CN104219683B - Farmland wireless sensor network regenerative resource node deployment method and system - Google Patents
Farmland wireless sensor network regenerative resource node deployment method and system Download PDFInfo
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- CN104219683B CN104219683B CN201410411868.0A CN201410411868A CN104219683B CN 104219683 B CN104219683 B CN 104219683B CN 201410411868 A CN201410411868 A CN 201410411868A CN 104219683 B CN104219683 B CN 104219683B
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
The present invention provides a kind of farmland wireless sensor network regenerative resource node deployment method and system, is related to farmland wireless sensor network technical field, wherein, including：Common batteries node deployment is carried out in monitoring region, regenerative resource number of nodes to be disposed is determined according to default cost and common batteries number of nodes, travel through the common batteries node, maximum expectation can be saved into common batteries node corresponding to energy consumption as node to be replaced, it is replaced with renewable energy source node, and the regenerative resource number of nodes to be disposed is subtracted 1, whether regenerative resource number of nodes to be disposed is 0 described in judgement, if, terminate flow, otherwise dispose next renewable energy source node.Thus the above method solves the problems, such as to preset cost constraint in the monitoring application of prior art farmland, and extends network life to greatest extent.
Description
Technical Field
The invention relates to the technical field of farmland wireless sensor networks, in particular to a method and a system for deploying renewable energy source nodes of a farmland wireless sensor network.
Background
A Wireless Sensor Network (WSN) for farmland can conveniently and accurately acquire real-time environmental information of agricultural production, and becomes a key technology for guiding agricultural production and improving crop yield. The existing farmland wireless sensor network node adopts a battery power supply mode, has serious energy constraint and is one of application bottlenecks of a wireless sensor network in large-scale farmland environment monitoring. In addition, in the application of farmland wireless sensor network environment monitoring, the problems of large number of wireless sensor network nodes, large deployment area, uneven distribution and the like exist, so that the battery replacement is very troublesome. Therefore, the problem of energy supply becomes a first problem restricting the development of the farmland wireless sensor network.
In recent years, renewable energy nodes become a new idea for wireless sensor network research, for example, resources such as solar energy and wind energy in a farmland environment are introduced to solve the problem of energy supply of the farmland wireless sensor network. In the renewable energy node deployment method in the prior art, a common battery node is deployed, and then the renewable energy node is replaced by a main node after deployment, so that the deployment of the renewable energy node is completed.
However, the method only analyzes the energy consumption problem simply and qualitatively, and does not analyze the correlation between the position of the renewable energy source node and the network energy consumption to obtain the optimal position of the renewable energy source node; in addition, the number of renewable energy source nodes is not limited in the prior art, the nodes are all configured according to needs, the problem of preset cost constraint is not considered, and practical application cannot be carried out; finally, the more the farmland wireless sensor network nodes are, the better the farmland wireless sensor network nodes are, and the prior art does not consider how to increase the marginal benefit of a renewable energy node on the life cycle of the network and whether the problem of balance point between the cost and the service life of the network exists.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a farmland wireless sensor network node deployment method and system, which solve the problem of preset cost constraint in farmland monitoring application and prolong the service life of a network to the maximum extent.
In one aspect, the invention provides a method for deploying a farmland wireless sensor network node, which comprises the following steps:
s1, deploying common battery nodes in a monitoring area;
s2, determining the number of renewable energy source nodes to be deployed according to the preset cost and the number of common battery nodes;
s3, traversing the common battery nodes, calculating the expectation energy saving of the traversed current common battery nodes to the peripheral common battery nodes when the traversed current common battery nodes are replaced by the renewable energy source nodes, and taking the common battery nodes corresponding to the maximum expectation energy saving as the nodes to be replaced, wherein the maximum expectation energy saving is a preset maximum threshold value of the energy saving;
and S4, replacing the nodes to be replaced with renewable energy source nodes, subtracting 1 from the number of the renewable energy source nodes to be deployed, judging whether the number of the renewable energy source nodes to be deployed is 0, if so, ending the process, and otherwise, returning to the step S3.
Alternatively, in step S3, the desired energy savings is calculated by,
wherein Eave i Can save energy consumption, pr, corresponding to the current common battery node i j The expected energy consumption of the jth peripheral common battery node of the current common battery node i,n i is the node degree, n, of the current common battery node i j The node degree of the jth peripheral common battery node of the current common battery node i, l is the data length acquired and uploaded by the current common battery node i, and R is the node degree of the jth peripheral common battery node of the current common battery node i s Communication radius of common battery node, epsilon fs Performing R for common battery node s Attenuation factor, epsilon, in intra-radius communication mp Attenuation factor, E, for a common battery node in communication with other renewable energy nodes or aggregation nodes ele For the current power consumption of the internal processing circuit of the common battery node i, d j The distance from the jth peripheral common battery node of the current common battery node i to the sink node.
Optionally, in step S3, the specifically taking the common battery node corresponding to the maximum expected energy consumption saving as the node to be replaced includes:
judging whether the common battery node corresponding to the maximum expected energy saving energy consumption is unique or not, and if so, taking the common battery node corresponding to the maximum expected energy saving energy consumption as a node to be replaced; and otherwise, selecting one of the common battery nodes corresponding to the maximum expected energy saving and farthest from the sink node as a node to be replaced.
Optionally, between step S3 and step S4, the method further includes:
a101: taking the node to be replaced as a cluster head, and generating a renewable energy cluster by adopting a dynamic clustering method;
a102: and if the renewable energy cluster has an island node, adjusting the position of the node to be replaced.
Optionally, in the step a102, the adjusting the position of the renewable energy source node to be replaced specifically includes:
traversing the neighbor nodes of the nodes to be replaced, and searching a neighbor node set v containing all island nodes 1 ；
If the neighbor node set v 1 Only one neighbor node in the set is used as a new node to be replaced, and step S4 is executed, otherwise, the neighbor node set v is searched 1 The neighbor node set v with the highest expected energy saving 2 ；
If the neighbor node set v 2 Taking the neighbor node as a new node to be replaced, and executing the step S4, otherwise, searching the neighbor node set v 2 Neighbor node set v with maximum number of in-reachable neighbor nodes 3 ；
If the neighbor node set v 3 Taking the neighbor node as a new node to be replaced, and executing the step S4, otherwise, searching the neighbor node set v 3 And taking the neighbor node closest to the node to be replaced as a new node to be replaced.
Optionally, between step S3 and step S4, the method further includes:
calculating the marginal benefit when the node to be replaced is replaced by the renewable energy source node, and judging whether the marginal benefit is not greater than a preset value; if yes, directly ending the process, otherwise executing the step S4;
wherein the marginal benefit is in accordance with EL before And EL after Obtained by calculation, EL before For the network life expectancy of the node to be replaced, EL after And replacing the node to be replaced with the renewable energy source node to obtain the expected network life.
Alternatively, the marginal benefit is calculated by the following formula,
EL mr ＝EL before -EL after
wherein the content of the first and second substances,E 0 initial energy of a common battery node, E n For the expected energy consumption of the node to be replaced, E m In order to replace the node to be replaced with the renewable energy source node, the node m is a node with the highest expected energy consumption in other nodes except the node to be replaced.
In another aspect, the present invention provides a system for deploying renewable energy nodes in a wireless sensor network in a farm field, including:
the common battery node deployment unit is used for deploying common battery nodes in a monitoring area;
the determining unit is used for determining the number of the renewable energy source nodes to be deployed according to the preset cost and the number of the common battery nodes;
the to-be-replaced unit is used for traversing the common battery nodes, calculating the expected energy saving of the traversed current common battery node to the peripheral common battery nodes when the traversed current common battery node is replaced by the renewable energy node, and taking the common battery node corresponding to the maximum expected energy saving as the to-be-replaced node, wherein the maximum expected energy saving is a preset maximum threshold value of the energy saving;
the first judging unit is used for replacing the nodes to be replaced with the renewable energy nodes, subtracting 1 from the number of the renewable energy nodes to be deployed, and judging whether the number of the renewable energy nodes to be deployed is 0.
Optionally, the system further comprises:
the generating unit is used for generating a renewable energy cluster by taking the node to be replaced as a cluster head and adopting a dynamic clustering method;
and the adjusting unit is used for adjusting the position of the node to be replaced if the renewable energy cluster has the island node.
Optionally, the system further comprises:
and the second judgment unit is used for calculating the marginal benefit when the node to be replaced is replaced by the renewable energy source node and judging whether the marginal benefit is not more than a preset value.
According to the technical scheme, the renewable energy node deployment method and the renewable energy node deployment system of the farmland wireless sensor network can save energy consumption by calculating the expectation of the traversed current common battery node to the surrounding common battery nodes when the traversed current common battery node is replaced by the renewable energy node, find out the maximum expectation energy consumption, replace the common battery node corresponding to the maximum expectation energy consumption to the renewable energy node, solve the problem of preset cost constraint in farmland monitoring application, and prolong the service life of the network to the maximum extent.
Drawings
Fig. 1 is a schematic flowchart of a renewable energy node deployment method for an agricultural wireless sensor network according to a first embodiment of the present invention;
fig. 2 is a schematic flowchart of a renewable energy node deployment method for a farmland wireless sensor network according to a second embodiment of the present invention;
fig. 3 is a diagram illustrating a deployment position and a position adjustment of a renewable energy node of a wireless sensor network in a farmland according to a second embodiment of the present invention;
FIG. 4 is a graph illustrating a life cycle and a marginal profit of a wireless sensor network for a farm field according to a second embodiment of the present invention as a function of the number of renewable energy nodes;
fig. 5 is a schematic structural diagram of a renewable energy node deployment system of an agricultural wireless sensor network according to a third embodiment of the present invention.
Detailed Description
The following detailed description of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
Fig. 1 is a schematic flow chart illustrating a method for deploying renewable energy nodes in an agricultural wireless sensor network according to a first embodiment of the present invention, and as shown in fig. 1, the method for deploying renewable energy nodes in an agricultural wireless sensor network according to the present embodiment is as follows.
S1, deploying common battery nodes in a monitoring area.
In this step, it should be noted that before the deployment of the common battery nodes, a network topology needs to be constructed, and the deployment of the common battery nodes is performed according to the connectivity of the network and the coverage of the monitored area.
For example, let the coverage radius of the ordinary battery node be R c Communication radius of R s Average distance between nodesThe balance between the node number and the coverage can be achieved, the area of a monitoring region is recorded as A, and the number of the nodes of the deployed common batteries under the constraint of the preset cost is as follows:
the common battery nodes are deployed by adopting the prior art, for example, the common battery nodes are deployed by adopting a random deployment mode in this embodiment, so that the deployed common battery nodes meet the requirements of network connectivity in the monitored area and coverage of the nodes in the monitored area, other node deployment methods can also be used, and the deployment method of the common battery nodes is not limited in this embodiment.
And S2, determining the number of the renewable energy source nodes to be deployed according to the preset cost and the number of the common battery nodes.
In this step, it can be understood that the farmland monitoring has strict preset cost constraint in practical application, that is, due to the limited preset cost, the renewable energy nodes cannot be deployed according to the ideal number in the prior art, and therefore, a maximum number of the renewable energy nodes allowed to be deployed within the preset cost range needs to be found.
For example, the total predetermined cost is C t Cost of a single common battery node is C b Cost of a single renewable energy node is C r The number of common battery nodes is N 0 Calculating the number N of the renewable energy source node deployment r Comprises the following steps:
and S3, traversing the common battery nodes, calculating the expectation energy saving of the traversed current common battery node to the peripheral common battery nodes when the traversed current common battery node is replaced by the renewable energy node, and taking the common battery node corresponding to the maximum expectation energy saving as a node to be replaced, wherein the maximum expectation energy saving is a preset maximum threshold value of the energy saving.
In this step, it should be noted that the peripheral common battery node refers to a communication radius R when the peripheral common battery node is replaced with a renewable energy node s A common battery node within range.
Specifically, traversing all common battery nodes in the monitoring area, and finding out the maximum expected energy consumption saving value when each common battery node is replaced by a renewable energy node;
and taking the common battery node corresponding to the expected maximum energy consumption saving value as the node to be replaced.
And S4, replacing the nodes to be replaced with the renewable energy nodes, subtracting 1 from the number of the renewable energy nodes to be deployed, judging whether the number of the renewable energy nodes to be deployed is 0, if so, ending the process, and otherwise, returning to the step S3.
In this step, if the number of the renewable energy nodes to be deployed is not 0, the step S3 is continuously performed on the remaining renewable energy nodes except the renewable energy nodes to be deployed, that is, the next renewable energy node is deployed, and if the number of the renewable energy nodes to be deployed is 0, the deployment of all the renewable energy nodes is completed, and the process is ended.
According to the renewable energy node deployment method of the farmland wireless sensor network, common battery nodes are deployed in a monitored area, the number of renewable energy nodes to be deployed is further determined according to preset cost and the number of the common battery nodes, the common battery nodes are traversed, energy consumption can be saved by calculating expectation of the traversed current common battery nodes to peripheral common battery nodes when the traversed current common battery nodes are replaced by the renewable energy nodes, the common battery node corresponding to the largest expected energy consumption can be saved is used as a node to be replaced, the node to be replaced is replaced by the renewable energy node, the number of the renewable energy nodes to be deployed is reduced by 1, whether the number of the renewable energy nodes to be deployed is 0 or not is judged, if yes, the flow is ended, and if not, the next renewable energy node is deployed. Therefore, the method can be correspondingly deployed aiming at the renewable energy source nodes with different quantities, the renewable energy source utilization can be maximized, the actual consumption of the battery is reduced, and the maximum network service life is obtained.
Fig. 2 is a schematic flowchart illustrating a method for deploying renewable energy nodes of an agricultural wireless sensor network according to a second embodiment of the present invention, and as shown in fig. 2, the method for deploying renewable energy nodes of an agricultural wireless sensor network according to this embodiment is as follows.
201. And carrying out common battery node deployment in the monitored area.
In this step, it should be noted that, in this embodiment, on the basis of deployment of common battery nodes in the prior art, renewable energy nodes are used to replace the optimal common battery nodes to solve the problem of the constraint of the preset cost of the farmland in the prior art. Therefore, it is first necessary to perform the deployment of ordinary battery nodes in the monitored area, which is shown as (a) in fig. 3.
202. And determining the number of the renewable energy source nodes to be deployed according to the preset cost and the number of the common battery nodes.
In this step, for example, the renewable energy provided in this embodiment includes, but is not limited to, solar energy, wind energy, and the like, which may be determined according to the renewable energy situation at the location of the farmland.
Generally, due to the limitation of preset cost, the number of the renewable energy nodes is also limited to a certain extent, and how to extend the network life of each renewable energy node to the greatest extent during the deployment of the renewable energy nodes is an important invention point of this embodiment.
Further, in order to accurately calculate the node energy consumption and the network lifetime under different conditions, a routing mode of data transmission needs to be determined first.
For example, in a planar routing manner, a node closer to a sink node needs to undertake data forwarding tasks of all remote nodes, and for a large-scale application scenario of a farmland wireless sensor network and a situation of a large number of nodes, energy of peripheral nodes of the sink node is rapidly consumed, so that the service life of the network is shortened.
In the hierarchical clustering routing mode, the cluster head forwards the data of the nodes in the cluster to the sink node in a one-hop manner, and the energy consumption of the cluster head is obviously higher than that of other nodes due to the long transmission distance.
Based on the defects of the two methods, the dynamic clustering method based on cluster head rotation is adopted in the embodiment, the number of nodes in a cluster is limited, and the extra energy consumption of the cluster head is averaged among the nodes in the cluster, so that the life cycle of the network is prolonged.
203. Traversing the common battery nodes, calculating the expectation energy saving of the traversed current common battery nodes to the peripheral common battery nodes when the traversed current common battery nodes are replaced by the renewable energy source nodes, and taking the common battery nodes corresponding to the maximum expectation energy saving as the nodes to be replaced.
In this step, the step of using the common battery node corresponding to the maximum expected energy consumption saving as the node to be replaced specifically includes:
judging whether the common battery nodes corresponding to the maximum expected energy consumption saving are one, if so, taking the common battery nodes corresponding to the maximum expected energy consumption saving as nodes to be replaced; and otherwise, selecting one of the common battery nodes corresponding to the maximum expected energy saving and farthest from the sink node as a node to be replaced.
Optionally, according to expected energy consumption of a common battery node, when the common battery node is replaced with a renewable energy node, expected energy consumption of the node for surrounding common battery nodes may be obtained, and a maximum value of the expected energy consumption may be found, as shown in fig. 3 (b), where a node a in the figure is a common battery node position corresponding to the maximum expected energy consumption, that is, a node to be replaced.
Optionally, the maximum allowable number of nodes in the cluster, which are all composed of common battery nodes in the cluster, is recorded as A 1 For the cluster with renewable energy source node as the cluster head, the maximum allowable node number is A 2 ，A 2 >A 1 For example, in the present embodiment, A 1 ＝10，A 2 =50, note n k Is the node degree of the current common battery node k, d k The distance R from the current common battery node k to the sink node s The distance of the common battery nodes during communication is also the communication radius of the range of the peripheral common battery nodes, and the probability that each common battery node k is selected as a cluster head when no renewable energy source node exists is obtainedSo the expected energy consumption of the current common battery node k is:
wherein l is the data length epsilon of the current common battery node k for collecting and uploading fs Performing R for common battery node s Attenuation factor in radial communication, epsilon mp The attenuation factor is the attenuation factor when the common battery node is communicated with other renewable energy source nodes or sink nodes;
for example, in this embodiment, l =1000bit ele ＝50nJ/bit，，ε fs ＝10pJ/bit/m 2 ,ε mp ＝0.0013pJ/bit/m 4 。
Optionally, after replacing any common battery node i with a renewable energy node, calculating expected energy saving of the common battery nodes at the periphery as follows:
wherein Escape i The expected energy consumption, pr, corresponding to the current common battery node i can be saved j Average expected energy consumption per round of j (th) peripheral common battery nodes of the current common battery node i, n i The node degree of the current common battery node i.
204. And taking the node to be replaced as a cluster head, and generating a renewable energy cluster by adopting a dynamic clustering method.
In this step, it should be noted that a dynamic clustering method is adopted to generate a renewable energy cluster for the node to be replaced as a cluster head, and if the number of nodes selected to be added to the cluster exceeds the maximum allowable number a 2 Sorting the nodes selected to be added into the renewable energy cluster according to the distance between the node and the sink node, and preferentially adding the nodes into the renewable energy cluster if the distance is larger until all the nodes are added into the renewable energy cluster or the number of the added nodes exceeds the maximum allowable number A 2 Optional additions, if any, may be madeAnd if the number of the renewable energy node clusters exceeds 1 node, adding the renewable energy cluster with less nodes in the cluster according to the number of the nodes in the cluster.
205. And if the renewable energy cluster has island nodes, adjusting the positions of the nodes to be replaced.
In this step, it should be noted that, because the dynamic clustering routing structure easily generates a small number of "island nodes", and the "island nodes" are far away from the sink node, the transmission energy consumption is large, and the number is small, and the extra cluster head communication energy consumption cannot obtain a longer node life through the average of a large number of nodes in the cluster, so after clustering the replaced renewable energy node, it is necessary to eliminate the newly generated "island nodes".
For a common battery node, if the condition is met: the node b does not belong to any renewable energy cluster, and if a certain node w belongs to a certain renewable energy cluster in any multi-hop path from the node b to the sink node, the node b is called as an island node. The "island node" may be one or multiple adjacent, and usually the "island node" appears at a gap between clusters or at an edge of a farmland monitoring area, as shown in fig. 3 (c), where a node c is a cluster head node of a current renewable energy cluster;
optionally, the adjusting specifically includes:
traversing the neighbor nodes of the nodes to be replaced, and searching a neighbor node set v containing all island nodes 1 ；
If the neighbor node set v 1 Only one neighbor node in the set is used as a new node to be replaced, and step S4 is executed, otherwise, the neighbor node set v is searched 1 The neighbor node set v with the highest expected energy saving 2 ；
If the neighbor node set v 2 Taking the neighbor node as a new node to be replaced, and executing the step S4, otherwise, searching the neighbor node set v 2 Neighbor node set v with maximum number of in-reachable neighbor nodes 3 ；
If the neighbor node set v 3 Only one neighbor node in the set is used as a new node to be replaced, and step S4 is executed, otherwise, the neighbor node set v is searched 3 And taking the neighbor node closest to the node to be replaced as a new node to be replaced.
Selecting the position of the neighbor node d meeting the above conditions, and taking the neighbor node d as a new node to be replaced, as shown in (d) in fig. 3.
206. Calculating the marginal benefit when the node to be replaced is replaced by the renewable energy source node, and judging whether the marginal benefit is not greater than a preset value; if yes, the flow is directly ended, otherwise step 207 is executed.
In this step, all renewable energy nodes and common battery nodes in a renewable energy cluster generated by taking the renewable energy nodes as a cluster head are excluded, expected energy consumption is calculated for other nodes, a maximum value is selected, according to the maximum value of the expected energy consumption of other nodes, the network expected life of the node to be replaced and the network expected life of the node to be replaced when the node to be replaced is replaced by the renewable energy nodes are calculated, according to the network expected life, marginal income when the node to be replaced is replaced by the renewable energy nodes is obtained, whether the marginal income is not greater than a preset value or not is judged, if yes, deployment of the current node is cancelled, the flow is directly ended, and if not, step 207 is executed.
Note that the initial energy of the common battery node is E 0 The expected energy consumption of the node to be replaced is E n So the expected lifetime of the network replacing a common battery node is:
the expected energy consumption when the node to be replaced is replaced by the renewable energy source node is recorded as E m The node m is the node with the highest expected energy consumption in other nodes except the node to be replaced, so the node to be replaced is replacedThe expected network life when replacing with a renewable energy node is:
for example, the marginal benefit of the present embodiment is calculated as follows,
EL mr ＝EL before -EL after
it should be noted that, the calculation method of the marginal benefit in this embodiment is a subtraction form, but in practical application, the present invention does not limit the calculation method of the marginal benefit, and may also be a division form, which is determined according to actual situations.
It will be appreciated that, as the preset cost increases, the maximum number of nodes allowed to deploy renewable energy increases, with marginal gain EL mr And gradually decreasing, and when the marginal profit is less than or equal to the preset value, the effect of continuously increasing the cost income on the service life of the network is weakened or eliminated.
Fig. 4 shows a graph of a life cycle and a marginal benefit of a farmland wireless sensor network provided by a second embodiment of the present invention as a function of the number of renewable energy nodes, as shown in fig. 4, the marginal benefit gradually decreases as the proportion of the renewable energy nodes increases, and the life cycle of the network tends to be stable, so when the number of deployed renewable energy nodes reaches a certain number, the influence of the deployment of the renewable energy nodes on the life cycle of the network is not changed, that is, the deployment of the renewable energy nodes is continued, and the expected life of the network cannot be prolonged.
For example, in this embodiment, the preset value of the marginal benefit is 0, that is, when the marginal benefit obtained when the node to be replaced is replaced with the renewable energy node is not greater than 0, the cost is continuously increased to deploy the renewable energy node so that the network life cannot be prolonged, that is, the influence of the deployed renewable energy node on the network life is weakened or disappears, the deployment of the renewable energy node is cancelled, and the process is directly ended.
207. And replacing the nodes to be replaced with renewable energy nodes, subtracting 1 from the number of the renewable energy nodes to be deployed, judging whether the number of the renewable energy nodes to be deployed is 0, if so, ending the process, otherwise, returning to the step 203.
In this step, according to the method for deploying renewable energy nodes of a farmland wireless sensor network, the maximum number of renewable energy nodes allowed to be deployed is obtained through the preset cost, the optimal positions for deploying the renewable energy nodes are found out according to the expected energy consumption saving, and the 'isolated island nodes' are eliminated by adjusting the optimal positions for deploying the renewable energy nodes, so that the problem of cluster structure on node coverage is solved, each deployed renewable energy node can reduce the energy consumption of a common battery as much as possible, and finally the service life of the network is maximized under the constraint of the preset cost.
Fig. 5 is a schematic structural diagram illustrating a renewable energy node deployment system of an agricultural wireless sensor network according to a third embodiment of the present invention, and as shown in fig. 5, the renewable energy node deployment system of an agricultural wireless sensor network in this embodiment includes: a general battery node deployment unit 51, a determination unit 52, a replacement unit 53, and a first determination unit 54;
the common battery node deployment module 51 is configured to deploy common battery nodes in a monitored area;
the determining unit 52 is configured to determine the number of renewable energy nodes to be deployed according to a preset cost and the number of common battery nodes;
the replacing unit 53 is configured to traverse the common battery node, calculate expected energy saving of the current common battery node, which is traversed, to the peripheral common battery node when the traversed common battery node is replaced with the renewable energy node, and use the common battery node corresponding to the maximum expected energy saving as the node to be replaced, where the maximum expected energy saving is a preset maximum threshold of energy saving;
the first determining unit 54 is configured to replace the node to be replaced with a renewable energy node, subtract 1 from the number of the renewable energy nodes to be deployed, and determine whether the number of the renewable energy nodes to be deployed is 0.
Optionally, the system further comprises: a generation unit and an adjustment unit;
the generating unit is used for generating a renewable energy cluster by taking the node to be replaced as a cluster head and adopting a dynamic clustering method;
and the adjusting unit is used for adjusting the position of the node to be replaced when the renewable energy cluster has the island node.
The adjusting unit specifically includes:
traversing the neighbor nodes of the nodes to be replaced, and searching a neighbor node set v containing all island nodes 1 ；
If the neighbor node set v 1 Takes the neighbor node as a new node to be replaced, and executes the first determination unit 54, otherwise, searches the neighbor node set v 1 Neighbor node set v with maximum expected energy saving 2 ；
If the neighbor node set v 2 Takes the neighbor node as a new node to be replaced, and executes a first judgment unit 54, otherwise, finds the neighbor node set v 2 Neighbor node set v with maximum number of in-reachable neighbor nodes 3 ；
If the neighbor node set v 3 Takes the neighbor node as a new node to be replaced, and executes a first judgment unit 54, otherwise, finds the neighbor node set v 3 And taking the neighbor node closest to the node to be replaced as a new node to be replaced.
Optionally, the system further comprises: a second judgment unit;
the second judging unit is used for calculating the marginal benefit when the node to be replaced is replaced by the renewable energy source node, and judging whether the marginal benefit is not greater than a preset value.
After the deployment of the renewable energy node deployment system of the farmland wireless sensor is completed, the marginal profit of each renewable energy node after the deployment is evaluated, the deployment of the renewable energy nodes can be stopped when the cost is increased to reach the inflection point of the marginal profit curve, unnecessary cost investment is reduced, the problem of preset cost constraint in farmland monitoring application is solved, game balance between preset cost and network life is achieved, and the network life is prolonged to the maximum extent.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions and scope of the present invention as defined in the appended claims.
Claims (6)
1. A renewable energy node deployment method for a farmland wireless sensor network is characterized by comprising the following steps:
s1, deploying common battery nodes in a monitoring area;
s2, determining the number of renewable energy source nodes to be deployed according to the preset cost and the number of common battery nodes;
s3, traversing the common battery nodes, calculating the expectation of the traversed current common battery nodes to the peripheral common battery nodes when the traversed current common battery nodes are replaced by the renewable energy source nodes, and taking the common battery nodes corresponding to the maximum expectation of energy conservation as nodes to be replaced;
s4, replacing the nodes to be replaced with renewable energy source nodes, subtracting 1 from the number of the renewable energy source nodes to be deployed, judging whether the number of the renewable energy source nodes to be deployed is 0, if yes, ending the process, otherwise, returning to the step S3; the desired energy savings are calculated by the following equation,
wherein Escape i Can save energy consumption, pr, corresponding to the current common battery node i j The expected energy consumption of the jth peripheral common battery node of the current common battery node i,n i is the node degree, n, of the current common battery node i j The node degree of the jth peripheral common battery node of the current common battery node i, l is the data length acquired and uploaded by the current common battery node i, and R s Communication radius of common battery node, epsilon fs Radius R for common battery node s Attenuation factor in internal communication, epsilon mp Attenuation factor for a common battery node in communication with other renewable energy nodes or sink nodes, E ele For the current power consumption of the internal processing circuit of the common battery node i, d j The distance from the jth peripheral common battery node of the current common battery node i to the sink node.
2. The method according to claim 1, wherein in step S3, the step of using the common battery node corresponding to the maximum expected energy consumption saving as the node to be replaced specifically includes:
judging whether the common battery node corresponding to the maximum expected energy saving energy consumption is unique or not, and if so, taking the common battery node corresponding to the maximum expected energy saving energy consumption as a node to be replaced; and otherwise, selecting one of the common battery nodes corresponding to the maximum expected energy saving and farthest from the sink node as a node to be replaced.
3. The method of claim 1, wherein between the step S3 and the step S4, further comprising:
a101: taking the node to be replaced as a cluster head, and generating a renewable energy cluster by adopting a dynamic clustering method;
a102: and if the renewable energy cluster has island nodes, adjusting the positions of the nodes to be replaced.
4. The method according to claim 3, wherein in the step a102, the adjusting the position of the renewable energy node to be replaced specifically includes:
traversing the neighbor nodes of the nodes to be replaced, and searching a neighbor node set v containing all island nodes 1 ；
If the neighbor node set v 1 Only one neighbor node in the set is used as a new node to be replaced, and step S4 is executed, otherwise, the neighbor node set v is searched 1 The neighbor node set v with the highest expected energy saving 2 ；
If the neighbor node set v 2 Only one neighbor node in the set is used as a new node to be replaced, and step S4 is executed, otherwise, the neighbor node set v is searched 2 Neighbor node set v with maximum number of in-reachable neighbor nodes 3 ；
If the neighbor node set v 3 Taking the neighbor node as a new node to be replaced, and executing the step S4, otherwise, searching the neighbor node set v 3 And taking the neighbor node closest to the node to be replaced as a new node to be replaced.
5. The method according to any one of claims 1-4, wherein between step S3 and step S4, further comprising:
calculating the marginal benefit when the node to be replaced is replaced by the renewable energy source node, and judging whether the marginal benefit is not greater than a preset value; if yes, directly ending the process, otherwise executing the step S4;
wherein the marginal benefit is in accordance with EL before And EL after Obtained by calculation, EL before For the network life expectancy of the node to be replaced, EL after To replace the node to be replaced with a regenerable nodeNetwork life expectancy at the energy node.
6. The method of claim 5, wherein the marginal gain is calculated by the following equation,
EL mr ＝EL before -EL after
wherein the content of the first and second substances,E 0 initial energy of a common battery node, E n For the expected energy consumption of the node to be replaced, E m In order to replace the node to be replaced with the renewable energy source node, the m is a node with the highest expected energy consumption in other nodes except the node to be replaced.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101155090A (en) * | 2006-09-29 | 2008-04-02 | 湖南大学 | Agricultural water-saving irrigation system and method based on wireless sensor network |
| WO2011011811A1 (en) * | 2009-07-29 | 2011-02-03 | Commonwealth Scientific And Industrial Research Organisation | Energy-aware compressive sensing |
| CN103987055A (en) * | 2014-05-27 | 2014-08-13 | 北京农业信息技术研究中心 | Wireless sensor network node deployment and power supply method |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101155090A (en) * | 2006-09-29 | 2008-04-02 | 湖南大学 | Agricultural water-saving irrigation system and method based on wireless sensor network |
| WO2011011811A1 (en) * | 2009-07-29 | 2011-02-03 | Commonwealth Scientific And Industrial Research Organisation | Energy-aware compressive sensing |
| CN103987055A (en) * | 2014-05-27 | 2014-08-13 | 北京农业信息技术研究中心 | Wireless sensor network node deployment and power supply method |
Non-Patent Citations (1)
| Title |
|---|
| 基于簇首轮换的农田WSN节点能耗状态机;缪祎晟等;《计算机工程与设计》;20140816;第35卷(第8期);第2723-2727页 * |
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