CN106792757B - Sensor network deployment optimization method and device for event detection - Google Patents
Sensor network deployment optimization method and device for event detection Download PDFInfo
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Abstract
The invention discloses a sensor network deployment optimization method and device for event detection, wherein the types of wireless sensor nodes required by a first deployment scheme are determined according to an event to be monitored, the number of the wireless sensor nodes of each type is set as a theoretical maximum value, the relative deployment cost of each type of wireless sensor node is calculated, one wireless sensor node is deleted from the wireless sensor node of the type with the largest relative deployment cost to obtain a second deployment scheme, and the operation is executed in a circulating manner to sequentially obtain a new deployment scheme. And when a new deployment scheme is obtained, judging the monitoring precision of the deployment scheme, stopping circularly executing the operation until the monitoring precision of one deployment scheme is smaller than or equal to a preset threshold value, and determining an optimal deployment scheme according to the deployment scheme. According to the technical scheme, the deployment cost is effectively reduced on the premise that the requirement on the monitoring precision of the event to be monitored is met.
Description
Technical Field
The invention relates to the technical field of wireless sensor networks, in particular to a sensor network deployment optimization method and device for event detection.
Background
Accidents such as public safety incidents and natural disasters frequently occur around the world, and monitoring of such incidents by using a wireless sensor network is widely applied. The monitoring of the condition of the monitoring area is realized by deploying a large number of wireless sensor nodes in the monitoring area, so that accidents can be effectively prevented from happening or the accidents can be processed in time, and the loss caused by the accidents is reduced.
For an event, in order to make the monitoring result of the event more consistent with the actual situation, the characteristics of the event in various aspects are often considered, and the event is generally called a composite event. For example, when a fire disaster is monitored, characteristics of the fire disaster event, such as temperature, brightness, smoke concentration and the like, need to be considered, and a monitoring result obtained by monitoring the characteristics can better accord with an actual situation, and the fire disaster is a composite event at this time. When the composite event is monitored, for each characteristic of the composite event, a corresponding type of wireless sensor node can be selected for monitoring, for example, for the temperature characteristic of a fire event, a temperature sensor can be used for monitoring, and for the brightness characteristic of the fire event, a brightness sensor can be used for monitoring.
When monitoring a composite event in a large range, in order to ensure the monitoring accuracy, that is, the monitoring precision, a large number of wireless sensor nodes are often deployed in the monitoring area in the large range, the price and performance of each type of wireless sensor node, for example, the monitoring precision, are different, and if the number of each type of wireless sensor node can be reasonably determined on the premise of meeting the requirement on the monitoring precision of the composite event, the corresponding deployment cost is low.
Therefore, how to reduce the deployment cost on the premise of meeting the requirement on the monitoring precision of the composite event is a problem to be solved urgently by technical personnel in the field.
Disclosure of Invention
The invention aims to provide a sensor network deployment optimization method and device for event detection. The deployment cost can be reduced on the premise of meeting the requirement on the monitoring precision of the composite event.
In order to solve the technical problem, the invention provides an event detection-oriented sensor network deployment optimization method, which comprises 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: and determining an optimal deployment scheme according to the second deployment scheme.
Optionally, 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 typemaxWherein E represents the monitoring precision required to be met by the event to be monitored, and wminRepresenting 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 wminThe 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.
Optionally, in the S11:
according to the formula
Calculating relative deployment costs of the wireless sensor nodes of each type, wherein ViRepresenting the relative deployment cost of i-type wireless sensor nodes, ciRepresenting the node cost, E (n), of a wireless sensor node of type i1,...ni..,nk) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes1,...ni..,nk) Corresponding monitoring accuracy，E(n1,...ni-1,..,nk) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes1,...ni-1,..,nk) Corresponding monitoring accuracy.
Optionally, in the S14:
and if the monitoring precision of the second deployment scheme on the event to be monitored is equal to a preset threshold value, taking the second deployment scheme as an optimal deployment scheme.
Optionally, 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.
The invention also provides a sensor network deployment optimization device for event detection, which comprises 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;
and the second determining unit is used for determining an optimal deployment scheme according to the second deployment scheme.
Optionally, 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 typemaxWherein E represents the monitoring precision required to be met by the event to be monitored, and wminRepresenting 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 wminThe 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.
Optionally, the computing unit is specifically configured to:
according to the formula
Calculating relative deployment costs of the wireless sensor nodes of each type, wherein ViRepresenting the relative deployment cost of i-type wireless sensor nodes, ciRepresenting the node cost, E (n), of a wireless sensor node of type i1,...ni..,nk) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes1,...ni..,nk) Corresponding monitoring accuracy, E (n)1,...ni-1,..,nk) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes1,...ni-1,..,nk) Corresponding monitoring accuracy.
Optionally, the second determining unit is specifically configured to take the second deployment scenario as an optimal deployment scenario if the monitoring accuracy of the second deployment scenario on the event to be monitored is equal to a preset threshold.
Optionally, the second determining unit includes 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.
According to the technical scheme, for the deployment of the wireless sensor nodes, the types of the wireless sensor nodes required by the first deployment scheme can be determined according to the events to be monitored, the number of the wireless sensor nodes of each type is set to be the theoretical maximum value in the first deployment scheme, the relative deployment cost of each type of wireless sensor node is calculated, in order to reduce the deployment cost, one wireless sensor node can be deleted from the wireless sensor node of the type with the maximum relative deployment cost, so that the second deployment scheme is obtained, the operation is executed in a circulating mode, and the new deployment schemes can be obtained in sequence. In order to ensure that the deployment scheme meets the requirement of monitoring precision, the monitoring precision of the deployment scheme needs to be judged every time a new deployment scheme is obtained, and the operation is stopped to be executed circularly until the monitoring precision of one deployment scheme is smaller than or equal to a preset threshold value, so that an optimal deployment scheme can be determined according to the deployment scheme. The optimal deployment scheme is the deployment scheme with the lowest deployment cost determined on the premise that the deployment scheme meets the monitoring precision requirement. Therefore, the technical scheme can effectively reduce the deployment cost on the premise of meeting the monitoring precision requirement of the event to be monitored.
Drawings
In order to illustrate the embodiments of the present invention more clearly, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained by those skilled in the art without inventive effort.
Fig. 1 is a flowchart of an event detection-oriented sensor network deployment optimization method according to an embodiment of the present invention;
fig. 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 Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present invention without any creative work belong to the protection scope of the present invention.
In order that those skilled in the art will better understand the disclosure, the invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Next, a method for optimizing sensor network deployment for event detection according to an embodiment of the present invention is described in detail. Fig. 1 is a flowchart of an event detection-oriented sensor network deployment optimization method according to an embodiment of the present invention, where the method includes:
s10: according to the event to be monitored, a first deployment scenario is determined.
The event to be monitored may be an event to be monitored, the event may be a single event, that is, an event only requiring consideration of one characteristic, or may be a composite event, and multiple characteristics of the event need to be considered when monitoring the composite event. The events monitored daily are events requiring consideration of a plurality of characteristics, and for convenience of description, the following description will be given by taking the event to be monitored as a composite event as an example.
The first deployment scheme may be a scheme of deployment of the wireless sensor nodes determined when the event to be monitored is monitored, and the wireless sensor nodes may adopt a random uniform deployment mode. For a deployment scenario, the types of wireless sensor nodes included in the deployment scenario and the number of wireless sensor nodes of each type need to be determined.
The wireless sensor nodes can be divided into multiple types according to different functions, the type of the wireless sensor nodes required in monitoring can be determined according to the characteristics of the event to be monitored, for example, the event to be monitored is a fire disaster, the characteristics can be considered to include brightness, temperature and smoke concentration when the fire disaster is monitored, and 3 types of the wireless sensor nodes can be determined according to the 3 characteristics, specifically, the types can be a brightness sensor, a temperature sensor and a smoke concentration sensor.
In the initially determined deployment scenario, the number of each type of wireless sensor node may be set to a theoretical maximum. In the embodiment of the present invention, the determination method of the theoretical maximum value of each type of wireless sensor node is not limited, and may be a method using a formula:
calculating the number of each type of wireless sensor node, wherein nmaxThe number of the nodes of the wireless sensor is shown, namely the theoretical maximum value, E shows the monitoring precision required by the event to be monitored, and wminRepresenting 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 wminThe 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.
The wireless sensor nodes of different types may have different degrees of influence on the monitoring accuracy of the event to be monitored, the greater the degree of influence, the greater the contribution of the wireless sensor nodes of the type to the monitoring accuracy, and for each type of wireless sensor node, according to the different degrees of contribution to the monitoring accuracy, a corresponding contribution weight value, w, may be setminMay be the smallest one of the contribution weight values corresponding to each type of wireless sensor node.
For example, there are k types of the determined wireless sensor nodes, and each type of wireless sensor node contributes a weight value of w to the monitoring accuracy of the event to be monitored1-wkAnd w is1+...+wi+...wkIf w is equal to 11-wkThe minimum contribution weight value of w1Then w ismin＝w1。
S11: and calculating the relative deployment cost of each type of wireless sensor node.
Each type of the wireless sensor nodes and the number of the wireless sensor nodes of each type can be determined through S10, and since the number of the wireless sensor nodes of each type is set to be a theoretical maximum value in the first deployment scheme, the greater the number of the wireless sensor nodes, the higher the corresponding deployment cost is. Therefore, on the premise of meeting the monitoring precision requirement, the deployment cost can be reduced by deleting the wireless sensor nodes.
Considering that the price, performance, such as monitoring accuracy, and the like of each type of wireless sensor node are different, the degree of influence of each type of wireless sensor node on the deployment cost is also different.
Taking a type of wireless sensor node as an example, the relative deployment cost may be used to represent the degree of influence of the type of wireless sensor node on the deployment cost compared with other types of wireless sensor nodes, and a larger relative deployment cost indicates that the type of wireless sensor node has a larger degree of influence on the deployment cost compared with 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 a calculation method using a formula:
calculating relative deployment costs of the wireless sensor nodes of each type, wherein ViRepresenting the relative deployment cost of i-type wireless sensor nodes, ciRepresenting the node cost, E (n), of a wireless sensor node of type i1,...ni..,nk) Representing by k typesDeployment scenario D (n) determined by wireless sensor node1,...ni..,nk) Corresponding monitoring accuracy, E (n)1,...ni-1,..,nk) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes1,...ni-1,..,nk) Corresponding monitoring accuracy.
It should be noted that, for the k types of wireless sensor nodes, the value of k may be determined according to the type of the wireless sensor node determined in S10, for example, if there are 10 determined types of the wireless sensor node, the value of k is 10.
D(n1,...ni..,nk) The number of the wireless sensor nodes is n1-nkThe deployment scenario of (1); for the number of wireless sensor nodes, D (n)1,...ni-1,..,nk) Compared with D (n)1,...ni..,nk) The difference is that the number of the wireless sensor nodes for the i type is changed from niIs changed into ni1, i.e. D (n)1,...ni-1,..,nk) The number of i type wireless sensor nodes in the deployment scheme is compared with D (n)1,...ni..,nk) The number of i-type wireless sensor nodes in the deployment scheme of (1) is reduced.
ciNode cost, c, of a wireless sensor node representing type iiMay be a fixed value, may be determined according to the price of the wireless sensor node, and is not limited herein. The node costs of different types of wireless sensor nodes may be the same or different. In order to distinguish different types of wireless sensor nodes, different node costs are set for the different types of wireless sensor nodes.
S12: and 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.
According to the relative deployment cost of each type of wireless sensor node which can be calculated by S11, there may be one or more wireless sensor nodes in each type, and when the relative deployment cost of a certain type of wireless sensor node is large, the deployment cost generated when monitoring is performed using the type of wireless sensor node is relatively high. Therefore, in the embodiment of the present invention, in order to effectively reduce the deployment cost, one wireless sensor node may be deleted from the type of wireless sensor node with the largest relative deployment cost.
For example, in the first deployment scheme, there are 3 types of wireless sensor nodes, which are respectively 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 12, and it is known that the relative deployment cost of type b is the largest, and therefore one wireless sensor node can be deleted from the wireless sensor nodes belonging to type b.
For the convenience of distinguishing from the first deployment scheme, the deployment scheme obtained after one wireless sensor node is deleted may be referred to as a second deployment scheme. The second deployment scenario reduces one wireless sensor node compared to the first deployment scenario in terms of the number of wireless sensor nodes comprised by the deployment scenario, and thus the deployment cost of the second deployment scenario is reduced compared to the first deployment scenario.
S13: judging whether the monitoring precision of the second deployment scheme on the event to be monitored is greater than a preset threshold value; and if the second deployment scheme is not larger than the preset threshold, executing S14, and if the second deployment scheme is larger than the preset threshold, taking the second deployment scheme as the first deployment scheme, and returning to S11.
In the embodiment of the invention, the deployment scheme needs to be optimized on the premise of ensuring the monitoring precision requirement, so that the deployment cost is reduced. Therefore, in order to ensure that the second deployment scheme can meet the requirement on monitoring accuracy, the monitoring accuracy of the second deployment scheme when the event to be monitored is monitored needs to be judged, that is, whether the monitoring accuracy of the event to be monitored by the second deployment scheme can meet the requirement on monitoring accuracy is judged. For convenience of subsequent introduction, the monitoring precision of the deployment scheme for the event to be monitored may be referred to as the monitoring precision of the deployment scheme.
The monitoring accuracy requirement can be adjusted by setting a preset threshold according to the monitoring accuracy requirement, for example, for an event with a higher monitoring accuracy requirement, the preset threshold can be set to a higher value, and for an event with a lower monitoring accuracy requirement, the preset threshold can be set to a lower value.
In the embodiment of the present invention, a calculation manner of the second deployment scenario for the monitoring accuracy of the event to be monitored is not limited, for example, in one-time monitoring, the contribution weight values of the monitoring accuracy of each different type of wireless sensor node in the common coverage area are added, so as to obtain the monitoring accuracy of the second deployment scenario. It should be noted that, when the second deployment scheme is used to perform primary monitoring on the event to be monitored, each wireless sensor node included in the second deployment scheme may perform monitoring simultaneously.
When the monitoring accuracy of the second deployment scheme on the event to be monitored is greater than the preset threshold, it is indicated that the second deployment scheme can meet the requirement of the monitoring accuracy, at this time, in order to further reduce the cost of deployment, the second deployment scheme may be used as the first deployment scheme to circularly execute the operations of S11-S13, until the finally obtained monitoring accuracy of the deployment scheme on the event to be monitored is less than or equal to the preset threshold, the circular execution of the operations is stopped. It should be noted that, each time the operations of S11-S13 are executed circularly, there are corresponding first deployment scenario and second deployment scenario. The first deployment scheme in each loop execution is different from the first deployment scheme in the last loop execution, and the second deployment scheme obtained in each loop execution is different from the second deployment scheme obtained in the last loop execution.
S14: and determining an optimal deployment scheme according to the second deployment scheme.
When the monitoring precision of the second deployment scheme on the event to be monitored is equal to the preset threshold, it is indicated that the second deployment scheme can meet the requirement of the monitoring precision, and the deployment cost of the second deployment scheme is already reduced to the minimum on the premise of meeting the requirement of the monitoring precision, so that the second deployment scheme can be used as the optimal deployment scheme.
Considering that the monitoring precision of the event to be monitored by the second deployment scheme may be smaller than the preset threshold, if the monitoring precision of the event to be monitored by the second deployment scheme is smaller than the preset threshold, it indicates that the monitoring precision of the second deployment scheme obtained at this time cannot meet the monitoring precision requirement. In consideration of the fact that the monitoring precision of the obtained deployment scheme is reduced by deleting one wireless sensor node, similarly, if one wireless sensor node is added to the original deployment scheme, the monitoring precision of the obtained deployment scheme is improved. Therefore, for the case that the monitoring precision of the second deployment scheme on the event to be monitored is smaller than the preset threshold, the monitoring precision of the deployment scheme can be improved by adding one wireless sensor node, so that the monitoring precision requirement can be met.
Next, an operation of adding one wireless sensor node will be described. As shown in fig. 2, a feasible manner of adding a wireless sensor node specifically operates as follows:
s20: and sequentially adding one wireless sensor node of different types in the second deployment scheme to sequentially obtain at least one deployment scheme.
In one deployment scheme, different types of wireless sensor nodes have different degrees of influence on the monitoring accuracy of the deployment scheme. To select a suitable wireless sensor node, a wireless sensor node of some type may be added to the second deployment scenario, resulting in a new deployment scenario. And the types of the wireless sensor nodes are correspondingly different in deployment schemes.
For example, according to an event to be monitored, if there are 3 types of the determined wireless sensor nodes, which are respectively type a, type b, and type c, a wireless sensor node belonging to type a may be added to the second deployment scheme, so as to obtain a new deployment scheme.
S21: and calculating the monitoring precision of each deployment scheme to the event to be monitored.
S22: and screening out the deployment scheme with the monitoring precision larger than the preset threshold value.
In order to enable the monitoring precision of the deployment schemes to meet the monitoring precision requirement, the monitoring precision of at least one deployment scheme to the event to be monitored can be obtained through calculation, so that the deployment scheme meeting the monitoring precision requirement, namely a preset threshold value, is selected. The manner of calculating the monitoring accuracy is similar to that of the monitoring accuracy in S13, and is not described herein again.
S23: and 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.
The calculation manner of the relative deployment cost of the wireless sensor node is similar to the calculation manner of the relative deployment cost in S11, and is not described herein again.
S24: 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.
One or more screened deployment schemes may be possible, and when there are multiple deployment schemes whose monitoring accuracy is greater than a preset threshold, the multiple deployment schemes may be further screened. Specifically, the screening may 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 less impact on the deployment cost of adding it to the second deployment scenario. Therefore, a wireless sensor node with the minimum relative deployment cost can be added to the second deployment scheme to obtain a new deployment scheme, or the deployment scheme obtained by adding the wireless sensor node with the minimum relative deployment cost to the deployment scheme selected in S22 is used as a new deployment scheme, and the new deployment scheme can meet the requirement of monitoring accuracy, and is the optimal deployment scheme.
According to the technical scheme, for the deployment of the wireless sensor nodes, the types of the wireless sensor nodes required by the first deployment scheme can be determined according to the events to be monitored, the number of the wireless sensor nodes of each type is set to be the theoretical maximum value in the first deployment scheme, the relative deployment cost of each type of wireless sensor node is calculated, in order to reduce the deployment cost, one wireless sensor node can be deleted from the wireless sensor node of the type with the maximum relative deployment cost, so that the second deployment scheme is obtained, the operation is executed in a circulating mode, and the new deployment schemes can be obtained in sequence. In order to ensure that the deployment scheme meets the requirement of monitoring precision, the monitoring precision of the deployment scheme needs to be judged every time a new deployment scheme is obtained, and the operation is stopped to be executed circularly until the monitoring precision of one deployment scheme is smaller than or equal to a preset threshold value, so that an optimal deployment scheme can be determined according to the deployment scheme. The optimal deployment scheme is the deployment scheme with the lowest deployment cost determined on the premise that the deployment scheme meets the monitoring precision requirement. Therefore, the technical scheme can effectively reduce the deployment cost on the premise of meeting the monitoring precision requirement of the event to be monitored.
Fig. 3 is a device structure diagram of an event detection-oriented sensor network deployment optimization device provided in an embodiment of the present invention, where the device includes a first determining unit 31, a calculating unit 32, a deleting unit 33, a determining unit 34, and a second determining unit 35:
the first determining unit 31 is configured to determine a first deployment scenario according to an event to be monitored, where the first deployment scenario includes each type of wireless sensor node and the number of the wireless sensor nodes of each type.
The calculating unit 32 is configured to calculate relative deployment costs of the wireless sensor nodes of the respective types.
The deleting 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, so as to obtain a second deployment scheme.
The determining unit 34 is configured to determine whether the monitoring precision of the second deployment scenario on the event to be monitored is greater than a preset threshold; and if the first deployment scheme is larger than the preset threshold, the second determination unit is triggered, and if the first deployment scheme is larger than the preset threshold, the second deployment scheme is used as the first deployment scheme to trigger the calculation unit.
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 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 typemaxWherein E represents the monitoring precision required to be met by the event to be monitored, and wminRepresenting 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 wminThe 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.
Optionally, the computing unit is specifically configured to:
according to the formula
Calculating the relative deployment generations of the wireless sensor nodes of each typeValence of, wherein, ViRepresenting the relative deployment cost of i-type wireless sensor nodes, ciRepresenting the node cost, E (n), of a wireless sensor node of type i1,...ni..,nk) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes1,...ni..,nk) Corresponding monitoring accuracy, E (n)1,...ni-1,..,nk) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes1,...ni-1,..,nk) Corresponding monitoring accuracy.
Optionally, the second determining unit is specifically configured to take the second deployment scenario as an optimal deployment scenario if the monitoring accuracy of the second deployment scenario on the event to be monitored is equal to a preset threshold.
Optionally, the second determining unit includes an adding subunit, a calculating subunit, a screening subunit, and a determining subunit:
and 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.
And the screening subunit is used for screening 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.
For the description of the features in the embodiment corresponding to fig. 3, reference may be made to the related description of the embodiments corresponding to fig. 1 and fig. 2, which is not repeated here.
According to the technical scheme, for the deployment of the wireless sensor nodes, the types of the wireless sensor nodes required by the first deployment scheme can be determined according to the events to be monitored, the number of the wireless sensor nodes of each type is set to be the theoretical maximum value in the first deployment scheme, the relative deployment cost of each type of wireless sensor node is calculated, in order to reduce the deployment cost, one wireless sensor node can be deleted from the wireless sensor node of the type with the maximum relative deployment cost, so that the second deployment scheme is obtained, the operation is executed in a circulating mode, and the new deployment schemes can be obtained in sequence. In order to ensure that the deployment scheme meets the requirement of monitoring precision, the monitoring precision of the deployment scheme needs to be judged every time a new deployment scheme is obtained, and the operation is stopped to be executed circularly until the monitoring precision of one deployment scheme is smaller than or equal to a preset threshold value, so that an optimal deployment scheme can be determined according to the deployment scheme. The optimal deployment scheme is the deployment scheme with the lowest deployment cost determined on the premise that the deployment scheme meets the monitoring precision requirement. Therefore, the technical scheme can effectively reduce the deployment cost on the premise of meeting the monitoring precision requirement of the event to be monitored.
The method and the device for optimizing sensor network deployment facing event detection provided by the invention are described in detail above. The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
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 typemaxWherein E represents the monitoring precision required to be met by the event to be monitored, and wminRepresenting 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 wminWireless 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 ViRepresenting the relative deployment cost of i-type wireless sensor nodes, ciRepresenting the node cost, E (n), of a wireless sensor node of type i1,...ni..,nk) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes1,...ni..,nk) Corresponding monitoring accuracy, E (n)1,...ni-1,..,nk) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes1,...ni-1,..,nk) 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 typemaxWherein E represents the monitoring precision required to be met by the event to be monitored, and wminRepresenting 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 wminThe 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 ViRepresenting the relative deployment cost of i-type wireless sensor nodes, ciRepresenting the node cost, E (n), of a wireless sensor node of type i1,...ni..,nk) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes1,...ni..,nk) Corresponding monitoring accuracy, E (n)1,...ni-1,..,nk) Representing a deployment scenario D (n) determined by k types of wireless sensor nodes1,...ni-1,..,nk) Corresponding monitoring accuracy.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103476042A (en) * | 2013-09-03 | 2013-12-25 | 吉林大学 | Wireless temperature sensor optimizing arrangement method in environment monitoring system |
| CN105636094A (en) * | 2016-03-16 | 2016-06-01 | 中国地质大学（武汉） | Wireless sensor network early warning method and system based on clustering compressed sensing |
-
2017
- 2017-01-11 CN CN201710017926.5A patent/CN106792757B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103476042A (en) * | 2013-09-03 | 2013-12-25 | 吉林大学 | Wireless temperature sensor optimizing arrangement method in environment monitoring system |
| CN105636094A (en) * | 2016-03-16 | 2016-06-01 | 中国地质大学（武汉） | Wireless sensor network early warning method and system based on clustering compressed sensing |
Non-Patent Citations (3)
| Title |
|---|
| Composite Event Coverage in Wireless Sensor;Jing Gao;《2015 IEEE Conference on Computer Communications (INFOCOM)》;20151231;全文 * |
| Delay-Bounded and Energy-Efficient Composite Event Monitoring in Heterogeneous Wireless Sensor Networks;Yingshu Li;《IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS》;20100930;第21卷(第9期);全文 * |
| Deployment Cost Optimal for Composite Event Detection in Heterogeneous Wireless Sensor Networks;Xiaoqing Dong;《IEEE》;20161103;第二节-第三节 * |
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