CN114666766A - Internet of things gateway communication load sharing method and system - Google Patents
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Abstract
The invention relates to the technical field of artificial intelligence, in particular to a gateway communication load sharing method and system of the Internet of things, wherein the method comprises the steps of firstly collecting the strength of a received signal between every two gateways to obtain the interference degree of the corresponding gateway; obtaining a communication load according to the size and the interference degree of a data packet transmitted between gateways; and calculating the idle power of any gateway. Obtaining a gateway distance index between gateways according to the communication load and the vacant power between the gateways; obtaining an index error rate of the gateway according to the similarity of the flight speeds between the unmanned aerial vehicles; and obtaining the matching path distance according to the index error rate and the gateway distance index. Acquiring a plurality of data packets transmitted between gateways; and matching the matching path distance with the data packet to obtain the optimal path for transmitting the data packet. According to the invention, the optimal path for transmitting each data packet is obtained through the interference degree, the communication power and the idle power of each gateway, so that the stability of a communication network between unmanned aerial vehicles is improved and the communication energy consumption is reduced.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a method and a system for internet of things gateway communication load sharing.
Background
The communication mode of the unmanned aerial vehicle on the forest airspace is mainly radio communication, a local area network is established between the unmanned aerial vehicle and the unmanned aerial vehicle to carry out information transmission contact, various forest airspace communication services are guaranteed to be carried out smoothly, and the communication quality is greatly influenced by signal intensity and frequency.
At present, various devices and systems of a conventional unmanned aerial vehicle are usually relatively independent, a large amount of data is difficult to collect, analyze and share, meanwhile, because in the environment of aerial forestry measurement, no available operator network exists, that is, 2/3/4/5G network cannot be utilized to send out information of an Internet of things terminal, so that limitation is caused to the actual use of the Internet of things terminal device, a proper communication path is difficult to find when a gateway transmits information, the data communication network between the unmanned aerial vehicles is unstable, and the communication energy consumption is high.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a method and a system for internet of things gateway communication load sharing, and the adopted technical scheme is as follows:
in a first aspect, an embodiment of the present invention provides an internet of things gateway communication load sharing method, which is applied to communication between unmanned aerial vehicles, where a communication receiving and sending device of each unmanned aerial vehicle is a gateway in a local area network, and the method includes the following steps:
acquiring the received signal strength between every two gateways to obtain the interference degree of the corresponding gateway; acquiring the size of a data packet transmitted between gateways, and multiplying the size of the data packet by the interference degree to obtain a redundant load; adding the redundant load and the size of the data packet to obtain a communication load between the two gateways; calculating the vacant power of any gateway;
obtaining a gateway distance index between any two gateways according to the communication load and the vacant power between the two gateways; obtaining an index error rate of a gateway corresponding to the unmanned aerial vehicle according to the similarity of the flight speeds between the two unmanned aerial vehicles; weighting and summing the index error rate and the gateway distance index to obtain a matching path distance;
acquiring a plurality of data packets transmitted between two gateways; and matching the matching path distance with the data packets to obtain a plurality of optimal paths for data packet transmission.
Preferably, the calculating the idle power of any gateway includes:
acquiring rated power of each gateway; and the difference value between the rated power and the communication load is idle power.
Preferably, the obtaining of the gateway distance index between any two gateways according to the communication load and the idle power between the two gateways includes:
the calculation formula of the gateway distance index is as follows:
wherein,
is a gateway
And a gateway
The gateway distance index between;
is a gateway
And a gateway
The communication load between;
is a gateway
An empty load of (2);
is a gateway
Is empty of load.
Preferably, the obtaining of the index error rate of the gateway corresponding to the drone according to the similarity of the flying speeds between the two drones includes:
obtaining index error rates of gateways corresponding to the two unmanned aerial vehicles according to the cosine similarity of the flight speeds between the two unmanned aerial vehicles;
the calculation formula of the index error rate is as follows:
wherein,
is a gateway
And a gateway
A corresponding index error rate;
is a gateway
The corresponding flight speed of the unmanned aerial vehicle;
is a gateway
The corresponding flight speed of the unmanned aerial vehicle;
is a gateway
And a gateway
Cosine similarity of flying speed between two corresponding unmanned aerial vehicles.
Preferably, the weighted summation of the index error rate and the gateway distance index is to obtain a matching path distance, further comprising:
the transmission path of the data packet between the two gateways comprises: a direct transmission path and an indirect transmission path;
the indirect transmission path comprises a plurality of branch paths, and each branch path corresponds to two gateways; calculating the gateway distance index and the index error rate corresponding to each branch path, and weighting and summing the gateway distance indexes and the index error rates of a plurality of branch paths in the indirect transmission path to obtain the matching path distance of the indirect transmission path;
each direct transmission path corresponds to two gateways, and the product of the gateway distance index and the index error rate corresponding to the direct transmission path is calculated to be the matching path distance of the direct transmission path.
Preferably, the matching path distance with the data packet includes:
and matching the data packet with the matching path distance by utilizing a K-M algorithm.
Preferably, the acquiring the strength of the received signal between every two gateways to obtain the interference degree of the corresponding gateway includes:
the calculation formula of the interference degree is as follows:
wherein,
is a gateway
And a gateway
The corresponding interference degree between the two;
is a gateway
And a gateway
Corresponding received signal strength.
In a second aspect, an embodiment of the present invention provides an internet of things gateway communication offloading system, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the internet of things gateway communication offloading method when executing the computer program.
The embodiment of the invention at least has the following beneficial effects:
the embodiment of the invention utilizes the artificial intelligence technology, firstly collects the intensity of the received signal between every two gateways to obtain the interference degree of the corresponding gateway, and the interference degree can reflect the loss rate of the data packet so as to further determine the retransmission rate of the data packet. Acquiring the size of a data packet transmitted between gateways, and multiplying the size of the data packet by the interference degree to obtain a redundant load; adding the size of the redundant load and the size of the data packet to obtain a communication load between the two gateways; and calculating the idle power of any gateway. Obtaining a gateway distance index between two gateways according to the communication load and the vacant power between any two gateways, wherein the gateway distance index is reflected by the transmission efficiency of a data packet, and the higher the transmission efficiency is, the smaller the gateway distance index is, and the lower the transmission efficiency is, the larger the gateway distance index is; obtaining an index error rate of a gateway corresponding to the unmanned aerial vehicle according to the similarity of the flight speeds between the two unmanned aerial vehicles; and weighting and summing the index error rate and the gateway distance index to obtain the matching path distance. Acquiring a plurality of data packets transmitted between two gateways; and matching the distance of the matched path with the data packet to obtain an optimal path for transmitting a plurality of data packets, and selecting the most appropriate transmission path from the plurality of transmission paths. According to the method and the system, the optimal path for transmitting each data packet is obtained through the interference degree, the communication power and the idle power of each gateway, so that the stability of a communication network between the unmanned aerial vehicles is ensured, and the communication energy consumption is reduced.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a method for sharing communication load of an internet of things gateway according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating a step of obtaining a matching path distance of each transmission path according to an embodiment of the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention adopted to achieve the predetermined object, the following detailed description is provided with reference to the accompanying drawings and preferred embodiments for a method for offloading communication of an internet of things gateway according to the present invention, and the specific implementation, structure, features and effects thereof are described in detail. In the following description, different "one embodiment" or "another embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The embodiment of the invention provides a specific implementation method of an Internet of things gateway communication load sharing method and system, and the method is suitable for gateway communication scenes among aerial unmanned aerial vehicles. A plurality of unmanned aerial vehicles are arranged in each forest airspace, a local area network is constructed among the unmanned aerial vehicles, equipment for receiving and sending signals is installed on each unmanned aerial vehicle, and the signal sending and receiving equipment corresponding to each unmanned aerial vehicle serves as a gateway in the local area network. In order to solve the problems of unstable data communication network and high communication energy consumption between unmanned aerial vehicles, the embodiment of the invention obtains the optimal path for transmitting each data packet through the interference degree, the communication power and the idle power of each gateway, thereby achieving the purposes of stabilizing the communication network between the unmanned aerial vehicles and reducing the communication energy consumption.
The following describes a specific scheme of the internet of things gateway communication load sharing method provided by the invention in detail with reference to the accompanying drawings.
Referring to fig. 1, a flowchart illustrating steps of a method for offloading internet of things gateway communication according to an embodiment of the present invention is shown, where the method includes the following steps:
step S100, collecting the received signal strength between every two gateways to obtain the interference degree of the corresponding gateway; acquiring the size of a data packet transmitted between gateways, and multiplying the size of the data packet by the interference degree to obtain a redundant load; adding the size of the redundant load and the size of the data packet to obtain a communication load between the two gateways; and calculating the idle power of any gateway.
A local area network is constructed between unmanned aerial vehicles belonging to the same forest airspace to realize communication transmission between the unmanned aerial vehicles, and each unmanned aerial vehicle is communicated and sent as a gateway in the local area network.
Installing a Received Signal Strength (RSSI) detection module on each unmanned aerial vehicle, and acquiring the received signal strength between every two unmanned aerial vehicles
I.e. the received signal strength between two gateways is collected. And reflecting the interference degree between the two unmanned aerial vehicles according to the received signal strength, namely the interference degree between the two gateways corresponding to the two unmanned aerial vehicles.
Gateway
And a gateway
Degree of interference corresponding to each other
The calculation formula of (2) is as follows:
wherein,
is a gateway
And a gateway
Corresponding received signal strength.
It should be noted that the gateway
And a gateway
I.e. any two gateways communicating with each other, the gateway on each drone has an id of unique identification.
The interference level has a value range of (0, 1). The stronger the received signal strength, the smaller the interference degree of the gateway, and the smaller the received signal strength, the larger the interference degree of the gateway. The method of acquiring the received signal strength is a conventional method.
The communication load between gateways is affected not only by the size of the data packets but also by the redundancy load of the retransmitted data packets. The reason why the data packet needs to be retransmitted is that interference exists when the local area network is wirelessly propagated, so that the data packet is lost, and the lost data packet needs to be retransmitted.
And collecting the communication load between every two gateways. Specifically, the method comprises the following steps: information transmission is carried out between unmanned aerial vehicle to information transmission based on specific frequency's information transmission ware, because local area network wireless transmission has the interference, so can appear the condition that the data packet loses, solve the problem that the data packet loses and then need carry out retransmission many times, the rate of losing of data packet is concerned with the retransmission number of times of data packet. The interference degree between two liang of unmanned aerial vehicles can reflect the data packet loss rate when transmitting the data packet, because the data packet loss rate can receive the influence of interference degree, receives the interference degree big more, and then the data packet loss rate that corresponds also can be big more, and when receiving the interference degree small more, then the data packet loss rate that corresponds also can be little. Based on the size of the data packet and the interference degree of the signal, the redundancy load of the retransmission data packet is obtained, and further the communication load for transmitting the data packet between every two gateways can be obtained.
And acquiring the size of a data packet transmitted between gateways. And multiplying the size of the data packet by the interference degree to obtain a redundant load, and adding the redundant load and the size of the data packet to obtain the communication load between the gateways. It should be noted that the size of the data packets transmitted between the gateways is available in advance.
Gateway
And a gateway
Corresponding communication load therebetween
The calculation formula of (2) is as follows:
wherein,
is a gateway
And a gateway
The size of the data packet transmitted therebetween;
is a gateway
And a gateway
Corresponding to the degree of interference therebetween.
Wherein, in the calculation formula of the communication load,
namely the gateway
And a gateway
Corresponding redundant loads therebetween.
It should be noted that the redundant load is affected by the number of redundant packets that need to be retransmitted, and in the signal transmission process, due to the shielding of a medium or an obstacle, transmission deviation occurs in wireless transmission, which further causes retransmission, so the worse the received signal strength is, the larger the interference degree of the unmanned aerial vehicle is, the larger the data packet loss rate is, the more redundant packets that need to be retransmitted are, and the larger the redundant load is; conversely, the better the received signal strength is, the smaller the interference degree of the drone is, the smaller the data packet loss rate is, the fewer redundant packets need to be retransmitted, and the smaller the redundant load is.
Further, the idle power of each gateway is calculated. Specifically, the method comprises the following steps: since the gateway communication power corresponding to the drone includes a receiving power and a transmitting power, the gateway corresponding to each drone has a rated communication power. The current communication task of each gateway occupies a part of power, and the unoccupied part in the rated power is idle power. It should be noted that the rated communication power of the gateway corresponding to each drone is known. Therefore, the communication power of the current communication task of each gateway is collected, and the real-time idle power of the current gateway is obtained
Specifically, the method comprises the following steps: the difference between the rated power and the communication load is the idle power. It should be noted that the communication power of the current communication task of the gateway is the communication load.
Step S200, obtaining a gateway distance index between two gateways according to the communication load and the idle power between any two gateways; obtaining an index error rate of a gateway corresponding to the unmanned aerial vehicle according to the similarity of the flight speeds between the two unmanned aerial vehicles; and weighting and summing the index error rate and the gateway distance index to obtain the matching path distance.
Referring to fig. 2, the matching path distance of each transmission path during transmission of each data packet is obtained. Specifically, the method comprises the following steps:
step S210, obtaining a gateway distance index between two gateways according to the communication load and the idle power between any two gateways.
And obtaining a gateway distance index between any two gateways based on the communication load and the idle power between any two gateways. The transmission distance between the gateways is not an actual spatial distance, but reflects the distance between the two gateways through the transmission efficiency of the data packets transmitted between the two gateways. The transmission efficiency of the data packet between the two gateways is determined by the communication load and the vacant power of the two gateways, the larger the communication load between the two gateways is, the smaller the corresponding vacant power is, and the lower the corresponding transmission efficiency is, the longer the distance between the two gateways is; conversely, the smaller the communication load between two gateways, the larger the corresponding idle power, and the lower the corresponding transmission efficiency, the closer the distance between the two corresponding gateways.
Gateway
And a gateway
Gateway distance index between
The calculation formula of (2) is as follows:
wherein,
is a gateway
And a gateway
The communication load between;
is a gateway
An empty load of (2);
is a gateway
Is empty of load.
Step S220, calculating the index error rate of the gateway corresponding to the unmanned aerial vehicle according to the similarity of the flying speeds between the two unmanned aerial vehicles.
Acquiring the flight speeds of the two unmanned aerial vehicles, and obtaining the index error rate of the received data packet corresponding to the gateway corresponding to the two unmanned aerial vehicles according to the cosine similarity of the flight speeds between the two unmanned aerial vehicles.
Because the trip task of the unmanned aerial vehicles is in a forest airspace, the position between the unmanned aerial vehicles has a large influence on the communication quality, the cosine similarity of the speed vectors between the unmanned aerial vehicles is larger, the error between the actual transmission path of the data packet and the predicted gateway distance index is larger, and the error is reflected by the index error rate.
Gateway
And a gateway
Corresponding index error rate
The calculation formula of (2) is as follows:
wherein,
is a gateway
The corresponding flight speed of the unmanned aerial vehicle;
is a gateway
The corresponding flight speed of the unmanned aerial vehicle;
is a gateway
And a gateway
Cosine similarity of flying speed between two corresponding unmanned aerial vehicles.
The larger the cosine similarity of the flight speed vectors of the two unmanned aerial vehicles is, the smaller the corresponding index error rate is; the smaller the cosine similarity is, the larger the corresponding index error rate is.
And step S230, weighting and summing the index error rate and the gateway distance index to obtain the matching path distance.
The transmission path of the data packet between the two gateways comprises: a direct transmission path and an indirect transmission path. That is, besides calculating the gateway distance index obtained by directly transmitting the data packets between the gateway a and the gateway B, other transmission paths can be obtained by performing communication and load sharing on the data packets through other gateways. E.g., from gateway a to gateway C, from gateway C to gateway B. That is, there are multiple transmission paths between the slave gateway a and the gateway B, not only the direct transmission path directly from the gateway a and the gateway B, but also multiple other indirect transmission paths, such as a-C-B, and so on.
For these indirect transmission paths, such as indirect transmission path A-C-B, i.e. the indirect transmission path from gateway A to gateway C and then to gateway B, the gateway distance index corresponding to gateway A and gateway C is first calculated
And index error rate
Then, the gateway distance index corresponding to the gateway C and the gateway B is calculated
And index error rate
Index error rate
And index error rate
As a weight, the gateway distance index
The index error rate
Gateway distance index
And index error rate
And carrying out weighted summation to obtain the matching path distance of the indirect transmission path A-C-B. Note that the path from gateway a to gateway C belongs to a partial path, and the path from gateway C to gateway B also belongs to a partial path. The indirect transmission path includes a plurality of branch paths, each branch path corresponding to two gateways.
For the indirect transmission path, calculating a gateway distance index and an index error rate corresponding to each branch path, and weighting and summing the gateway distance indexes and the index error rates of a plurality of branch paths in the indirect transmission path to obtain the matching path distance of the indirect transmission path.
For the direct transmission path, each direct transmission path corresponds to two gateways, other branch paths are not directly included, and the product of the gateway distance index and the index error rate corresponding to the direct transmission path is calculated to be the matching path distance of the direct transmission path.
Multiple data packets are transmitted simultaneously between the unmanned aerial vehicles, and an optimal path needs to be selected for each data packet simultaneously. Based on any data packet, calculating index error rate and gateway distance index to calculate matching path distance in data packet transmission process.
Gateway
And a gateway
To a first
Matching path distance of strip transmission path
The calculation formula of (2) is as follows:
wherein,
is a gateway
And a gateway
To get rid of
First of a strip transmission path
Index error rates corresponding to the respective paths;
is a gateway
And a gateway
To get rid of
First of the strip path
And gateway distance indexes corresponding to the branch paths.
And obtaining the matching path distance corresponding to a plurality of transmission paths between any two gateways.
Step S300, acquiring a plurality of data packets transmitted among gateways; and matching the distance of the matched path with the data packet to obtain the optimal path for transmitting a plurality of data packets.
When a plurality of data packets are transmitted between the unmanned aerial vehicles at the same time, an optimal path needs to be optimized for transmission of each data packet at the same time, and the mutual interference condition between the data packet transmission paths needs to be analyzed.
Based on the selection of the matching path distance in the transmission process of a plurality of data packets, the data packets and the matching path distance are matched by using a K-M algorithm, namely the transmission paths of the plurality of data packets are optimally distributed by using the K-M algorithm. Not only the transmission distance of each transmission path but also the mutual influence between the transmission paths when a plurality of data packets are transmitted simultaneously need to be considered when a plurality of data packets are transmitted simultaneously.
Because the K-M algorithm can not predict the transmission load condition at the next moment, the K-M algorithm is used for carrying out optimal distribution on paths of a plurality of data packets needing to be transmitted, the mutual influence among the paths is eliminated, and a fully-connected neural network can be used for carrying out real-time adjustment on the communication load and the idle power of all matching schemes.
Numbering the data packets needing to be transmitted between the gateways, and constructing a data packet set according to the sequence needing to be transmitted, wherein the data packet set needing to be transmitted between the gateway A and the gateway B comprises the following steps:
。
first from the data packet
Start planning transmission path, data packet
Matching path distance of
The transmission path is any corresponding transmission path between two gateways.
Packet-based data
Distance of matching path of
On the basis, the communication load and the vacant power are analyzed according to the gateways corresponding to other unmanned aerial vehicles in the local area network to obtain a data packet
Matching path distance of
(ii) a Based on the data packet
Matching path distance of
And data packet
Matching path distance of
Based on the received data packet, obtain the data packet again
Matching path distance of
Repeating the above steps until obtaining the matching path distance of each data packet
。
Optimally matching each data packet in the data packet set with the matching path distance by using a K-M algorithm to obtain the matching path distance optimally matched with each data packet
. And acquiring the sum of the distances of the matching paths of the data packet set, wherein when the sum of the distances of the matching paths is minimum, the matching scheme is the optimal matching result.
The purpose of optimally matching the matching path distances of all the data packets is to reduce the influence of the flight direction of the unmanned aerial vehicle on the data packets and the matching paths, and in the matching process, normalization processing is performed on matching values.
And obtaining the optimal path of the real-time gateway communication load sharing of each data packet between every two unmanned aerial vehicles based on the matching result of the K-M algorithm.
Based on the communication interference and the difference of the flight speed between the unmanned aerial vehicles in the airspace, an optimal load sharing path is selected for the communication between the local area network gateways constructed by the unmanned aerial vehicles, the stability of the communication network between the unmanned aerial vehicles is ensured, and the communication consumption is reduced.
In summary, the embodiment of the present invention utilizes the artificial intelligence technology, and first collects the received signal strength between two gateways to obtain the interference degree of the corresponding gateway; acquiring the size of a data packet transmitted between gateways, and multiplying the size of the data packet by the interference degree to obtain a redundant load; adding the size of the redundant load and the size of the data packet to obtain a communication load between the two gateways; and calculating the idle power of any gateway. Obtaining a gateway distance index between two gateways according to the communication load and the vacant power between any two gateways; obtaining an index error rate of a gateway corresponding to the unmanned aerial vehicle according to the similarity of the flight speeds between the two unmanned aerial vehicles; and weighting and summing the index error rate and the gateway distance index to obtain the matching path distance. Acquiring a plurality of data packets transmitted between two gateways; and matching the distance of the matched path with the data packet to obtain the optimal path for transmitting a plurality of data packets. According to the method and the system, the optimal path for transmitting each data packet is obtained through the interference degree, the communication power and the idle power of each gateway, so that the stability of a communication network between the unmanned aerial vehicles is ensured, and the communication energy consumption is reduced.
The embodiment of the invention also provides an internet of things gateway communication load sharing system, which comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor realizes the steps of the method when executing the computer program. Since the detailed description is given above for the internet of things gateway communication load sharing method, no further description is given.
It should be noted that: the sequence of the above embodiments of the present invention is only for description, and does not represent the advantages or disadvantages of the embodiments. And that specific embodiments have been described above. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (8)
1. A gateway communication load sharing method of the Internet of things is applied to communication among unmanned aerial vehicles, and communication receiving and sending equipment of each unmanned aerial vehicle is a gateway in a local area network, and is characterized by comprising the following steps:
acquiring the received signal strength between every two gateways to obtain the interference degree of the corresponding gateway; acquiring the size of a data packet transmitted between gateways, and multiplying the size of the data packet by the interference degree to obtain a redundant load; adding the redundant load and the size of the data packet to obtain a communication load between the two gateways; calculating the idle power of any gateway;
obtaining a gateway distance index between any two gateways according to the communication load and the vacant power between the two gateways; obtaining an index error rate of a gateway corresponding to the unmanned aerial vehicle according to the similarity of the flight speeds between the two unmanned aerial vehicles; weighting and summing the index error rate and the gateway distance index to obtain a matching path distance;
acquiring a plurality of data packets transmitted between two gateways; and matching the matching path distance with the data packets to obtain a plurality of optimal paths for data packet transmission.
2. The internet of things gateway communication load sharing method according to claim 1, wherein the calculating of the idle power of any gateway includes:
acquiring rated power of each gateway; and the difference value between the rated power and the communication load is idle power.
3. The internet of things gateway communication load sharing method according to claim 1, wherein obtaining the gateway distance index between any two gateways according to the communication load and the idle power between the two gateways comprises:
the calculation formula of the gateway distance index is as follows:
wherein,
is a gateway
And a gateway
The gateway distance index between;
is a gateway
And a gateway
The communication load between;
is a gateway
An empty load of (2);
is a gateway
Is empty of load.
4. The internet of things gateway communication load sharing method according to claim 1, wherein obtaining the index error rate of the gateway corresponding to the unmanned aerial vehicle according to the similarity of the flight speeds between the two unmanned aerial vehicles comprises:
obtaining index error rates of gateways corresponding to the two unmanned aerial vehicles according to the cosine similarity of the flight speeds between the two unmanned aerial vehicles;
the calculation formula of the index error rate is as follows:
wherein,
is a gateway
And a gateway
A corresponding index error rate;
is a gateway
The corresponding flight speed of the unmanned aerial vehicle;
is a gateway
Corresponding flying speed of unmanned aerial vehicleDegree;
is a gateway
And a gateway
Cosine similarity of flying speed between two corresponding unmanned aerial vehicles.
5. The internet of things gateway communication load sharing method according to claim 1, wherein the index error rate and the gateway distance index are weighted and summed to obtain a matching path distance, further comprising:
the transmission path of the data packet between the two gateways comprises: a direct transmission path and an indirect transmission path;
the indirect transmission path comprises a plurality of branch paths, and each branch path corresponds to two gateways; calculating the gateway distance index and the index error rate corresponding to each branch path, and weighting and summing the gateway distance indexes and the index error rates of a plurality of branch paths in the indirect transmission path to obtain the matching path distance of the indirect transmission path;
each direct transmission path corresponds to two gateways, and the product of the gateway distance index and the index error rate corresponding to the direct transmission path is calculated to be the matching path distance of the direct transmission path.
6. The internet of things gateway communication load sharing method according to claim 1, wherein the matching path distance and the data packet comprises:
and matching the data packet with the matching path distance by utilizing a K-M algorithm.
7. The internet of things gateway communication load sharing method according to claim 1, wherein the acquiring the received signal strength between every two gateways to obtain the interference degree of the corresponding gateway comprises:
the calculation formula of the interference degree is as follows:
wherein,
is a gateway
And a gateway
The corresponding interference degree between the two signals;
is a gateway
And a gateway
Corresponding received signal strength.
8. An internet of things gateway communication load sharing system, comprising a memory, a processor and a computer program stored in the memory and operable on the processor, wherein the processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120182935A1 (en) * | 2011-01-14 | 2012-07-19 | Cisco Technology, Inc. | System and method for packet distribution in a vehicular network environment |
| WO2014185768A1 (en) * | 2013-05-13 | 2014-11-20 | Mimos Berhad | A method of spectrum aware routing in a mesh network and a system derived thereof |
| CN104184829A (en) * | 2014-09-10 | 2014-12-03 | 西安电子科技大学宁波信息技术研究院 | Routing method in vehicular ad hoc network based on content integrality and location information |
| CN110784852A (en) * | 2019-10-15 | 2020-02-11 | 中国科学院自动化研究所 | V2V routing method based on online link duration prediction |
| CN114040358A (en) * | 2021-12-06 | 2022-02-11 | 大连大学 | High-stability clustering method for unmanned aerial vehicle cluster network |
-
2022
- 2022-05-24 CN CN202210565952.2A patent/CN114666766B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120182935A1 (en) * | 2011-01-14 | 2012-07-19 | Cisco Technology, Inc. | System and method for packet distribution in a vehicular network environment |
| WO2014185768A1 (en) * | 2013-05-13 | 2014-11-20 | Mimos Berhad | A method of spectrum aware routing in a mesh network and a system derived thereof |
| CN104184829A (en) * | 2014-09-10 | 2014-12-03 | 西安电子科技大学宁波信息技术研究院 | Routing method in vehicular ad hoc network based on content integrality and location information |
| CN110784852A (en) * | 2019-10-15 | 2020-02-11 | 中国科学院自动化研究所 | V2V routing method based on online link duration prediction |
| CN114040358A (en) * | 2021-12-06 | 2022-02-11 | 大连大学 | High-stability clustering method for unmanned aerial vehicle cluster network |
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