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CN111328083A - Wireless radio frequency communication self-evolution dynamic networking method based on genetic algorithm - Google Patents

Wireless radio frequency communication self-evolution dynamic networking method based on genetic algorithm
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Publication number
CN111328083A
CN111328083ACN202010148412.5ACN202010148412ACN111328083ACN 111328083 ACN111328083 ACN 111328083ACN 202010148412 ACN202010148412 ACN 202010148412ACN 111328083 ACN111328083 ACN 111328083A
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radio frequency
wireless radio
communication
network
wireless
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CN202010148412.5A
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任军
冯志刚
李俊
艾小亮
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Guizhou Baozhida Network Technology Co ltd
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Guizhou Baozhida Network Technology Co ltd
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Abstract

The invention discloses a radio frequency communication self-evolution dynamic networking method based on a genetic algorithm, which relates to the field of radio frequency networking communication transmission, and comprises the following steps of self-constructing an initial radio frequency communication network: when the wireless radio frequency network is initialized and constructed, a unique number is set for each wireless radio frequency device, communication data final receiver numbers are set for all networking wireless radio frequency devices, and after all the wireless radio frequency devices are installed in place, all the wireless radio frequency devices are networked from near to far away from the final receiver device. The invention solves the problems that the traditional wireless radio frequency networking mode cannot realize rapid self-networking in a complicated space and a long distance and data accumulation or loss is easy to generate during high concurrency by applying a genetic algorithm to the construction of a wireless radio frequency communication network.

Description

Wireless radio frequency communication self-evolution dynamic networking method based on genetic algorithm
Technical Field
The invention relates to the technical field of wireless radio frequency networking communication transmission, in particular to a wireless radio frequency communication self-evolution dynamic networking method based on a genetic algorithm.
Background
The wireless radio frequency is a non-contact automatic identification technology, can realize target identification and data exchange, and has the characteristics of non-contact, high reading speed, no abrasion, no environmental influence, long service life and convenient use.
However, because the network quality of a communication operator has a great relationship with the coverage rate of the base station and the utilization rate of the base station, in signal blind areas, unmanned areas, semi-unmanned areas, urban and rural cross-connection areas, underground tunnels, basements and other occasions, the phenomenon that the coverage of a single communication means often cannot meet the actual use requirement exists, and the actual requirements of the internet of things service are difficult to meet.
The genetic algorithm is a randomized search method evolved by using the evolution law of the biological world for reference, and has natural advantages when being applied to the field of wireless radio frequency, so that the invention of an ad hoc network communication system which is long in distance, low in cost, flexible in deployment and rapid in networking is a necessary trend.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a wireless radio frequency communication self-evolution dynamic networking method based on a genetic algorithm, which solves the problems that the traditional wireless radio frequency networking mode cannot realize rapid self-networking in a complicated space and a long distance and is easy to generate data accumulation or loss during high concurrency.
(II) technical scheme
In order to achieve the purpose, the invention provides the following technical scheme: a wireless radio frequency communication self-evolution dynamic networking method based on a genetic algorithm comprises the following steps:
s1, self-construction of an initial wireless radio frequency communication network: when the wireless radio frequency network is initialized and constructed, a unique number is set for each wireless radio frequency device, communication data final receiver numbers are set for all networking wireless radio frequency devices, and after all the wireless radio frequency devices are installed in place, all the wireless radio frequency devices are networked from near to far away from the final receiver device.
S2, self-optimizing according to the stability of the network link: after the initialization network is successfully established, the network communication test needs to be performed on the whole network, and after the test process, all the wireless equipment modules reselect one or more backup wireless communication links and each backup wireless communication link participates in the test.
S3, self-optimizing according to the data transmission speed: when the whole wireless radio frequency communication network is stable, a single wireless radio frequency module can conduct self-optimization according to the current communication data load capacity of the single wireless radio frequency module, a most appropriate communication route is selected as a leading communication link, and then other standby links are removed from the cache.
S4, obtaining the final dynamic stable wireless radio frequency communication network: through the repeated and independent optimization of the steps S2 and S3, a communication network which is relatively efficient and stable in the testing stage is finally obtained, and the whole network can be put into formal business use.
Preferably, in step S1, the number range set by the wireless rf device is defined as an integer within a closed interval of 1-65534.
Preferably, in step S1, all the wireless rf devices autonomously and nearby connect to the wireless device with the strongest signal as the bridge point of their current devices according to the signal strength of other peripheral devices, and assist in calculating the shortest communication distance when seeking the strongest signal point.
Preferably, in step S1, when it is determined that the link cannot be formed through the strongest signal device point to the final receiving device point, the device point with the next signal is selected, and the process is repeated until all the radio frequency devices form a complete link.
Preferably, in step S2, all the rf devices perform the communication stability test at a rate of more than 20% of the actual traffic.
Preferably, in step S2, since each wireless device module has multiple wireless communication links, in order to ensure the uniqueness of the received data, the data protocol between the entire networks is agreed in sequence according to the message time, the message number, the sender, the receiver, the command bit, the command length, the command content, and the terminator.
Preferably, in step S2, the entire communication message is transmitted in the radio frequency network by using 16-ary system.
Preferably, in step S2, the sender is the device ID of the currently sent message, and the recipient is the device ID at which the message finally arrives.
Preferably, in step S3, the evaluation criteria for selecting a most suitable communication route are the time of arrival of the data packet and the data carrying capacity.
Preferably, in steps S1-S3, when the wireless radio frequency device finds itself offline, the wireless radio frequency device autonomously restarts the self-construction of the initial wireless radio frequency communication network, autonomously optimizes according to the stability of the network link, and autonomously optimizes according to the data transmission speed.
(III) advantageous effects
The invention provides a wireless radio frequency communication self-evolution dynamic networking method based on a genetic algorithm, which has the following beneficial effects:
the invention applies the genetic algorithm to the wireless radio frequency communication network construction, so when a batch of wireless radio frequency equipment is networked in a three-dimensional space, after all the wireless radio frequency equipment is deployed, the wireless radio frequency equipment in the whole three-dimensional space automatically searches an equipment module close to the optimum according to the strength of a wireless radio frequency signal for data link transmission, dynamically optimizes the wireless radio frequency communication networking quality in real time along with the time lapse, and constructs a balanced wireless radio frequency communication network between the most stable communication and the fastest transmission speed, thereby improving the performances of the wireless radio frequency communication network in the aspects of throughput, transmission delay and the like, improving the data transmission efficiency, and the wireless radio frequency communication self-evolution dynamic networking method based on the genetic algorithm can be widely applied to the remote complex networking of various wireless radio frequency communication equipment and can realize the self-evolution dynamic networking according to the communication stability among the radio frequency networks, The quality of data transmission high efficiency carries out dynamic adjustment networking structure, has solved traditional wireless radio frequency networking mode, can't realize quick complicated space long distance ad hoc network, produces the problem that data pile up or lose easily when high concurrency simultaneously.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a technical scheme that: a wireless radio frequency communication self-evolution dynamic networking method based on a genetic algorithm comprises the following steps:
s1, self-construction of an initial wireless radio frequency communication network: when the wireless radio frequency network is initialized and constructed, firstly, a unique serial number is set for each wireless radio frequency device, meanwhile, a communication data final receiver serial number is set for all networking wireless radio frequency devices, after all the wireless radio frequency devices are installed in place, all the wireless radio frequency devices are networked from near to far away from the final receiver device, the serial number of each wireless radio frequency device is a unique identifier of each wireless radio frequency device, and data string packets are prevented.
S2, self-optimizing according to the stability of the network link: after the initialization network is successfully established, the network communication test needs to be performed on the whole network, and after the test process, all the wireless equipment modules reselect one or more backup wireless communication links and each backup wireless communication link participates in the test.
S3, self-optimizing according to the data transmission speed: when the whole wireless radio frequency communication network is stable, a single wireless radio frequency module can self-optimize according to the current self communication data load capacity, a most suitable communication route is selected as a leading communication link, other standby links are removed from a cache, the standard of self-optimization according to the data transmission speed is from a central point to a farthest end communication node, the data transmission speed is stably controlled at 5Kb per second, meanwhile, the data delay is less than 2 seconds, as the radio frequency communication is easily subjected to external electromagnetic interference, even a front solid object can also have great influence on the whole communication, therefore, once a certain node device in the network has a standard that the packet loss rate is more than 10 percent in the network, the communication is unstable, the self-optimization in the area range can be triggered relative to a nearby node with stable communication, and only when the small-range optimization cannot be met, the tuning range is gradually enlarged, if tuning is carried out, the network is in a load state, normal data transmission is preferentially met, communication cannot be communicated after continuous tuning is carried out for more than 30 minutes, the node is abandoned temporarily in the whole communication network, a fault is reported on corresponding communication management software, and next tuning is triggered manually.
S4, obtaining the final dynamic stable wireless radio frequency communication network: through the repeated and independent optimization of the steps S2 and S3, a communication network which is relatively efficient and stable in the testing stage is finally obtained, and the whole network can be put into formal business use.
As a technical optimization scheme of the present invention, in step S1, the number range set by the radio frequency device is defined as an integer within the closed interval 1-65534, in practical applications, the number is only required to be started from 1, and in a complex building, it can be agreed that the number 1 is started from floor 1, for example, 1001 identifies the device No. 1 from floor 1, and the number 32001 identifies the device No. 1 from floor 32, so that the position of the device can be known from the number later, and the device failure point is easy to be located.
As a technical optimization scheme of the present invention, in step S1, all the radio frequency devices autonomously and proximally connect the radio device with the strongest signal as the bridging point of their own current devices according to the signal strength of other peripheral devices, and when seeking the strongest signal point, simultaneously assist in calculating the shortest communication distance, that is, the time interval between the transmission end sending out the data signal and the receiving end receiving the response signal is denoted as Tt, and the time interval between the receiving end receiving the signal of the transmission end and the receiving end sending out the response signal is denoted as Tr, so that the one-way flight time Tf of the signal at the transmitting and receiving ends is (Tt-Tr)/2, and the distance d between the two points is c Tf, thus using the shortest distance to assist the signal strength, and determining the best radio communication path more accurately.
As a technical optimization scheme of the present invention, in step S1, when it is determined that the device point with the strongest signal cannot form a link to the device point to be finally received, the device point with the second signal is selected, and the process is repeated until all the radio frequency devices form a complete link, and when it is found that a device is not linked to the entire network, nodes of the radio frequency module need to be added reasonably.
As a technical optimization scheme of the present invention, in step S2, all the radio frequency devices perform a communication stability test at a rate exceeding 20% of the actual traffic volume.
As a technical optimization scheme of the invention, in step S2, because each wireless device module has a plurality of wireless communication links, in order to ensure the uniqueness of received data, the data protocol between the whole networks is agreed according to message time, message number, sender, receiver, command bit, command length, command content and end symbol in sequence, the uniqueness of the message can be determined through the message time and the message number, when receiving repeated messages, unprocessed messages are directly discarded, network overhead is saved, data oscillation is avoided, when finding that the receiver is not self, the messages are directly sent out along the links, the operation overhead of the wireless radio frequency device is saved, wherein the message time means timestamp means the total seconds from 00 minutes 00 seconds to the present time when the time of Beijing is 1970.01.01.08 to the present time, the message number means within 1 second, and if a plurality of messages are sent, sequentially increasing 1, if not, defaulting to 0, numbering range is 0-99, command content is a data packet finally transmitted to the terminal equipment, and the format and characteristics of the terminator are a 16-system bit obtained according to a standard binary exclusive-or algorithm, and a certain data checking function is borne.
As a technical optimization scheme of the present invention, in step S2, the entire communication packet is transmitted in the radio frequency network by using 16 systems, so as to improve the data transmission efficiency.
As a technical optimization scheme of the present invention, in step S2, the sender is the device ID of the currently sent message, and the recipient is the device ID at which the message finally arrives.
As a technical optimization of the present invention, in step S3, the evaluation criteria for selecting a most suitable communication route are the time of arrival of the data packet and the data carrying capacity.
As a technical optimization scheme of the present invention, in steps S1-S3, in the actual application process, the radio frequency transmission distance and the signal strength are easily interfered, which causes instability of the local communication network, so each radio frequency device has a set of self-checking mechanism, when the radio frequency device finds itself offline, the radio frequency device automatically restarts the self-construction of the initial radio frequency communication network, automatically optimizes according to the network link stability, and automatically optimizes according to the data transmission speed.
In conclusion, the invention solves the problems that the traditional wireless radio frequency networking mode cannot realize rapid self-networking in a complicated space and a long distance and data accumulation or loss is easy to generate during high concurrency by applying the genetic algorithm to the construction of the wireless radio frequency communication network.
It should be noted that, in this document, terms such as "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (10)

CN202010148412.5A2020-03-052020-03-05Wireless radio frequency communication self-evolution dynamic networking method based on genetic algorithmPendingCN111328083A (en)

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Application publication date:20200623


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