CN111290405B - Method and system for scheduling mobile robot of agricultural condition acquisition edge server of burst task - Google Patents
Method and system for scheduling mobile robot of agricultural condition acquisition edge server of burst task Download PDFInfo
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Abstract
The invention discloses a dispatching method and a dispatching system for a mobile robot of an agricultural condition acquisition edge server of a burst task, wherein the method comprises the following steps: the server processes the data acquired by the wireless sensor network by adopting an intelligent algorithm, and determines parameters such as the number, the position and the like of the abnormal sensing data nodes; the server adopts a greedy algorithm to solve the number, the positions and the number of the coverable abnormal perception data nodes of the mobile edge server; and then, according to the data quantity of the abnormal sensing data nodes and the bearing scale of the edge server mobile robot, solving the number of the edge server mobile robots again. And finally, driving the edge computing robot to enter a designated position to finish the transmission of agricultural condition data. The invention drives a plurality of edge mobile robots to complete data acquisition based on the quantity of data to be transmitted in the emergency region, and provides processing efficiency.
Description
Technical Field
The invention relates to the technical field of agricultural information, in particular to a scheduling method and a system for an agricultural condition acquisition edge server mobile robot of a sudden task.
Background
As is well known, the modern agriculture is taken as a priority strategy for the future development of the country in each country, and the modern agriculture, the precise agriculture, the intelligent agriculture and the like compete for new high points in the international major countries. The acquisition of agricultural conditions is one of key foundations for realizing intelligent agriculture and accurate agriculture. In order to construct a modern agriculture system, data with various types, heterogeneous data types and large data difference are required to be collected especially under burst conditions, however, on one hand, a large amount of data is used for the data with huge load and low value density brought by a communication network; on the other hand, because of the special agricultural environment, the fixed communication base station cannot be built in farmland, orchards and other environments. The traditional agricultural condition acquisition is mostly based on an agricultural wireless sensor network, and the agricultural data acquisition is completed in a periodic mode. When a sudden task is encountered, a large amount of data needs to be collected, a huge load is brought to the network, and the defects of poor real-time performance, large data volume, low information value density and the like exist. Meanwhile, the existing technology and invention can not meet the agricultural condition acquisition requirement of burst tasks. Therefore, constructing a mobile edge server robot for agricultural condition acquisition facing sudden tasks and a related scheduling strategy become key problems and technologies to be solved in order to change agricultural condition acquisition.
Disclosure of Invention
In order to overcome the defects and shortcomings in the prior art, the invention provides a dispatching method and a dispatching system for an agricultural condition acquisition edge server mobile robot of a burst task, which can be used for data compression, processing, information extraction and related information rapid transmission under the burst task.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a method for dispatching a mobile robot of an edge server for acquiring agricultural conditions of burst tasks comprises the following steps:
the edge server classifies abnormal agricultural condition data by adopting an intelligent algorithm;
the edge server determines the number and the position information of abnormal data sensing nodes;
adopting a greedy algorithm to primarily determine the number and positions of the mobile robots needing the edge server and the sensing nodes capable of covering abnormal data;
based on the bandwidth of the mobile robot of the edge server and the number information of the coverable nodes, secondarily determining the number of the robots;
driving the edge service mobile robot to enter a designated position;
and (5) completing agricultural condition acquisition of the burst task.
As an optimal technical scheme, the abnormal agricultural condition data is classified specifically as follows:
the wireless sensor network deployed in the farmland environment gathers the collected data to the server, and the collected data comprises sensing data, node ID and node position information;
the edge server judges the information collected by the nodes according to the normal range interval or by adopting a support vector machine algorithm;
and classifying the nodes which are not in the normal range into a sensing abnormal data node set, and classifying the abnormal data node set into an area which is formed by the abnormal data node set as an emergency area.
As an preferable technical scheme, the method for determining the number and the position of the robots needing to move the edge server for the first time by adopting a greedy algorithm and the sensing nodes capable of covering abnormal data specifically comprises the following steps:
according to the node position, the communication radius of the mobile edge service node is converted into the problem of the least circle covering the most points, and then a greedy algorithm is adopted to solve the problem of the least mobile edge service node covering the most points, and the method comprises the following steps:
firstly, sorting all points according to ascending order of the abscissa;
taking out the point with the smallest abscissa, regarding the point as a point on the left half circumference, taking the point on the x axis which is d from the abscissa of the point as a circle center, taking d as a radius from the circle center as a circle, and then removing the point contained in the circle; then continuously selecting the point with the smallest abscissa among the rest points, repeating the above operation until all the points are included in the circle, wherein the circle is obtained at the moment, and the number of the circles is the optimal solution of the problem;
the points are sequenced according to the X axis to obtain a section which can cover the points on the X axis, and if the left section of the next point is larger than the current right section from the leftmost point, a new mobile edge server is needed; if the next right interval is smaller than the current right interval, the current right interval needs to be updated to be small because all points must be covered;
if the coordinates of the circle center of the communication circle of the edge server are at the left side of the coordinates of the previous circle center, the coordinates of the previous circle center are discarded, otherwise, the circle center is indicated to be established, by the method, the circle can cover surrounding points as much as possible, the local is optimal, and the global optimal is satisfied by repeating each operation.
As an preferable technical scheme, the method for secondarily determining the number of the robots based on the bandwidth and the number information of the coverable nodes of the edge server mobile robot specifically includes:
if the data transmission time is less than the limit time, namely, the time limit condition is met;
if the data transmission time is limited by university, namely the time limiting condition is not met; then adding an edge robot and repeating the steps until the number of the mobile nodes is increased to meet the time limit condition.
As a preferred technical solution, the step of determining the number of mobile robots of the edge server specifically includes:
and the cloud server solves the number k of the mobile robots participating in the burst edge server according to the perceived scale of the burst task agriculture condition data, the data volume and the bearing scale of the mobile robots of the edge server.
As a preferred technical solution, the step of determining the position of the edge server by using the gravity center method specifically includes:
clustering the sensing areas according to the positions of wireless sensing nodes and the data quantity to be transmitted, and dividing the sensing areas into k sub-areas, wherein the sensing areas are areas formed by sensing nodes participating in burst tasks;
then, constructing a polygon for a certain sub-region according to the position of the sensing node, and acquiring the working position of the edge server mobile robot by taking the gravity center position of the polygon as the agricultural condition.
As a preferable technical scheme, after the edge server mobile robot enters a preset position, firstly broadcasting information M1 added into the sub-network, and after surrounding sensing nodes receive the information M1, sending determination information M2 added into the sub-network;
after networking is completed, the wireless sensor network node transmits data to the edge server mobile robot R through a communication network;
after the R collects the data of all the sensing nodes, preprocessing the data, extracting the agriculture condition, and then completing the data transmission in a high-speed communication channel.
The invention also provides a dispatching system of the agricultural condition acquisition edge server mobile robot of the burst task, which comprises a classification module, an abnormal data determination module, a processing module, a secondary determination module and a driving module;
the classification module is used for classifying abnormal agricultural condition data by the edge server through an intelligent algorithm;
the abnormal data determining module is used for determining the number and the position information of abnormal data sensing nodes by the edge server;
the processing module is used for primarily determining the number and the positions of the mobile robots needing the edge server and the coverable abnormal data sensing nodes by adopting a greedy algorithm;
the secondary determining module is used for secondarily determining the number of the robots based on the bandwidth of the edge server mobile robot and the number information of the coverable nodes;
the driving module is used for driving the edge server mobile robot to enter a designated position to complete agricultural condition acquisition of the burst task.
As an optimal technical scheme, the classification module comprises an acquisition module, a judgment module and an emergency region determination module;
the acquisition module is used for gathering acquired data to a server by a wireless sensor network deployed in a farmland environment, wherein the acquired data comprises sensing data, node ID and node position information;
the judging module is used for judging the node acquisition information according to the normal range interval or by adopting a support vector machine algorithm by the edge server;
the emergency determining module is used for classifying the nodes which are not in the normal range into a sensing abnormal data node set and an area formed by the abnormal data node set as an emergency area.
As an preferable technical scheme, the secondary determining module specifically includes:
if the data transmission time is less than the limit time, namely, the time limit condition is met;
if the data transmission time is limited by university, namely the time limiting condition is not met; then adding an edge robot and repeating the steps until the number of the mobile nodes is increased to meet the time limit condition.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the invention has the characteristics of small data transmission delay, low cost and the like. Firstly, driving a plurality of edge server mobile robots to complete data acquisition based on the quantity of data to be transmitted in an emergency area; meanwhile, the data compression, agriculture condition extraction and other methods are adopted, so that the transmission data volume is reduced, and meanwhile, the data communication is completed through a high-speed communication module configured by the edge server mobile robot. And secondly, the edge server mobile robot can be reused, so that the cost is reduced.
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Fig. 1 is a flow chart of a method for dispatching an agricultural condition acquisition edge server mobile robot for burst tasks.
Fig. 2 is a schematic diagram of a dispatching system of an agricultural condition acquisition edge server mobile robot for burst tasks.
Fig. 3 is a schematic structural view of the classification module according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Example 1
The agricultural condition acquisition system is based on a traditional wireless sensor network, and is additionally provided with an edge server mobile robot, wherein the edge server mobile robot consists of a mobile module, a low-speed communication module, a high-speed communication module, a calculation server, a navigation system and the like; the computing server is used for fusing data of the traditional wireless sensor network, extracting agricultural conditions and the like.
The traditional agricultural wireless sensor network periodically senses data and transmits the sensed data to a remote cloud server through a wireless communication network. When sensing abnormal data, the cloud server processes the abnormal data, and determines the area of an emergency (the area of a convex polygon formed by the positions of abnormal data sensing nodes) and the number of nodes (the abnormal data sensing nodes and a neighbor node set thereof) which need to participate in the emergency task according to the number and the positions of the abnormal sensing data nodes; and further determining the burst task data acquisition scale.
As shown in fig. 1, the method for scheduling the mobile robot of the edge server for acquiring the agricultural condition of the burst task in the embodiment includes the following steps:
s100, classifying abnormal agricultural condition data by an edge server by adopting an intelligent algorithm, wherein the method specifically comprises the following steps:
s101, collecting collected data to a server by a wireless sensor network deployed in a farmland environment, (the collected data comprises sensing data, node IDs and node position information (or node position information corresponding to the node IDs in an edge server)). And the edge server judges the information collected by the nodes according to the normal range interval or by adopting a support vector machine or other intelligent algorithms. Then, classifying the nodes which are not in the normal range as a sensing abnormal data node set; the region formed by the abnormal data node set is an emergency region.
For example: in a block of farmland a, 20 sensing nodes are deployed, for example sensing soil humidity. The normal humidity for crops is (20% -50%). The 20 pieces of perception data are (20%, 23%,45%,65%,34%, 78%,56%,46%,78%,60%, 25%,26%,56%,49%,45%, 58%,23%,34%,56%, 45%) by number (i.e., node ID). The server determines (4,6,7,9,10,13,16,19) as a function of the normal range based on humidity.
S102, the edge server drives the abnormal node to collect more data (such as turning on the node which does not work before), and further the sensing area is detected more finely.
Note: i.e., the amount of data that a node needs to transmit, will surely lead to congestion of the network.
S103, the edge server determines the number of the edge servers to be moved according to the data collection amount of the single node, the transmission time limit of the supportable capacity of the edge servers (particularly the bandwidth of the edge servers) and other factors.
S200, determining the number and the position information of abnormal data sensing nodes by an edge server;
s300, adopting a greedy algorithm to primarily determine the number and the positions of the mobile robots needing the edge server and the covered abnormal data sensing nodes;
for example: with the above example in mind, the set of perceptually anomalous data nodes (4,6,7,9,10,13,16,19) total 8 nodes. First, according to the node position, the communication radius of the edge service node is moved, the problem is converted into a least circle coverage most point problem, and then a greedy algorithm is adopted to solve the least movement edge server node coverage most point problem. (this algorithm is a classical algorithm, described briefly below.)
S301, firstly, ordering all points according to the ascending order of the abscissa. The point with the smallest abscissa is taken out each time (the point is used for representing the abnormal node of the perception data), the point is regarded as the point on the left half circumference, the point on the x axis which is d from the point is taken as the center of a circle, the circle is taken as the radius from the center of the circle (the center of the circle is on the right side of the point coordinate), and then the point contained in the circle is removed. And then continuously selecting the point with the smallest abscissa among the rest points, and repeating the above operation until all the points are included in the circles, wherein the number of the circles obtained at the moment is the optimal solution of the problem, and the indication that all the points are covered is realized.
S302, firstly, sorting the points according to the X axis to obtain the section which can cover the points on the X axis. Starting from the leftmost point, if the left interval of the next point is larger than the current right interval, a new mobile edge server is needed; if the next right interval is smaller than the present right interval, the present right interval needs to be updated to be small because all points must be covered.
S303, if the coordinates of the circle center of the communication circle of the edge server mobile robot are at the left side of the coordinates of the previous circle center, discarding the coordinates of the previous circle center, otherwise, indicating that the circle center is established.
S400, according to the method, the number of edge server mobile robots (hereinafter referred to as edge robots) covering all abnormal data and the number of possible coverage nodes can be obtained, and the positions where the edge robots are deployed are still available, but some edge robots have fewer coverage nodes and some edge robots have more coverage nodes. Meanwhile, the edge robot and the covered nodes are divided into a plurality of subareas.
For the edge robots with a plurality of coverage nodes, the defects of large agricultural condition data quantity, high delay and the like exist, and the risk of overtime of data acquisition time can be caused.
S500, determining the number of the edge robots according to the factors such as the bandwidth of the mobile edge robots, the number of the coverage nodes and the like.
S501, if the data transmission time is smaller than the limit time, namely, the time limit condition is met.
S502, if the data transmission time university limits the time, namely the time limit condition is not met; an edge robot is added, and the steps are repeated until the number of the mobile nodes is increased to meet the time limiting condition.
For example: through steps S303 and S304, the number of the covered nodes of the edge robot is determined to be 6, the perceived data volume of each node is 10Mb, the transmission rate between the edge robot and the nodes is 1Mb/S, and the transmission rate between the edge robot and the edge server is 100Mb/S; meanwhile, the edge robot and the nodes are the distance of one hop between the edge robot and the edge server; the limiting time is 40s. Thus, the transmission time can be calculated as follows:
6 x 10/1+6 x 10/100=60.6s >40s does not satisfy the condition.
Then, an identical edge robot is added, and the data transmission time is calculated to be 30.3s by adopting an identical method.
In summary, the sub-area needs two edge robots, and so on, the number k of edge robots needed for the whole emergency area can be obtained.
S600, the server drives k robots to move the designated positions to finish data collection.
In this embodiment, when the scale and the data volume of agricultural condition data perception exceed the limits that the wireless sensor network can bear, the cloud server drives the edge server mobile robot to enter the emergency region, and data fusion and transmission are completed. For this reason, the scheduling problem of two edge server mobile robots needs to be solved, 1) number; 2) The edge server moves the robot position. The first problem is that the cloud server solves the number k of the mobile robots participating in the sudden edge server according to the perceived scale of the sudden task agriculture condition data, the data volume and the scale that the mobile robots of the edge server can bear. The second problem is that the sensing area (the area formed by sensing nodes participating in burst tasks) is clustered according to the positions of wireless sensing nodes, the data quantity to be transmitted and the like, and the sensing area is divided into k sub-areas. Then, a polygon is constructed for a certain sub-area according to the position of the sensing node, etc., and the position of the center of gravity of the polygon (the polygon takes the data amount as the quality) is taken as the position of the agricultural condition to acquire the working position of the edge server mobile robot. Specifically, after the edge server mobile robot enters a preset position, the information M1 joining the sub-network is broadcast first, and after the surrounding sensing nodes receive the information M1, the determination information M2 joining the sub-network is transmitted. After networking is completed, the wireless sensor network node transmits data to the edge server mobile robot R through a communication network. After the R collects the data of all the sensing nodes (wireless sensor network nodes), preprocessing the data, extracting agricultural conditions, and completing data transmission in a high-speed communication channel; i.e., high-speed transmission of data to a remote server.
Example 2
As shown in fig. 2, the agricultural condition acquisition edge server mobile robot scheduling system for burst tasks of the present embodiment includes a classification module 1, an abnormal data determination module 2, a processing module 3, a secondary determination module 4 and a driving module 5;
the classification module 1 is used for classifying abnormal agricultural condition data by an edge server through an intelligent algorithm;
the abnormal data determining module 2 is used for determining the number and the position information of abnormal data sensing nodes by the edge server;
the processing module 3 is used for primarily determining the number and the positions of the mobile robots needing the edge server and the coverable abnormal data sensing nodes by adopting a greedy algorithm;
the secondary determining module 4 is configured to secondarily determine the number of robots based on the bandwidth of the edge server mobile robot and the number information of the coverage nodes;
the driving module 5 is used for driving the edge service robot to enter a designated position to complete agricultural condition acquisition of the burst task.
Further, as shown in fig. 3, the classification module 1 includes an acquisition module 11, a decision module 12, and an emergency region determination module 13;
the acquisition module 11 is configured to aggregate acquired data, including sensing data, node ID and node location information, to a server by using a wireless sensor network deployed in a farmland environment;
the judging module 12 is configured to judge the node acquisition information according to the normal range interval or by adopting a support vector machine algorithm by using an edge server;
the emergency determining module 13 is configured to classify the nodes that are not in the normal range into a sensing abnormal data node set, and an area formed by the abnormal data node set is an emergency area.
Further, the processing procedure of the processing module 3 is as follows:
according to the node position, the communication radius of the mobile edge service node is converted into the problem of the least circle covering the most points, and then a greedy algorithm is adopted to solve the problem of the least mobile edge service node covering the most points, and the method comprises the following steps:
firstly, sorting all points according to ascending order of the abscissa;
taking out the point with the smallest abscissa, regarding the point as a point on the left half circumference, taking the point on the x axis which is d from the abscissa of the point as a circle center, taking d as a radius from the circle center as a circle, and then removing the point contained in the circle; then continuously selecting the point with the smallest abscissa among the rest points, repeating the above operation until all the points are included in the circle, wherein the circle is obtained at the moment, and the number of the circles is the optimal solution of the problem;
the points are sequenced according to the X axis to obtain a section which can cover the points on the X axis, and if the left section of the next point is larger than the current right section from the leftmost point, a new mobile edge server is needed; if the next right interval is smaller than the current right interval, the current right interval needs to be updated to be small because all points must be covered;
if the coordinates of the circle center of the communication circle of the edge robot are at the left side of the previous circle center coordinates, the previous circle center coordinates are discarded, and on the contrary, the circle center is indicated to be established.
Further, the secondary determining module 4 specifically includes:
if the data transmission time is less than the limit time, namely, the time limit condition is met;
if the data transmission time is limited by university, namely the time limiting condition is not met; then adding an edge robot and repeating the steps until the number of the mobile nodes is increased to meet the time limit condition.
Specific implementation of each module in this embodiment may be referred to embodiment 1 above, and will not be described in detail herein; it should be noted that, in the system provided in this embodiment, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be performed by different functional modules according to needs, that is, the internal structure is divided into different functional modules to perform all or part of the functions described above.
The above examples are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above examples, and any other changes, modifications, substitutions, combinations, and simplifications that do not depart from the spirit and principle of the present invention should be made in the equivalent manner, and the embodiments are included in the protection scope of the present invention.
Claims (10)
1. The method for dispatching the mobile robot of the agricultural condition acquisition edge server of the burst task is characterized by comprising the following steps:
the edge server classifies abnormal agricultural condition data by adopting an intelligent algorithm;
the edge server determines the number and the position information of abnormal data sensing nodes;
adopting a greedy algorithm to primarily determine the number and positions of the mobile robots needing the edge server and the sensing nodes capable of covering abnormal data;
based on the bandwidth of the mobile robot of the edge server and the number information of the coverable nodes, secondarily determining the number of the robots;
driving the edge service mobile robot to enter a designated position;
and (5) completing agricultural condition acquisition of the burst task.
2. The method for dispatching the mobile robot for the agricultural condition acquisition edge server for the burst task according to claim 1, wherein the classification of the abnormal agricultural condition data is specifically as follows:
the wireless sensor network deployed in the farmland environment gathers the collected data to the server, and the collected data comprises sensing data, node ID and node position information;
the edge server judges the information collected by the nodes according to the normal range interval or by adopting a support vector machine algorithm;
and classifying the nodes which are not in the normal range into a sensing abnormal data node set, and classifying the abnormal data node set into an area which is formed by the abnormal data node set as an emergency area.
3. The method for dispatching the mobile robots of the edge servers for acquiring the agricultural conditions of the sudden tasks according to claim 1, wherein the method for dispatching the mobile robots of the edge servers for initially determining the number and the positions of the robots of the edge servers to be moved and the node capable of covering abnormal data by adopting a greedy algorithm is specifically as follows:
according to the node position, the communication radius of the mobile edge service node is converted into the problem of the least circle covering the most points, and then a greedy algorithm is adopted to solve the problem of the least mobile edge service node covering the most points, and the method comprises the following steps:
firstly, sorting all points according to ascending order of the abscissa;
taking out the point with the smallest abscissa, regarding the point as a point on the left half circumference, taking the point on the x axis which is d from the abscissa of the point as a circle center, taking d as a radius from the circle center as a circle, and then removing the point contained in the circle; then continuously selecting the point with the smallest abscissa among the rest points, repeating the above operation until all the points are included in the circle, wherein the circle is obtained at the moment, and the number of the circles is the optimal solution of the problem;
the points are sequenced according to the X axis to obtain a section which can cover the points on the X axis, and if the left section of the next point is larger than the current right section from the leftmost point, a new mobile edge server is needed; if the next right interval is smaller than the current right interval, the current right interval needs to be updated to be small because all points must be covered;
if the coordinates of the circle center of the communication circle of the edge server are at the left side of the coordinates of the previous circle center, the coordinates of the previous circle center are discarded, otherwise, the circle center is indicated to be established, by the method, the circle can cover surrounding points as much as possible, the local is optimal, and the global optimal is satisfied by repeating each operation.
4. The method for dispatching the mobile robot of the edge server for acquiring the agricultural condition of the sudden task according to claim 1, wherein the number of the robots is determined secondarily based on the bandwidth and the number information of the coverable nodes of the mobile robot of the edge server, specifically:
if the data transmission time is less than the limit time, namely, the time limit condition is met;
if the data transmission time is limited by university, namely the time limiting condition is not met; then adding an edge robot and repeating the steps until the number of the mobile nodes is increased to meet the time limit condition.
5. The method for dispatching the mobile robots of the edge server for acquiring the agricultural condition of the sudden task according to claim 1, wherein the step of determining the number of the mobile robots of the edge server is specifically:
and the cloud server solves the number k of the mobile robots participating in the burst edge server according to the perceived scale of the burst task agriculture condition data, the data volume and the bearing scale of the mobile robots of the edge server.
6. The method for dispatching the mobile robot for acquiring the agricultural condition of the sudden task by using the edge server according to claim 1, wherein the step of determining the position of the edge server by using a gravity center method is specifically as follows:
clustering the sensing areas according to the positions of wireless sensing nodes and the data quantity to be transmitted, and dividing the sensing areas into k sub-areas, wherein the sensing areas are areas formed by sensing nodes participating in burst tasks;
then, constructing a polygon for a certain sub-region according to the position of the sensing node, and acquiring the working position of the edge server mobile robot by taking the gravity center position of the polygon as the agricultural condition.
7. The method for dispatching the mobile robot of the edge server for acquiring the agricultural condition of the sudden task according to claim 6, wherein after the mobile robot of the edge server enters a preset position, information M1 added into the corresponding subarea is broadcast firstly, and after surrounding sensing nodes receive the information M1, determining information M2 added into the corresponding subarea is sent;
after networking is completed, the wireless sensor network node transmits data to the edge server mobile robot R through a communication network;
after the R collects the data of all the sensing nodes, preprocessing the data, extracting the agriculture condition, and then completing the data transmission in a high-speed communication channel.
8. The agricultural condition acquisition edge server mobile robot scheduling system for the sudden task is characterized by comprising a classification module, an abnormal data determination module, a processing module, a secondary determination module and a driving module;
the classification module is used for classifying abnormal agricultural condition data by the edge server through an intelligent algorithm;
the abnormal data determining module is used for determining the number and the position information of abnormal data sensing nodes by the edge server;
the processing module is used for primarily determining the number and the positions of the mobile robots needing the edge server and the coverable abnormal data sensing nodes by adopting a greedy algorithm;
the secondary determining module is used for secondarily determining the number of the robots based on the bandwidth of the edge server mobile robot and the number information of the coverable nodes;
the driving module is used for driving the edge server mobile robot to enter a designated position to complete agricultural condition acquisition of the burst task.
9. The agricultural condition acquisition edge server mobile robot scheduling system for sudden tasks according to claim 8, wherein the classification module comprises an acquisition module, a decision module and a sudden event area determination module;
the acquisition module is used for gathering acquired data to a server by a wireless sensor network deployed in a farmland environment, wherein the acquired data comprises sensing data, node ID and node position information;
the judging module is used for judging the node acquisition information according to the normal range interval or by adopting a support vector machine algorithm by the edge server;
the emergency region determining module is used for classifying the nodes which are not in the normal range into a sensing abnormal data node set and a region formed by the abnormal data node set, wherein the sensing abnormal data node set is an emergency region.
10. The agricultural condition acquisition edge server mobile robot scheduling system for sudden tasks according to claim 8, wherein the secondary determining module specifically comprises:
if the data transmission time is less than the limit time, namely, the time limit condition is met;
if the data transmission time is limited by university, namely the time limiting condition is not met; then adding an edge robot and repeating the steps until the number of the mobile nodes is increased to meet the time limit condition.
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