CN106792757B - An event detection-oriented sensor network deployment optimization method and device - Google Patents

Abstract

The invention discloses an event detection-oriented sensor network deployment optimization method and device. The types of wireless sensor nodes required by a first deployment scheme are determined according to the events to be monitored, and the number of each type of wireless sensor nodes is set as a theoretical value. Maximum value, calculate the relative deployment cost of each type of wireless sensor node, delete a wireless sensor node from the type of wireless sensor node with the largest relative deployment cost, obtain a second deployment scheme, and perform the above operations in a loop, which can be in turn Get new deployment scenarios. Every time a new deployment scheme is obtained, the monitoring accuracy of the deployment scheme needs to be judged. When the monitoring accuracy of a deployment scheme is less than or equal to the preset threshold, the above operations are stopped cyclically. According to the deployment scheme, a optimal deployment solution. The above technical solution effectively reduces deployment costs on the premise that the monitoring accuracy requirements of the events to be monitored are met.

Description

An event detection-oriented sensor network deployment optimization method and device

technical field

The present invention relates to the technical field of wireless sensor networks, in particular to an event detection-oriented sensor network deployment optimization method and device.

Background technique

Accidents such as public safety incidents and natural disasters occur frequently all over the world, and the use of wireless sensor networks to monitor these incidents has been widely used. By deploying a large number of wireless sensor nodes in the monitoring area, the monitoring of the monitoring area can be realized, which can effectively prevent accidents or deal with them in time, thereby reducing losses caused by accidents.

For an event, in order to make the monitoring result of the event more in line with the actual situation, it is often necessary to consider the multi-faceted characteristics of the event, and this type of event is usually called a compound event. For example, when monitoring a fire, it is necessary to consider the temperature, brightness, smoke concentration and other characteristics of the fire event. The monitoring results obtained by monitoring these characteristics will be more in line with the actual situation. At this time, the fire is a composite event. When monitoring a composite event, for each feature of the composite event, a corresponding type of wireless sensor node can be selected for monitoring. For example, for the temperature feature of a fire event, temperature sensor monitoring can be used, and for the brightness feature of a fire event, it can be monitored. Monitored by brightness sensor.

When monitoring complex events in a wide range, in order to ensure the accuracy of monitoring, that is, monitoring accuracy, it is often necessary to deploy a large number of wireless sensor nodes in the large-scale monitoring area. The price and performance of each type of wireless sensor nodes such as The monitoring accuracy is different. If the number of wireless sensor nodes of each type can be reasonably determined on the premise of meeting the requirements for the monitoring accuracy of composite events, the corresponding deployment cost will be lower.

It can be seen that how to reduce the deployment cost on the premise of meeting the requirements for the monitoring accuracy of the composite event is an urgent problem to be solved by those skilled in the art.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide an event detection-oriented sensor network deployment optimization method and device. The deployment cost can be reduced on the premise of meeting the precision requirements for compound event monitoring.

In order to solve the above technical problems, the present invention provides an event detection-oriented sensor network deployment optimization method, including:

S10: Determine a first deployment scheme according to the event to be monitored, where the first deployment scheme includes each type of wireless sensor node and the number of each type of wireless sensor node;

S11: Calculate the relative deployment costs of the various types of wireless sensor nodes;

S12: Delete the one wireless sensor node with the largest relative deployment cost from the wireless sensor nodes included in the first deployment scheme to obtain a second deployment scheme;

S13: Determine whether the monitoring accuracy of the event to be monitored by the second deployment solution is greater than a preset threshold; if it is not greater than the preset threshold, execute S14, and if it is greater than the preset threshold, use the second deployment solution as the For the first deployment scheme, return to S11;

S14: Determine an optimal deployment scheme according to the second deployment scheme.

Optionally, in the S10:

Determine the type of the wireless sensor node according to the characteristics of the event to be monitored;

According to the formula

表示所述各个类型的无线传感器节点的监测精度贡献权重值为w_min时所需要无线传感器节点的类型数，r表示无线传感器节点感知半径，A表示监测区域的面积。The number of wireless sensor nodes of each type is calculated as n _max , where E represents the monitoring accuracy that the event to be monitored needs to meet, and w _min represents the contribution of each type of wireless sensor nodes to the monitoring accuracy of the common coverage area the smallest contribution weight value,

Indicates the number of types of wireless sensor nodes required when the monitoring accuracy contribution weight value of each type of wireless sensor node is w _min , r represents the sensing radius of the wireless sensor node, and A represents the area of the monitoring area.

Optionally, in the S11:

According to the formula

Calculate the relative deployment cost of each type of wireless sensor nodes, where V _i represents the relative deployment cost of the i-type wireless sensor node, c _i represents the node cost of the i-type wireless sensor node, E(n ₁ ,. ..n _i ..,n _k ) represents the monitoring accuracy corresponding to the deployment scheme D(n ₁ ,...n _i ..,n _k ) determined by k types of wireless sensor nodes, E(n ₁ , ...n _i -1,..,n _k ) represents the monitoring corresponding to the deployment scheme D(n ₁ ,...n _i -1,..,n _k ) determined by k types of wireless sensor nodes precision.

Optionally, in the S14:

If the monitoring accuracy of the event to be monitored by the second deployment solution is equal to a preset threshold, the second deployment solution is used as the optimal deployment solution.

Optionally, in the S14:

If the monitoring accuracy of the event to be monitored by the second deployment solution is less than a preset threshold, then sequentially adding a wireless sensor node of different types to the second deployment solution to obtain at least one deployment solution in sequence;

calculating the monitoring accuracy of each of the at least one deployment scheme for the event to be monitored;

Screening out deployment solutions with the monitoring accuracy greater than the preset threshold;

determining the wireless sensor nodes added by the deployment scheme compared to the second deployment scheme, and calculating the relative deployment cost of the wireless sensor nodes;

A wireless sensor node with the smallest relative deployment cost is selected, and the wireless sensor node is added to the second deployment scheme to obtain an optimal deployment scheme.

The present invention also provides an event detection-oriented sensor network deployment optimization device, comprising a first determination unit, a calculation unit, a deletion unit, a judgment unit and a second determination unit:

the first determining unit, configured to determine a first deployment scheme according to the to-be-monitored event, where the first deployment scheme includes each type of wireless sensor node and the number of each type of wireless sensor node;

the calculation unit, configured to calculate the relative deployment costs of the various types of wireless sensor nodes;

The deletion unit is configured to delete the one wireless sensor node with the largest relative deployment cost from the wireless sensor nodes included in the first deployment scheme to obtain a second deployment scheme;

The judging unit is configured to judge whether the monitoring accuracy of the event to be monitored by the second deployment solution is greater than a preset threshold; if not greater than the preset threshold, trigger the second determining unit, if greater than the preset threshold , then the second deployment scheme is used as the first deployment scheme to trigger the computing unit;

The second determining unit is configured to determine an optimal deployment scheme according to the second deployment scheme.

Optionally, the first determining unit is specifically used for:

Determine the type of the wireless sensor node according to the characteristics of the event to be monitored;

According to the formula

表示所述各个类型的无线传感器节点的监测精度贡献权重值为w_min时所需要无线传感器节点的类型数，r表示无线传感器节点感知半径，A表示监测区域的面积。The number of wireless sensor nodes of each type is calculated as n _max , where E represents the monitoring accuracy that the event to be monitored needs to meet, and w _min represents the contribution of each type of wireless sensor nodes to the monitoring accuracy of the common coverage area the smallest contribution weight value,

Indicates the number of types of wireless sensor nodes required when the monitoring accuracy contribution weight value of each type of wireless sensor node is w _min , r represents the sensing radius of the wireless sensor node, and A represents the area of the monitoring area.

Optionally, the computing unit is specifically used for:

According to the formula

Calculate the relative deployment cost of each type of wireless sensor nodes, where V _i represents the relative deployment cost of the i-type wireless sensor node, c _i represents the node cost of the i-type wireless sensor node, E(n ₁ ,. ..n _i ..,n _k ) represents the monitoring accuracy corresponding to the deployment scheme D(n ₁ ,...n _i ..,n _k ) determined by k types of wireless sensor nodes, E(n ₁ , ...n _i -1,..,n _k ) represents the monitoring corresponding to the deployment scheme D(n ₁ ,...n _i -1,..,n _k ) determined by k types of wireless sensor nodes precision.

Optionally, the second determining unit is specifically configured to use the second deployment solution as an optimal deployment solution if the monitoring accuracy of the event to be monitored by the second deployment solution is equal to a preset threshold.

Optionally, the second determining unit includes an adding subunit, a computing subunit, a screening subunit and a determining subunit:

If the monitoring accuracy of the event to be monitored by the second deployment solution is less than a preset threshold, the adding subunit is triggered, and the adding subunit is used to sequentially add different types of A wireless sensor node obtains at least one deployment scheme in turn;

the calculation subunit, configured to calculate the monitoring accuracy of each of the at least one deployment solution for the to-be-monitored event;

the screening subunit, configured to screen out deployment schemes with the monitoring accuracy greater than the preset threshold;

The determining subunit is configured to determine the wireless sensor nodes added by the deployment scheme compared with the second deployment scheme, and calculate the relative deployment cost of the wireless sensor nodes;

The determining subunit is further configured to select a wireless sensor node with the smallest relative deployment cost, and add the wireless sensor node to the second deployment scheme to obtain an optimal deployment scheme.

It can be seen from the above technical solutions that, for the deployment of wireless sensor nodes, the types of wireless sensor nodes required by the first deployment solution can be determined according to the events to be monitored, and the number of wireless sensor nodes of each type can be determined in the first deployment solution. Set to the theoretical maximum value, and calculate the relative deployment cost of each type of wireless sensor node. In order to reduce the deployment cost, a wireless sensor node can be deleted from the type of wireless sensor node with the highest relative deployment cost, thus obtaining For the second deployment scheme, the above operations are performed cyclically, and new deployment schemes can be obtained in sequence. In order to ensure that the deployment scheme meets the monitoring accuracy requirements, each time a new deployment scheme is obtained, the monitoring accuracy of the deployment scheme needs to be judged. When the monitoring accuracy of a deployment scheme is less than or equal to the preset threshold, the loop execution of the above is stopped. Operation, according to the deployment scheme, an optimal deployment scheme can be determined. The optimal deployment scheme is a deployment scheme with the lowest deployment cost determined on the premise of ensuring that the deployment scheme meets the monitoring accuracy requirements. It can be seen that the above technical solution can effectively reduce the deployment cost on the premise of meeting the monitoring accuracy requirements of the events to be monitored.

Description of drawings

In order to explain the embodiments of the present invention more clearly, the following will briefly introduce the accompanying drawings that need to be used in the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention, which are not relevant to ordinary skills in the art. As far as personnel are concerned, other drawings can also be obtained from these drawings on the premise of no creative work.

FIG. 1 is a flowchart of an event detection-oriented sensor network deployment optimization method provided by an embodiment of the present invention;

2 is a flowchart of a method for adding a wireless sensor node according to an embodiment of the present invention;

FIG. 3 is a device structure diagram of an event detection-oriented sensor network deployment optimization device according to an embodiment of the present invention.

Detailed ways

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. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present invention.

In order to make those skilled in the art better understand the solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

Next, an event detection-oriented sensor network deployment optimization method provided by an embodiment of the present invention is introduced in detail. 1 is a flowchart of an event detection-oriented sensor network deployment optimization method provided by an embodiment of the present invention, where the method includes:

S10: Determine a first deployment scheme according to the event to be monitored.

The event to be monitored may be an event that needs to be monitored, the event may be a single event, that is, only one feature needs to be considered, or the event may be a composite event, and multiple features of the event need to be considered when monitoring a composite event. The daily monitoring events are often events that need to consider multiple characteristics. For the convenience of subsequent introduction, the content introduced below takes the event to be monitored as a compound event as an example to introduce.

The first deployment scheme may be a scheme of wireless sensor node deployment determined when monitoring the event to be monitored, and the wireless sensor nodes may be randomly and uniformly deployed. For a deployment scheme, the types of wireless sensor nodes included in the deployment scheme and the number of each type of wireless sensor nodes need to be determined.

Wireless sensor nodes can be divided into various types according to different functions. According to the characteristics of the event to be monitored, the type of wireless sensor node required for monitoring can be determined. For example, if the event to be monitored is a fire, when monitoring a fire It needs to be considered that the characteristics can include brightness, temperature and smoke concentration. According to these three characteristics, it can be determined that there are three types of wireless sensor nodes, which can be brightness sensor, temperature sensor and smoke concentration sensor.

In the initially determined deployment scheme, the number of wireless sensor nodes of each type can be set to a theoretical maximum value. In the embodiment of the present invention, the method for determining the theoretical maximum value of each type of wireless sensor node is not limited, and the formula can be used:

表示所述各个类型的无线传感器节点的监测精度贡献权重值为w_min时所需要无线传感器节点的类型数，r表示无线传感器节点感知半径，A表示监测区域的面积。Calculate the number of wireless sensor nodes of each type, where n _max represents the number of wireless sensor nodes, that is, the theoretical maximum value, E represents the monitoring accuracy that the event to be monitored needs to meet, and w _min represents the wireless sensor nodes of each type The contribution weight value that contributes the least to the monitoring accuracy of the common coverage area,

Indicates the number of types of wireless sensor nodes required when the monitoring accuracy contribution weight value of each type of wireless sensor node is w _min , r represents the sensing radius of the wireless sensor node, and A represents the area of the monitoring area.

Different types of wireless sensor nodes may affect the monitoring accuracy of events to be monitored differently. The greater the impact, the greater the contribution of this type of wireless sensor nodes to the monitoring accuracy. For each type of wireless sensor node, Corresponding contribution weight values can be set according to different contribution degrees to the monitoring accuracy, and w _min can be the smallest contribution weight value among the contribution weight values corresponding to each type of wireless sensor node.

For example, there are k types of wireless sensor nodes determined, and the contribution weights of each type of wireless sensor nodes to the monitoring accuracy of the events to be monitored are respectively w ₁ -w _k , and w ₁ +...+w _i +. ..w _k =1, if the minimum contribution weight value in w ₁ -w _k is w ₁ , then w _min =w ₁ .

S11: Calculate the relative deployment costs of the respective types of wireless sensor nodes.

Various types of wireless sensor nodes and the number of each type of wireless sensor nodes can be determined through S10. Since the number of wireless sensor nodes of each type is set to a theoretical maximum value in the first deployment solution above, the number of wireless sensor nodes The more, the corresponding deployment cost is relatively high. Therefore, on the premise of meeting the monitoring accuracy requirements, the deployment cost can be reduced by deleting wireless sensor nodes.

Considering that the price and performance of each type of wireless sensor node, such as monitoring accuracy, are different, each type of wireless sensor node has a different degree of influence on the deployment cost.

Taking a type of wireless sensor node as an example, the relative deployment cost can be used to represent the impact of this type of wireless sensor node on the deployment cost compared to other types of wireless sensor nodes. Nodes have a greater impact on deployment costs than other types of wireless sensor nodes.

The embodiment of the present invention does not limit the calculation method of the relative deployment cost of each type of wireless sensor node, and a feasible calculation method may be to use the formula:

Calculate the relative deployment cost of each type of wireless sensor nodes, where V _i represents the relative deployment cost of the i-type wireless sensor node, c _i represents the node cost of the i-type wireless sensor node, E(n ₁ ,. ..n _i ..,n _k ) represents the monitoring accuracy corresponding to the deployment scheme D(n ₁ ,...n _i ..,n _k ) determined by k types of wireless sensor nodes, E(n ₁ , ...n _i -1,..,n _k ) represents the monitoring corresponding to the deployment scheme D(n ₁ ,...n _i -1,..,n _k ) determined by k types of wireless sensor nodes precision.

It should be noted that, for the above k types of wireless sensor nodes, the value of k can be determined according to the type of wireless sensor nodes determined in S10. For example, if there are 10 types of wireless sensor nodes determined, then the value of k is The value is 10.

D(n ₁ ,...n _i ..,n _k ) represents a deployment scheme consisting of k types of wireless sensor nodes, and the number of each type of wireless sensor nodes is n ₁ -n _k in turn; for wireless sensor nodes In terms of the number of nodes, D(n ₁ ,...n _i -1,..,n _k ) differs from D(n ₁ ,...n _i ..,n _k ) in that for i The number of types of wireless sensor nodes has changed from n _i to n _i -1, that is, the wireless sensor nodes of type i in the deployment scheme of D(n ₁ ,...n _i -1,...,n _k ). The number of sensor nodes is reduced by 1 compared to the number of wireless sensor nodes of type i in the deployment scheme of D(n ₁ ,...n _i ..,n _k ).

c _i represents the node cost of the wireless sensor node of type i, and _ci can be a fixed value, which can be determined according to the price of the wireless sensor node, which is not limited here. The node cost of different types of wireless sensor nodes can be the same or different. In order to distinguish different types of wireless sensor nodes, different node costs are set for different types of wireless sensor nodes.

S12: Delete the one wireless sensor node with the largest relative deployment cost from the wireless sensor nodes included in the first deployment solution to obtain a second deployment solution.

According to the relative deployment cost of each type of wireless sensor nodes that can be calculated in S11, the number of each type of wireless sensor nodes can be one or more. When the relative deployment cost of a certain type of wireless sensor nodes is large, When using this type of wireless sensor node for monitoring, the deployment cost is relatively high. Therefore, in this embodiment of the present invention, in order to effectively reduce the deployment cost, one wireless sensor node may be deleted from the wireless sensor node of this type with the highest relative deployment cost.

For example, in the first deployment scheme, there are three types of wireless sensor nodes, namely type a, type b, and type c, the relative deployment cost of type a is 10, the relative deployment cost of type b is 15, and the relative deployment cost of type c is 15. The deployment cost is 12. It can be seen that the relative deployment cost of type b is the largest, so one wireless sensor node can be deleted from the wireless sensor nodes belonging to type b.

In order to facilitate the distinction from the first deployment scheme, the deployment scheme obtained after deleting one wireless sensor node may be referred to as the second deployment scheme. In terms of the number of wireless sensor nodes included in the deployment solution, compared with the first deployment solution, the second deployment solution reduces one wireless sensor node. Therefore, compared with the first deployment solution, the deployment cost of the second deployment solution Reduced.

S13: Determine whether the monitoring accuracy of the event to be monitored by the second deployment solution is greater than a preset threshold; if it is not greater than the preset threshold, execute S14, and if it is greater than the preset threshold, use the second deployment solution as the For the first deployment solution, return to S11.

In the embodiment of the present invention, the deployment scheme needs to be optimized on the premise of ensuring the monitoring accuracy requirements, so as to reduce the deployment cost. Therefore, in order to ensure that the second deployment solution can meet the monitoring accuracy requirements, it is necessary to judge the monitoring accuracy of the second deployment solution when monitoring the event to be monitored, that is, to determine whether the monitoring accuracy of the event to be monitored in the second deployment solution can meet the monitoring accuracy. Require. For the convenience of subsequent introduction, the monitoring accuracy of the events to be monitored by the deployment scheme may be referred to as the monitoring accuracy of the deployment scheme.

For monitoring accuracy requirements, a preset threshold can be set, and the preset threshold can be adjusted according to the level of monitoring accuracy requirements. For example, for events that require high monitoring accuracy, the preset threshold can be set to a higher value. For events that require less precision, the preset threshold can be set to a lower value.

In this embodiment of the present invention, the method for calculating the monitoring accuracy of the to-be-monitored event for the second deployment solution is not limited. For example, in one monitoring, the monitoring of different types of wireless sensor nodes in the common coverage area The contribution weight values of the accuracy are added to obtain the monitoring accuracy of the second deployment scheme. It should be noted that when the event to be monitored is monitored once by using the second deployment solution, each wireless sensor node included in the second deployment solution can perform monitoring at the same time.

When the monitoring accuracy of the event to be monitored in the second deployment solution is greater than the preset threshold, it indicates that the second deployment solution can meet the monitoring accuracy requirements. In this case, in order to further reduce the cost of deployment, the second deployment solution can be used as the first deployment solution The operations of S11-S13 are executed cyclically until the monitoring accuracy of the event to be monitored in the finally obtained deployment solution is less than or equal to the preset threshold, then the cyclic execution of the above operations is stopped. It should be noted that, when the operations of S11-S13 are performed in each cycle, there are corresponding first deployment solutions and second deployment solutions. The first deployment scheme in each cyclic execution is different from the first deployment scheme in the previous cyclic execution, and the second deployment scheme obtained in each cyclic execution is different from the second deployment scheme obtained in the previous cyclic execution.

S14: Determine an optimal deployment scheme according to the second deployment scheme.

When the monitoring accuracy of the event to be monitored in the second deployment solution is equal to the preset threshold, it means that the second deployment solution can meet the monitoring accuracy requirements, and on the premise that the monitoring accuracy requirements are met, the deployment cost of the second deployment solution has been minimized , therefore, the second deployment scheme can be taken as the optimal deployment scheme.

Considering that the monitoring accuracy of the events to be monitored in the second deployment solution may be smaller than the preset threshold, if this happens, it means that the monitoring accuracy of the second deployment solution obtained at this time cannot meet the monitoring accuracy requirements. Considering that deleting a wireless sensor node, the monitoring accuracy of the obtained deployment scheme will be reduced. Similarly, if a wireless sensor node is added to the original deployment scheme, the monitoring accuracy of the obtained deployment scheme will be improved. Therefore, in the case where the monitoring accuracy of the event to be monitored by the second deployment solution is less than the preset threshold, the monitoring accuracy of the deployment solution can be improved by adding a wireless sensor node, so that it can meet the monitoring accuracy requirements.

Next, the operation of adding a wireless sensor node will be introduced. As shown in Figure 2, it is a feasible way to add a wireless sensor node. The specific operations are as follows:

S20: Add one wireless sensor node of different types in sequence to the second deployment solution, and obtain at least one deployment solution in sequence.

In a deployment scheme, different types of wireless sensor nodes have different degrees of influence on the monitoring accuracy of the deployment scheme. In order to select a suitable wireless sensor node, a certain type of wireless sensor node can be added to the second deployment scheme, thereby obtaining a new deployment scheme. How many types of wireless sensor nodes there are, correspondingly how many different deployment schemes can be obtained.

For example, according to the events to be monitored, three types of wireless sensor nodes are determined, namely type a, type b, and type c, then a wireless sensor node belonging to type a can be added to the second deployment scheme, thereby obtaining For a new deployment scheme, in the same way, a wireless sensor node belonging to type b can be added to the second deployment scheme to obtain a new deployment scheme, and a wireless sensor node belonging to type c can be added to the second deployment scheme. , so as to obtain a new deployment scheme, from which it can be seen that three different deployment schemes can be obtained.

S21: Calculate the monitoring accuracy of each of the at least one deployment solution for the to-be-monitored event.

S22: Screen out deployment solutions with the monitoring accuracy greater than the preset threshold.

In order to make the monitoring accuracy of the deployment scheme meet the monitoring accuracy requirement, a deployment scheme that satisfies the monitoring accuracy requirement, that is, a preset threshold, can be selected by calculating the monitoring accuracy of the to-be-monitored event of at least one deployment scheme. The method for calculating the monitoring accuracy is similar to the method for calculating the monitoring accuracy in the above S13, and details are not repeated here.

S23: Determine the wireless sensor nodes added by the deployment scheme compared to the second deployment scheme, and calculate the relative deployment cost of the wireless sensor nodes.

The calculation method of the relative deployment cost of the wireless sensor node is similar to the calculation method of the relative deployment cost in the above S11, and will not be repeated here.

S24: Select a wireless sensor node with the smallest relative deployment cost, and add the wireless sensor node to the second deployment scheme to obtain an optimal deployment scheme.

There may be one or more deployment schemes that are screened out. When there are multiple deployment schemes whose monitoring accuracy is greater than the preset threshold, the multiple deployment schemes can be further screened. Specifically, the screening can be performed according to the relative deployment cost of the wireless sensor nodes. The smaller the relative deployment cost of the wireless sensor node, the smaller the impact on the deployment cost of adding it to the second deployment scheme. Therefore, a wireless sensor node with the smallest relative deployment cost can be added to the second deployment scheme to obtain a new deployment scheme, or a wireless sensor with the lowest relative deployment cost can be added to the deployment scheme screened in S22. The node deployment scheme is a new deployment scheme, which can meet the monitoring accuracy requirements, and the new deployment scheme is the optimal deployment scheme.

It can be seen from the above technical solutions that, for the deployment of wireless sensor nodes, the types of wireless sensor nodes required by the first deployment solution can be determined according to the events to be monitored, and the number of wireless sensor nodes of each type can be determined in the first deployment solution. Set to the theoretical maximum value, and calculate the relative deployment cost of each type of wireless sensor node. In order to reduce the deployment cost, a wireless sensor node can be deleted from the type of wireless sensor node with the highest relative deployment cost, thus obtaining For the second deployment scheme, the above operations are performed cyclically, and new deployment schemes can be obtained in sequence. In order to ensure that the deployment scheme meets the monitoring accuracy requirements, each time a new deployment scheme is obtained, the monitoring accuracy of the deployment scheme needs to be judged. When the monitoring accuracy of a deployment scheme is less than or equal to the preset threshold, the loop execution of the above is stopped. Operation, according to the deployment scheme, an optimal deployment scheme can be determined. The optimal deployment scheme is a deployment scheme with the lowest deployment cost determined on the premise of ensuring that the deployment scheme meets the monitoring accuracy requirements. It can be seen that the above technical solution can effectively reduce the deployment cost on the premise of meeting the monitoring accuracy requirements of the events to be monitored.

3 is a device structure diagram of an event detection-oriented sensor network deployment optimization device according to an embodiment of the present invention, the device includes a first determination unit 31, a calculation unit 32, a deletion unit 33, a judgment unit 34, and a second Determining Unit 35:

The first determining unit 31 is configured to determine a first deployment scheme according to an event to be monitored, where the first deployment scheme includes various types of wireless sensor nodes and the number of the various types of wireless sensor nodes.

The calculating unit 32 is configured to calculate the relative deployment costs of the various types of wireless sensor nodes.

The deletion unit 33 is configured to delete the wireless sensor node with the largest relative deployment cost from the wireless sensor nodes included in the first deployment scheme to obtain a second deployment scheme.

The judging unit 34 is configured to judge whether the monitoring accuracy of the event to be monitored by the second deployment solution is greater than a preset threshold; if not greater than the preset threshold, trigger the second determining unit, and if greater than the preset threshold If the threshold is set, the second deployment scheme is used as the first deployment scheme, and the computing unit is triggered.

The second determining unit 35 is configured to determine an optimal deployment scheme according to the second deployment scheme.

Optionally, the first determining unit is specifically used for:

Determine the type of the wireless sensor node according to the characteristics of the event to be monitored;

According to the formula

表示所述各个类型的无线传感器节点的监测精度贡献权重值为w_min时所需要无线传感器节点的类型数，r表示无线传感器节点感知半径，A表示监测区域的面积。The number of wireless sensor nodes of each type is calculated as n _max , where E represents the monitoring accuracy that the event to be monitored needs to meet, and w _min represents the contribution of each type of wireless sensor nodes to the monitoring accuracy of the common coverage area the smallest contribution weight value,

Indicates the number of types of wireless sensor nodes required when the monitoring accuracy contribution weight value of each type of wireless sensor node is w _min , r represents the sensing radius of the wireless sensor node, and A represents the area of the monitoring area.

Optionally, the computing unit is specifically used for:

According to the formula

Calculate the relative deployment cost of each type of wireless sensor nodes, where V _i represents the relative deployment cost of the i-type wireless sensor node, c _i represents the node cost of the i-type wireless sensor node, E(n ₁ ,. ..n _i ..,n _k ) represents the monitoring accuracy corresponding to the deployment scheme D(n ₁ ,...n _i ..,n _k ) determined by k types of wireless sensor nodes, E(n ₁ , ...n _i -1,..,n _k ) represents the monitoring corresponding to the deployment scheme D(n ₁ ,...n _i -1,..,n _k ) determined by k types of wireless sensor nodes precision.

Optionally, the second determining unit is specifically configured to use the second deployment solution as an optimal deployment solution if the monitoring accuracy of the event to be monitored by the second deployment solution is equal to a preset threshold.

Optionally, the second determining unit includes an adding subunit, a computing subunit, a screening subunit and a determining subunit:

If the monitoring accuracy of the event to be monitored by the second deployment solution is less than a preset threshold, the adding subunit is triggered, and the adding subunit is used to sequentially add different types of A wireless sensor node obtains at least one deployment scheme in turn.

The calculation subunit is configured to calculate the monitoring accuracy of each of the at least one deployment solution for the to-be-monitored event.

The screening subunit is configured to screen out deployment solutions with the monitoring accuracy greater than the preset threshold.

The determining subunit is configured to determine the wireless sensor nodes added by the deployment scheme compared with the second deployment scheme, and calculate the relative deployment cost of the wireless sensor nodes.

The determining subunit is further configured to select a wireless sensor node with the smallest relative deployment cost, and add the wireless sensor node to the second deployment scheme to obtain an optimal deployment scheme.

For the description of the features in the embodiment corresponding to FIG. 3 , reference may be made to the related description of the embodiment corresponding to FIG. 1 and FIG. 2 , which will not be repeated here.

It can be seen from the above technical solutions that, for the deployment of wireless sensor nodes, the types of wireless sensor nodes required by the first deployment solution can be determined according to the events to be monitored, and the number of wireless sensor nodes of each type can be determined in the first deployment solution. Set to the theoretical maximum value, and calculate the relative deployment cost of each type of wireless sensor node. In order to reduce the deployment cost, a wireless sensor node can be deleted from the type of wireless sensor node with the highest relative deployment cost, thus obtaining For the second deployment scheme, the above operations are performed cyclically, and new deployment schemes can be obtained in sequence. In order to ensure that the deployment scheme meets the monitoring accuracy requirements, each time a new deployment scheme is obtained, the monitoring accuracy of the deployment scheme needs to be judged. When the monitoring accuracy of a deployment scheme is less than or equal to the preset threshold, the loop execution of the above is stopped. Operation, according to the deployment scheme, an optimal deployment scheme can be determined. The optimal deployment scheme is a deployment scheme with the lowest deployment cost determined on the premise of ensuring that the deployment scheme meets the monitoring accuracy requirements. It can be seen that the above technical solution can effectively reduce the deployment cost on the premise of meeting the monitoring accuracy requirements of the events to be monitored.

The event detection-oriented sensor network deployment optimization method and device provided by the present invention are described above in detail. The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the various embodiments can be referred to each other. As for the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant part can be referred to the description of the method. It should be pointed out that for those skilled in the art, without departing from the principle of the present invention, several improvements and modifications can also be made to the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

Professionals may further realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two, in order to clearly illustrate the possibilities of hardware and software. Interchangeability, the above description has generally described the components and steps of each example in terms of function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of the present invention.

The steps of a method or algorithm described in conjunction with the embodiments disclosed herein may be directly implemented in hardware, a software module executed by a processor, or a combination of the two. A software module can be placed in random access memory (RAM), internal memory, read only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other in the technical field. in any other known form of storage medium.

Claims (6)

1. An event detection-oriented sensor network deployment optimization method is characterized by comprising the following steps:

s10: determining a first deployment scheme according to an event to be monitored, wherein the first deployment scheme comprises various types of wireless sensor nodes and the number of the wireless sensor nodes of the various types;

s11: calculating the relative deployment cost of each type of wireless sensor node;

s12: deleting the wireless sensor node with the largest relative deployment cost from the wireless sensor nodes included in the first deployment scheme to obtain a second deployment scheme;

s13: judging whether the monitoring precision of the second deployment scheme on the event to be monitored is greater than a preset threshold value; if the first deployment scheme is not larger than the preset threshold, executing S14, if the first deployment scheme is larger than the preset threshold, taking the second deployment scheme as the first deployment scheme, and returning to S11;

s14: determining an optimal deployment scheme according to the second deployment scheme;

in the S14:

if the monitoring precision of the second deployment scheme on the event to be monitored is smaller than a preset threshold value, sequentially adding one wireless sensor node of different types in the second deployment scheme to sequentially obtain at least one deployment scheme;

calculating the monitoring precision of each deployment scheme to the event to be monitored;

screening out the deployment scheme with the monitoring precision larger than the preset threshold;

determining the wireless sensor nodes added by the deployment scheme compared with the second deployment scheme, and calculating the relative deployment cost of the wireless sensor nodes;

and selecting the wireless sensor node with the minimum relative deployment cost, and adding the wireless sensor node to the second deployment scheme to obtain an optimal deployment scheme.

2. The method according to claim 1, wherein in the S10:

determining the type of the wireless sensor node according to the characteristics of the event to be monitored;

according to the formula

Calculating the number n of the wireless sensor nodes of each type_maxWherein E represents the monitoring precision required to be met by the event to be monitored, and w_minRepresenting a contribution weight value of the respective type of wireless sensor node that contributes least to the common coverage area monitoring accuracy,

the monitoring precision contribution weighted value of each type of wireless sensor node is w_minWireless sensor required by timeThe type number of the nodes, r represents the sensing radius of the wireless sensor node, and A represents the area of the monitoring area.

3. The method according to claim 1, wherein in the S11:

according to the formula

Calculating relative deployment costs of the wireless sensor nodes of each type, wherein V_iRepresenting the relative deployment cost of i-type wireless sensor nodes, c_iRepresenting the node cost, E (n), of a wireless sensor node of type i₁,...n_i..,n_k) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes₁,...n_i..,n_k) Corresponding monitoring accuracy, E (n)₁,...n_i-1,..,n_k) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes₁,...n_i-1,..,n_k) Corresponding monitoring accuracy.

4. The sensor network deployment optimization device for event detection is characterized by comprising a first determining unit, a calculating unit, a deleting unit, a judging unit and a second determining unit:

the first determining unit is configured to determine a first deployment scenario according to an event to be monitored, where the first deployment scenario includes each type of a wireless sensor node and the number of the wireless sensor nodes of each type;

the calculating unit is used for calculating the relative deployment cost of each type of wireless sensor node;

the deleting unit is configured to delete the wireless sensor node with the largest relative deployment cost from the wireless sensor nodes included in the first deployment scheme, so as to obtain a second deployment scheme;

the judging unit is used for judging whether the monitoring precision of the second deployment scheme on the event to be monitored is greater than a preset threshold value; if the first deployment scheme is not larger than the preset threshold, triggering the second determining unit, and if the first deployment scheme is larger than the preset threshold, taking the second deployment scheme as the first deployment scheme, and triggering the calculating unit;

the second determining unit is configured to determine an optimal deployment scheme according to the second deployment scheme;

the second determining unit comprises an adding subunit, a calculating subunit, a screening subunit and a determining subunit:

if the monitoring precision of the second deployment scheme on the event to be monitored is smaller than a preset threshold value, triggering the adding subunit, wherein the adding subunit is used for sequentially adding different types of wireless sensor nodes in the second deployment scheme to sequentially obtain at least one deployment scheme;

the calculating subunit is configured to calculate a monitoring accuracy of each of the at least one deployment scenario on the event to be monitored;

the screening subunit is used for screening out the deployment scheme of which the monitoring precision is greater than the preset threshold value;

the determining subunit is configured to determine the wireless sensor node added by the deployment scheme compared with the second deployment scheme, and calculate a relative deployment cost of the wireless sensor node;

and the determining subunit is further configured to select the wireless sensor node with the smallest relative deployment cost, and add the wireless sensor node to the second deployment scheme to obtain an optimal deployment scheme.

5. The apparatus according to claim 4, wherein the first determining unit is specifically configured to:

determining the type of the wireless sensor node according to the characteristics of the event to be monitored;

according to the formula

Calculating the number n of the wireless sensor nodes of each type_maxWherein E represents the monitoring precision required to be met by the event to be monitored, and w_minRepresenting a contribution weight value of the respective type of wireless sensor node that contributes least to the common coverage area monitoring accuracy,

the monitoring precision contribution weighted value of each type of wireless sensor node is w_minThe type number of the needed wireless sensor nodes, r represents the sensing radius of the wireless sensor nodes, and A represents the area of the monitoring area.

6. The apparatus according to claim 4, wherein the computing unit is specifically configured to:

according to the formula

Calculating relative deployment costs of the wireless sensor nodes of each type, wherein V_iRepresenting the relative deployment cost of i-type wireless sensor nodes, c_iRepresenting the node cost, E (n), of a wireless sensor node of type i₁,...n_i..,n_k) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes₁,...n_i..,n_k) Corresponding monitoring accuracy, E (n)₁,...n_i-1,..,n_k) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes₁,...n_i-1,..,n_k) Corresponding monitoring accuracy.

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