CN109768968B - Data informatization acquisition and analysis system and method based on cloud computing - Google Patents
Data informatization acquisition and analysis system and method based on cloud computing Download PDFInfo
- Publication number
- CN109768968B CN109768968B CN201811557227.0A CN201811557227A CN109768968B CN 109768968 B CN109768968 B CN 109768968B CN 201811557227 A CN201811557227 A CN 201811557227A CN 109768968 B CN109768968 B CN 109768968B
- Authority
- CN
- China
- Prior art keywords
- data
- cluster
- cluster head
- node
- cloud computing
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Mobile Radio Communication Systems (AREA)
- Arrangements For Transmission Of Measured Signals (AREA)
Abstract
The invention provides a data informatization acquisition and analysis system and method based on cloud computing, wherein the system comprises a wireless sensor network module, a cloud computing platform and local equipment, and the method comprises the following steps: the cloud computing platform receives and stores data which are collected in real time and sent in time by the wireless sensor network module; the cloud computing platform receives login key information sent by local equipment, matches the login key information with login key information stored in advance, and establishes communication connection with the local equipment when matching is successful; and the cloud computing platform performs anomaly analysis on the received data, and when the received data is abnormal, the abnormal data is sent to local equipment which establishes communication with the local equipment, so that the abnormal data is presented through a human-computer interface of the local equipment.
Description
Technical Field
The invention relates to the technical field of data management and control, in particular to a data informatization acquisition and analysis system and method based on cloud computing.
Background
With the development of science and technology, early manual monitoring is basically eliminated, a traditional method is to send people to handheld detection equipment in each monitoring area for monitoring, and input acquired data into a related system, the monitoring method is low in efficiency and high in cost, and a user cannot acquire required data in real time.
With the development of computer technology and wireless sensor network technology, a possible method and means are provided for wireless monitoring in a wide area. The wireless sensor network is a network formed by a large number of wireless sensor nodes in a self-organizing mode, has the characteristics of high sensor node density, frequent network topology change, limited node power, computing capacity and data storage capacity and the like, and has wide application prospects in the fields of environmental monitoring military, medical health, household intelligent monitoring and other commercial fields. However, the existing wireless sensor network still has more defects due to the limited energy of the sensor nodes.
Disclosure of Invention
In order to solve the problems, the invention provides a data informatization acquisition and analysis system and method based on cloud computing.
The purpose of the invention is realized by adopting the following technical scheme:
the embodiment of the first aspect of the invention provides a cloud computing-based data informatization acquisition and analysis system, which comprises a wireless sensor network module, a cloud computing platform and local equipment, wherein the wireless sensor network module is used for acquiring data in real time and transmitting the acquired data to the cloud computing platform in time;
the cloud computing platform comprises a cloud storage module, a data management module and a data analysis module, wherein the cloud storage module is used for storing data received from the wireless sensor network module and login key information of the local equipment, and the data management module is used for managing the received data and the login key information;
the data analysis module establishes communication connection with the local equipment when login key information sent by the local equipment is matched with login key information in the cloud storage module;
the data analysis module is used for carrying out abnormity analysis on the received data, and when the received data is abnormal, the data analysis module sends the abnormal data to local equipment which establishes communication with the local equipment so as to display the abnormal data through a human-computer interface of the local equipment;
the wireless sensor network module comprises a single aggregation node, a plurality of sensor nodes and a plurality of cluster heads, each sensor node selects the cluster head closest to the sensor node to join in a cluster, and the cloud computing platform is in data communication with the aggregation node; the method comprises the steps that a sensor collects data and sends the data to a cluster head of a cluster where the sensor is located, the cluster head collects the data sent by each sensor node in the cluster, when the distance between the cluster head and a sink node is smaller than a set distance threshold value, the cluster head selects a direct communication mode to communicate with the sink node, and otherwise, an indirect communication mode is selected to communicate with the sink node; the direct communication is that the cluster head directly sends the collected data to the sink node, and the indirect communication is that the cluster head sends the collected data to the next hop node, so that the next hop node forwards the collected data until the collected data is sent to the sink node.
In an implementation manner of the embodiment of the first aspect of the present invention, the managing the received data includes checking, modifying, and/or adding data in the cloud storage module.
In a manner that can be achieved by the embodiment of the first aspect of the present invention, the data analysis module is further configured to: responding to an access request of local equipment which establishes communication connection with the local equipment, and providing an operation interface of stored data to the local equipment;
and the data analysis module responds to the operation of the local equipment based on the operation interface.
In a manner that can be realized by the embodiment of the first aspect of the present invention, the login key information includes a key and identification information of an identity card of an owner of the key.
The embodiment of the second aspect of the invention provides a data informatization acquisition and analysis method based on cloud computing, which comprises the following steps:
the cloud computing platform receives and stores data which are collected in real time and sent in time by the wireless sensor network module;
the cloud computing platform receives login key information sent by local equipment, matches the login key information with login key information stored in advance, and establishes communication connection with the local equipment when matching is successful;
the cloud computing platform performs anomaly analysis on the received data, and when the received data is abnormal, the abnormal data is sent to local equipment which establishes communication with the cloud computing platform, so that the abnormal data is presented through a human-computer interface of the local equipment;
the wireless sensor network module comprises a single aggregation node, a plurality of sensor nodes and a plurality of cluster heads, each sensor node selects the cluster head closest to the sensor node to join in a cluster, and the cloud computing platform is in data communication with the aggregation node; the method comprises the steps that a sensor collects data and sends the data to a cluster head of a cluster where the sensor is located, the cluster head collects the data sent by each sensor node in the cluster, when the distance between the cluster head and a sink node is smaller than a set distance threshold value, the cluster head selects a direct communication mode to communicate with the sink node, and otherwise, an indirect communication mode is selected to communicate with the sink node; the direct communication is that the cluster head directly sends the collected data to the sink node, and the indirect communication is that the cluster head sends the collected data to the next hop node, so that the next hop node forwards the collected data until the collected data is sent to the sink node.
In an implementation manner of the embodiment of the second aspect of the present invention, the cloud computing platform further manages the stored data and the login key information, and the management of the data includes viewing, modifying and/or adding the stored data.
In an implementation manner of the embodiment of the second aspect of the present invention, after establishing a communication connection with the local device, the cloud computing platform further provides an operation interface of stored data to the local device in response to an access request of the local device with which the communication connection is established;
and the cloud computing platform responds to the operation of the local equipment based on the operation interface.
The embodiment of the invention is based on the wireless sensor network and the cloud computing technology, realizes the wireless communication of data and the real-time processing of the data, does not need wiring, and saves manpower and material resources; through the interaction of the data analysis module and the local equipment, the data required by the user can be more effectively presented to the user in real time; the account information of the local equipment is verified, so that the data privacy is protected.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a block diagram schematically illustrating a structure of a cloud computing-based data information collection and analysis system according to an exemplary embodiment of the present invention;
fig. 2 is a flowchart illustrating a cloud computing-based data information collection and analysis system method according to an exemplary embodiment of the present invention.
Reference numerals:
the system comprises a wireless sensor network module 1, a cloud computing platform 2 and local equipment 3.
Detailed Description
The invention is further described with reference to the following examples.
Referring to fig. 1, an embodiment of a first aspect of the present invention provides a data informatization acquisition and analysis system based on cloud computing, where the system includes a wireless sensor network module 1, a cloud computing platform 2, and a local device 3, where the wireless sensor network module 1 is configured to acquire data in real time and transmit the acquired data to the cloud computing platform 2 in time;
the cloud computing platform 2 comprises a cloud storage module, a data management module and a data analysis module, wherein the cloud storage module is used for storing data received from the wireless sensor network module 1 and login key information of the local device 3, and the data management module is used for managing the received data and the login key information;
the data analysis module establishes communication connection with the local device 3 when the login key information sent by the local device 3 is matched with the login key information in the cloud storage module;
the data analysis module is used for carrying out abnormity analysis on the received data, and when the received data is abnormal, the data analysis module sends the abnormal data to the local equipment 3 which establishes communication with the data analysis module, so that the abnormal data is presented through a human-computer interface of the local equipment 3;
the wireless sensor network module 1 comprises a single aggregation node, a plurality of sensor nodes and a plurality of cluster heads, each sensor node selects the cluster head closest to the sensor node to join in a cluster, and the cloud computing platform 2 is in data communication with the aggregation node; the method comprises the steps that a sensor collects data and sends the data to a cluster head of a cluster where the sensor is located, the cluster head collects the data sent by each sensor node in the cluster, when the distance between the cluster head and a sink node is smaller than a set distance threshold value, the cluster head selects a direct communication mode to communicate with the sink node, and otherwise, an indirect communication mode is selected to communicate with the sink node; the direct communication is that the cluster head directly sends the collected data to the sink node, and the indirect communication is that the cluster head sends the collected data to the next hop node, so that the next hop node forwards the collected data until the collected data is sent to the sink node.
In an implementation manner of the embodiment of the first aspect of the present invention, the managing the received data includes checking, modifying, and/or adding data in the cloud storage module.
In a manner that can be achieved by the embodiment of the first aspect of the present invention, the data analysis module is further configured to: responding to an access request of a local device 3 which establishes communication connection with the local device, and providing an operation interface of stored data to the local device 3;
and the data analysis module responds to the operation of the local equipment 3 based on the operation interface.
In a manner that can be realized by the embodiment of the first aspect of the present invention, the login key information includes a key and identification information of an identity card of an owner of the key.
As shown in fig. 2, a second aspect embodiment of the present invention provides a data informatization acquisition and analysis method based on cloud computing, where the method includes:
the S01 cloud computing platform 2 receives and stores data collected by the wireless sensor network module 1 in real time and sent in time.
S02, the cloud computing platform 2 receives the login key information sent by the local device 3, matches the login key information with the login key information stored in advance, and establishes a communication connection with the local device 3 when the matching is successful.
S03, the cloud computing platform 2 performs an anomaly analysis on the received data, and when the received data is abnormal, sends the abnormal data to the local device 3 that establishes communication with the received data, so as to present the abnormal data through a human-computer interface of the local device 3.
The wireless sensor network module 1 comprises a single aggregation node, a plurality of sensor nodes and a plurality of cluster heads, each sensor node selects the cluster head closest to the sensor node to join in a cluster, and the cloud computing platform 2 is in data communication with the aggregation node; the method comprises the steps that a sensor collects data and sends the data to a cluster head of a cluster where the sensor is located, the cluster head collects the data sent by each sensor node in the cluster, when the distance between the cluster head and a sink node is smaller than a set distance threshold value, the cluster head selects a direct communication mode to communicate with the sink node, and otherwise, an indirect communication mode is selected to communicate with the sink node; the direct communication is that the cluster head directly sends the collected data to the sink node, and the indirect communication is that the cluster head sends the collected data to the next hop node, so that the next hop node forwards the collected data until the collected data is sent to the sink node.
In a manner that can be realized by the embodiment of the second aspect of the present invention, the cloud computing platform 2 further manages the stored data and the login key information, and the management of the data includes viewing, modifying and/or adding the stored data.
In an implementation manner of the embodiment of the second aspect of the present invention, after establishing the communication connection with the local device 3, the cloud computing platform 2 further provides an operation interface of the stored data to the local device 3 in response to an access request of the local device 3 with which the communication connection is established;
the cloud computing platform 2 responds to the operation of the local device 3 based on the operation interface.
The embodiment of the invention is based on the wireless sensor network and the cloud computing technology, realizes the wireless communication of data and the real-time processing of the data, does not need wiring, and saves manpower and material resources; through the interaction of the data analysis module and the local device 3, the data required by the user can be more effectively presented to the user in real time; the account information of the local device 3 is verified, so that the data privacy is protected.
In the cloud computing-based data information acquisition and analysis system and method according to the above embodiments, initially, a cluster head performs information interaction with each sensor node in a cluster thereof, constructs a cluster sensor node list, calculates a first similarity with each sensor node in the cluster, and stores the first similarity to a corresponding position in the cluster sensor node list, where a calculation formula of the first similarity is:
in the formula, CxjIs the first similarity of the cluster head x and the sensor node y in the cluster, NxNumber of sensor nodes including cluster head in x communication range of cluster head, NyThe number of sensor nodes including cluster heads in the communication range of the sensor node y, D (x, y) is the distance between the cluster head x and the sensor node y, Dx,maxThe distance between the cluster head x and the sensor node farthest from the cluster head x is α a preset influence factor based on communication range crossing, and the value range of α is [0.4,0.5 ]]β is a preset distance-based influence factor, β has a value range of [0.3,0.4 ]]。
When the residual energy of the cluster head is lower than the preset energy lower limit, the cluster head acquires the current residual energy information of each sensor node in the cluster, calculates the corresponding average energy value, and sends a request to the sensor node with the maximum first similarity in the sensor nodes with the current residual energy higher than the average energy value, so that the sensor node with the maximum first similarity becomes a successor cluster head, and the sensor node changes roles to become the sensor nodes in the cluster.
The embodiment proposes a rotation mechanism of cluster heads, in which an index of a first similarity is proposed. In the embodiment, the cluster head obtains the first similarity with each sensor node in the cluster in advance according to a calculation formula of the first similarity, so that a data basis is provided for selecting the relay cluster head when the energy of the cluster head is too low, and the efficiency of selecting the relay cluster head by the cluster head is improved; when the residual energy of the cluster head is lower than the preset energy lower limit, the cluster head acquires the current residual energy information of each sensor node in the cluster, calculates the corresponding average energy value, and sends a request to the sensor node with the maximum first similarity in the sensor nodes with the current residual energy higher than the average energy value, so that the sensor node with the maximum first similarity becomes a successor cluster head, the successor cluster head can better take the role of the original cluster head, the stability of the cluster is favorably maintained, and the adverse effect of the cluster head rotation on data collection is reduced.
In one embodiment, the cluster head initially performs information interaction with each neighboring cluster head, that is, other cluster heads within the communication range, constructs a neighboring cluster head list, calculates a second similarity with each neighboring cluster head, and stores the second similarity to a corresponding position in the neighboring cluster head list, where the calculation formula of the second similarity is:
in the formula, CxjIs the second similarity of cluster head x and its neighbor cluster head j, MxNumber of neighbor cluster heads, M, for cluster head xjNumber of neighbor cluster heads, M, of the neighbor cluster head jx∩MjA number of neighbor cluster heads, m, common to the cluster head x and the neighbor cluster head jxNumber of sensor nodes m not including cluster head in x communication range of cluster headjThe number of sensor nodes m not including cluster head in the communication range of the neighbor cluster head jx∩mjThe number of sensor nodes, rho, not including cluster head in the communication range shared by the cluster head x and the neighbor cluster head j1、ρ2Is a preset weight coefficient and p1+ρ21 is ═ 1; d (x, j) is the distance between the cluster head x and the neighbor cluster head j, Dx,maxIs the distance between the cluster head x and the farthest neighbor cluster headAnd α is a preset influence factor based on communication range crossing, and α is a value range of [0.4,0.5 ]]β is a preset distance-based influence factor, β has a value range of [0.3,0.4 ]]；
When the cluster head selects the next hop node, the following steps are specifically executed:
(1) the cluster head takes a neighbor cluster head which is closer to the sink node relative to the cluster head as a candidate node;
(2) the sensor node is according to a set period delta T1Periodically, the own selection distance is determined according to the following formula:
in the formula, CHOOSExSelecting a distance, E, for a cluster head xx0Is the initial energy of the cluster head x, ExTheta is the current residual energy of the cluster head x and is a preset energy consumption influence factor, and the value range of 0 is [0.4,0.6 ]]，RxA communication distance of cluster head x;
(3) and selecting the neighbor cluster head with the minimum second similarity as the next hop node from the candidate nodes with the distances to the cluster heads smaller than the current selection distance.
Wherein the selection distance is less than RxAnd at the time of/3, stopping updating the selection distance.
The embodiment proposes a mechanism for selecting a next hop node by cluster heads, wherein a calculation formula of a second similarity of nodes is further proposed according to communication range crossing and distance factors, and the second similarity can represent the social relevance of two cluster heads. In the mechanism, a cluster head takes a neighbor cluster head which is closer to a sink node relative to the cluster head as a candidate node of a next hop node, so that the directional transmission of data to the sink node is ensured; the cluster head selects the neighbor cluster head with the minimum second similarity as the next hop node from the candidate nodes with the distance to the cluster head smaller than the current selection distance, so that the cluster head can select the next hop node with the proper distance according to the energy condition of the cluster head, the data can be reliably forwarded to the next hop node, and the cluster head can select the neighbor cluster head which is not associated with the cluster head as much as possible, the data collision is reduced, and the efficiency of sending the data to the sink node is improved.
In one embodiment, the next hop node is Δ T every other period2Judging the energy condition of the node, if the following energy conditions are met, the next hop node sends early warning information to all the previous hop cluster heads of the node, and the sensor node receiving the early warning information is prompted to reselect the next hop node:
in the formula, ElIs the current remaining energy of the next hop node l, El0Is the initial energy, τ, of the next hop node llThe number of times that the next hop node l has judged its own energy situation so far, EminIs a preset minimum energy value.
The embodiment provides a feedback early warning mechanism of a next hop node, wherein an energy condition for judging the energy condition of the next hop node per other period delta T is set innovatively. When the energy condition of the next hop node is determined, not only the current residual energy of the next hop node is considered, but also the energy which can be consumed by the next hop node in a period, namely the time delay of energy consumption, is considered, so that the determination of the energy condition of the next hop node is more robust and accurate. In this embodiment, when the next hop node meets the energy condition, the next hop node sends the warning information to the previous hop cluster head, so that the sensor node receiving the warning information reselects the next hop node, which is beneficial to reducing the probability of packet loss of the next hop node due to insufficient energy, thereby improving the reliability and efficiency of data communication, and also beneficial to balancing the load of each cluster head, and prolonging the service life of the wireless sensor network.
It will be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the system is divided into different functional modules to perform all or part of the above described functions. For the specific working process of the system and the terminal described above, reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
From the above description of embodiments, it is clear for a person skilled in the art that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For a hardware implementation, the processor may be implemented in one or more of the following sub-modules: an application specific integrated circuit, a digital signal processor, a digital signal processing system, a programmable logic device, a field programmable gate array, a processor, a controller, a microcontroller, a microprocessor, other electronic sub-modules designed to perform the functions described herein, or a combination thereof. For a software implementation, some or all of the procedures of an embodiment may be performed by a computer program instructing associated hardware. In practice, the program may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. The computer-readable medium can include, but is not limited to, random access memory, read only memory images, electrically erasable programmable read only memory or other optical disk storage, magnetic disk storage media or other magnetic storage systems, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (7)
1. A data informatization acquisition and analysis system based on cloud computing is characterized by comprising a wireless sensor network module, a cloud computing platform and local equipment, wherein the wireless sensor network module is used for acquiring data in real time and transmitting the acquired data to the cloud computing platform in time;
the cloud computing platform comprises a cloud storage module, a data management module and a data analysis module, wherein the cloud storage module is used for storing data received from the wireless sensor network module and login key information of the local equipment, and the data management module is used for managing the received data and the login key information;
the data analysis module establishes communication connection with the local equipment when login key information sent by the local equipment is matched with login key information in the cloud storage module;
the data analysis module is used for carrying out abnormity analysis on the received data, and when the received data is abnormal, the data analysis module sends the abnormal data to local equipment which establishes communication with the local equipment so as to display the abnormal data through a human-computer interface of the local equipment;
the wireless sensor network module comprises a single aggregation node, a plurality of sensor nodes and a plurality of cluster heads, each sensor node selects the cluster head closest to the sensor node to join in a cluster, and the cloud computing platform is in data communication with the aggregation node; the method comprises the steps that a sensor collects data and sends the data to a cluster head of a cluster where the sensor is located, the cluster head collects the data sent by each sensor node in the cluster, when the distance between the cluster head and a sink node is smaller than a set distance threshold value, the cluster head selects a direct communication mode to communicate with the sink node, and otherwise, an indirect communication mode is selected to communicate with the sink node; the direct communication is that the cluster head directly sends the collected data to the sink node, and the indirect communication is that the cluster head sends the collected data to the next hop node so that the next hop node forwards the collected data until the collected data is sent to the sink node; initially, a cluster head performs information interaction with each sensor node in a cluster to construct a sensor node list in the cluster, calculates a first similarity with each sensor node in the cluster, and stores the first similarity to a corresponding position in the sensor node list in the cluster, wherein a calculation formula of the first similarity is as follows:
in the formula, CxyIs the first similarity of the cluster head x and the sensor node y in the cluster, NxNumber of sensor nodes including cluster head in x communication range of cluster head, NyThe number of sensor nodes including cluster heads in the communication range of the sensor node y, D (x, y) is the distance between the cluster head x and the sensor node y, Dx,maxThe distance between the cluster head x and the sensor node farthest from the cluster head x is α a preset influence factor based on communication range crossing, and the value range of α is [0.4,0.5 ]]β is a preset distance-based influence factor, β has a value range of [0.3,0.4 ]]；
When the residual energy of the cluster head is lower than the preset energy lower limit, the cluster head acquires the current residual energy information of each sensor node in the cluster, calculates the corresponding average energy value, and sends a request to the sensor node with the maximum first similarity in the sensor nodes with the current residual energy higher than the average energy value, so that the sensor node with the maximum first similarity becomes a successor cluster head, and the sensor node changes roles to become the sensor nodes in the cluster.
2. The cloud computing-based data informatization acquisition and analysis system of claim 1, wherein the management of the received data includes viewing, modifying and/or adding data in cloud storage modules.
3. The cloud computing-based data informatization acquisition and analysis system of claim 1, wherein the data analysis module is further configured to: responding to an access request of local equipment which establishes communication connection with the local equipment, and providing an operation interface of stored data to the local equipment;
and the data analysis module responds to the operation of the local equipment based on the operation interface.
4. The cloud-computing-based data informatization acquisition and analysis system of claim 1, wherein the login key information includes a key and identification card identification information of the key owner.
5. A data informatization acquisition and analysis method based on cloud computing is characterized by comprising the following steps:
the cloud computing platform receives and stores data which are collected in real time and sent in time by the wireless sensor network module;
the cloud computing platform receives login key information sent by local equipment, matches the login key information with login key information stored in advance, and establishes communication connection with the local equipment when matching is successful;
the cloud computing platform performs anomaly analysis on the received data, and when the received data is abnormal, the abnormal data is sent to local equipment which establishes communication with the cloud computing platform, so that the abnormal data is presented through a human-computer interface of the local equipment;
the wireless sensor network module comprises a single aggregation node, a plurality of sensor nodes and a plurality of cluster heads, each sensor node selects the cluster head closest to the sensor node to join in a cluster, and the cloud computing platform is in data communication with the aggregation node; the method comprises the steps that a sensor collects data and sends the data to a cluster head of a cluster where the sensor is located, the cluster head collects the data sent by each sensor node in the cluster, when the distance between the cluster head and a sink node is smaller than a set distance threshold value, the cluster head selects a direct communication mode to communicate with the sink node, and otherwise, an indirect communication mode is selected to communicate with the sink node; the direct communication is that the cluster head directly sends the collected data to the sink node, and the indirect communication is that the cluster head sends the collected data to the next hop node so that the next hop node forwards the collected data until the collected data is sent to the sink node; initially, a cluster head performs information interaction with each sensor node in a cluster to construct a sensor node list in the cluster, calculates a first similarity with each sensor node in the cluster, and stores the first similarity to a corresponding position in the sensor node list in the cluster, wherein a calculation formula of the first similarity is as follows:
in the formula, CxyIs the first similarity of the cluster head x and the sensor node y in the cluster, NxNumber of sensor nodes including cluster head in x communication range of cluster head, NyThe number of sensor nodes including cluster heads in the communication range of the sensor node y, D (x, y) is the distance between the cluster head x and the sensor node y, Dx,maxThe distance between the cluster head x and the sensor node farthest from the cluster head x is α a preset influence factor based on communication range crossing, and the value range of α is [0.4,0.5 ]]β is a preset distance-based influence factor, β has a value range of [0.3,0.4 ]]；
When the residual energy of the cluster head is lower than the preset energy lower limit, the cluster head acquires the current residual energy information of each sensor node in the cluster, calculates the corresponding average energy value, and sends a request to the sensor node with the maximum first similarity in the sensor nodes with the current residual energy higher than the average energy value, so that the sensor node with the maximum first similarity becomes a successor cluster head, and the sensor node changes roles to become the sensor nodes in the cluster.
6. The cloud computing-based data informatization acquisition and analysis method according to claim 5, wherein the cloud computing platform further manages the stored data and the login key information, and the management of the data comprises viewing, modifying and/or adding the stored data.
7. The method for the informationized data acquisition and analysis based on the cloud computing as claimed in claim 5, wherein after the communication connection with the local device is established, the cloud computing platform further provides an operation interface of the stored data to the local device in response to an access request of the local device which is in communication connection with the cloud computing platform;
and the cloud computing platform responds to the operation of the local equipment based on the operation interface.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811557227.0A CN109768968B (en) | 2018-12-19 | 2018-12-19 | Data informatization acquisition and analysis system and method based on cloud computing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811557227.0A CN109768968B (en) | 2018-12-19 | 2018-12-19 | Data informatization acquisition and analysis system and method based on cloud computing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109768968A CN109768968A (en) | 2019-05-17 |
| CN109768968B true CN109768968B (en) | 2020-07-31 |
Family
ID=66450319
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811557227.0A Active CN109768968B (en) | 2018-12-19 | 2018-12-19 | Data informatization acquisition and analysis system and method based on cloud computing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109768968B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118174437A (en) * | 2023-12-19 | 2024-06-11 | 连云港微科电力科技有限公司 | Real-time monitoring system for electric power information |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101516099A (en) * | 2009-04-07 | 2009-08-26 | 华中科技大学 | Test method for sensor network anomaly |
| CN105848241A (en) * | 2016-03-21 | 2016-08-10 | 广州供电局有限公司 | Clustering method and system of mobile ad hoc network |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7562123B2 (en) * | 2003-09-05 | 2009-07-14 | Palo Alto Research Center Incorporated | Systems and methods for distributed group formation and maintenance in geographically based networks |
| CN107134153A (en) * | 2017-05-15 | 2017-09-05 | 深圳众厉电力科技有限公司 | Magnitude of traffic flow acquisition system based on wireless sensor network |
| CN108965409B (en) * | 2018-07-02 | 2021-05-04 | 浙江天演维真网络科技股份有限公司 | Intelligent real-time air quality monitoring system |
-
2018
- 2018-12-19 CN CN201811557227.0A patent/CN109768968B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101516099A (en) * | 2009-04-07 | 2009-08-26 | 华中科技大学 | Test method for sensor network anomaly |
| CN105848241A (en) * | 2016-03-21 | 2016-08-10 | 广州供电局有限公司 | Clustering method and system of mobile ad hoc network |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109768968A (en) | 2019-05-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11513583B2 (en) | Methods and systems for managing machine learning involving mobile devices | |
| US11425628B2 (en) | Method and system for achieving auto adaptive clustering in a sensor network | |
| US8655975B2 (en) | Home appliance managing system | |
| Alipour-Fanid et al. | Machine learning-based delay-aware UAV detection over encrypted Wi-Fi traffic | |
| CN111031585B (en) | Dormancy control method, device, storage medium and server | |
| CN112365219A (en) | Order processing method and device, storage medium and electronic equipment | |
| CN110784903A (en) | Network data transmission method and device, computer equipment and storage medium | |
| CN112187859A (en) | Method for dynamically mapping Internet of things service and edge network capability and electronic equipment | |
| CN107682241A (en) | A kind of intelligent home device control system based on cloud computing | |
| CN109361708A (en) | Data informationization acquisition, management and analysis system and method | |
| CN109768968B (en) | Data informatization acquisition and analysis system and method based on cloud computing | |
| JP5655192B2 (en) | Control device | |
| CN109257720B (en) | Data acquisition system based on cloud computing | |
| Liu et al. | Joint resource allocation optimization of wireless sensor network based on edge computing | |
| CN116582910B (en) | Digital information transmission method and system | |
| WO2020073555A1 (en) | Paging method and apparatus, equipment, and storage medium | |
| CN109890000B (en) | Internet of things system architecture and data communication method | |
| CN109714435B (en) | Cloud platform video collecting and processing system and method thereof | |
| CN109922449B (en) | Data informatization acquisition, management and analysis system and method | |
| CN109922453B (en) | Safety precaution analysis alarm system and method based on artificial intelligence | |
| Su et al. | Unknown tag identification protocol based on collision slot resolution in large-scale and battery-less RFID system | |
| CN109640327B (en) | Data communication method and device based on Internet of things | |
| CN107566974A (en) | A kind of agricultural product accumulating intelligent monitor system | |
| CN109885116B (en) | Internet of things platform monitoring system and method based on cloud computing | |
| CN109862314B (en) | Video image acquisition and processing system and method thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20200710 Address after: 215000 19 / F, No.99, nantiancheng Road, high speed rail new town, Suzhou, Jiangsu Province Applicant after: Ziguang cloud engine technology (Suzhou) Co., Ltd Address before: Room 601-A42, 88 Nantiancheng Road, Xiangcheng High-speed Railway New Town, Suzhou City, Jiangsu Province Applicant before: SUZHOU MAIRONGXIANG INFORMATION TECHNOLOGY Co.,Ltd. |