), the method for deploying the plant area monitoring area nodes in the plant area range to be monitored and determining the relevant parameters of the topological structure of the plant area monitoring area nodes comprises the following steps:
1.1) determining the relation between the distance between adjacent cluster heads and the sampling radius of a regular hexagon basic monitoring body in the adopted single Sink multilevel cluster structure:
in the formula, d is the sampling radius of the regular hexagon basic monitoring body;
1.2) determining the relation between the sampling radius of the regular hexagon basic monitoring body and the sensing radius of the sensor node according to the relation between the obtained distance between the adjacent cluster heads and the sampling radius of the regular hexagon basic monitoring body:
in the formula, RsThe sensing radius of the sensor node;
1.3) calculating the relation between the total layer number N of the plant area monitoring area node topological structure, the sensing radius of the sensor and the ideal monitoring area according to the relation between the sampling radius of the regular hexagon basic monitoring body and the sensing radius of the sensor node:
in the formula, S is the area of an ideal monitoring area;
1.4) calculating to obtain the total number N of layers of the topological structure in the monitoring area and the total number N of cluster head nodes in the monitoring area according to the relationship between the total number N of layers of the topological structure in the monitoring area and the sensing radius of the sensor and the area of the ideal monitoring areakeyThe relationship of (1):
Nkey＝3N(N-1)+1；
2) deploying monitoring area nodes around a factory area to be monitored, and determining related parameters of a topological structure of the monitoring area nodes around the factory area;
3) carrying out quantitative analysis on the reliability of the multilevel cluster structure of the plant monitoring area nodes in the range of the plant to be monitored to obtain the reliability of the multilevel cluster structure;
4) carrying out quantitative analysis on the reliability of remote transmission backbones with different redundancy structures;
in the step 4), the method for quantitatively analyzing the reliability of the remote transmission backbone with different redundancy structures includes the following steps:
4.1) carrying out quantitative analysis on the reliability of the system with the parallel redundancy to obtain the reliability and the average fault interval time;
the reliability of the system is:
where n is the number of components of the parallel redundant system, Ri(t), i ═ 1, 2.., n is the reliability of each component;
when in use
Then
The mean time between failure of the system is:
when n is 2 and Ri(t)＝e-λtWhen dual redundancy is connected in parallel, then
When n is 3 and Ri(t)＝e-λt3-parallel redundancy, then
4.2) carrying out quantitative analysis on the reliability of the voting redundancy system taking k from n to obtain the reliability and the average fault interval time of the voting redundancy system;
if all the components start to work at the same time at the initial moment, the reliability of the system is
In the formula, X1,X2,...,XnIs the lifetime X of n components in the systemi；
When R is0(t)＝e-λtWhen it is, then there are
In the formula, λ is a failure rate.
4. The reliability quantitative analysis method of the three-dimensional monitoring topological system of the internet of things according to claim 3, characterized in that: in the step 2), the method for deploying the nodes of the monitoring area around the factory to be monitored and determining the relevant parameters of the topological structure of the nodes of the monitoring area around the factory comprises the following steps:
2.1) calculating the relation between the adjacent distance of the rectangular area and the sensing radius of the sensor according to the width of the rectangular area and the sensing radius of the sensor node:
wherein W is the width of the rectangular region, RsIs the sense of a sensor nodeKnowing the radius, d is the adjacent distance of the strip-shaped rectangular area;
2.2) calculating the total node number N required by the rectangular area with the length of L according to the relationship between the adjacent distance of the rectangular area with the strip shape and the sensing radius of the sensorexRelationship to the sensing radius of the sensor:
in the formula, L is the length of a long strip-shaped rectangular area;
2.3) calculating to obtain the relation between the adjacent distance meeting the 1-fold coverage condition and the sensing radius of the sensor node according to the relation between the coverage density of the strip rectangular area and the total node number:
d＝1.5Rs。
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