CN116155817A - Data polling scheduling method and device, equipment and storage medium - Google Patents
Data polling scheduling method and device, equipment and storage medium Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/50—Queue scheduling
- H04L47/62—Queue scheduling characterised by scheduling criteria
- H04L47/622—Queue service order
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
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- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/08—Load balancing or load distribution
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- H—ELECTRICITY
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Abstract
The embodiment of the invention discloses a data polling scheduling method, a device, equipment and a storage medium, wherein the method comprises the following steps: determining a data transmission state of each data acquisition device for reflecting a data transmission success rate when the data acquisition device transmits data to the wireless communication device, wherein each data acquisition device corresponds to a service flow queue comprising a plurality of packet data and data addresses of each packet data; determining an initial weight of a service flow queue inversely proportional to the data transmission success rate by utilizing the data transmission success rate; and carrying out weighted polling scheduling processing on the packet data according to the initial weight and the data address of each service flow queue, and determining a target transmission queue of the current data frame. By the method, the target transmission queue of the current data frame can be obtained by carrying out weighted polling scheduling by utilizing the initial weight which is inversely proportional to the success rate of data transmission, so that the polling scheduling of the current data frame is divided into light and heavy urgency according to the weight, and the service transmission efficiency can be improved in a load balancing manner when the service volume is abnormal.
Description
Technical Field
The present invention relates to the field of data transmission technologies, and in particular, to a method, an apparatus, a device, and a storage medium for scheduling polling of data.
Background
Along with the continuous perfection of embedded system functions and the continuous expansion of markets, equipment state sensing equipment under multiple conditions is increasingly applied to terminals, for example, sensing equipment comprises data acquisition devices such as temperature sensors, vibration sensors and the like, and terminals comprise electronic equipment such as concentrators and energy controllers and the like with data processing capability, wherein the sensors timely transmit data back to the terminals through acquisition of environment variables, so that the monitoring of the working environment states of the terminals is realized. This increases the link traffic of the bluetooth bearer. If the change of the environmental variable is abnormal at a certain moment, the terminal needs to increase the traffic volume and report to each sensor, and the reporting abnormal blocking and other conditions are caused.
Therefore, a technical means for improving the problem of low service transmission efficiency when the transmission traffic of the conventional bluetooth communication link is high in rate is needed.
Disclosure of Invention
The invention mainly aims to provide a data polling scheduling method, a data polling scheduling device, data polling scheduling equipment and a storage medium, which can solve the problem of service transmission efficiency reduction in the prior art.
To achieve the above object, a first aspect of the present invention provides a method for scheduling polling of data, the method comprising:
determining a data transmission state of each data acquisition device, wherein the data transmission state is used for reflecting the data transmission success rate when the data acquisition devices transmit data to the wireless communication device, each data acquisition device corresponds to a service flow queue, each service flow queue comprises a plurality of packet data and data addresses of each packet data, and the data acquisition devices are in wireless communication connection with the wireless communication device;
determining an initial weight of the service flow queue by utilizing the data transmission success rate, wherein the initial weight is inversely proportional to the data transmission success rate;
and carrying out weighted polling scheduling processing on the packet data of each service flow queue according to the initial weight of each service flow queue and the data address, and determining a target transmission queue of the current data frame.
In one possible implementation manner, the determining the target transmission queue of the current data frame according to the initial weight of each traffic flow queue and the weighted polling scheduling processing of the packet data of each traffic flow queue by the data address includes:
Determining a target service flow queue corresponding to the maximum initial weight in the initial weights;
reading packet data corresponding to a first data address in the target service flow queue to a preset transmission queue of a current data frame, updating the target service flow queue, and recording polling times i=i+1;
and carrying out initial weight updating processing by using the maximum initial weight and the initial weight of each service flow queue, determining the updated initial weight of each service flow queue, and returning to the step of executing the target service flow queue corresponding to the maximum weight in the determined initial weight until the polling frequency i is equal to a preset polling frequency threshold value, thereby obtaining the target transmission queue of the current data frame.
In a possible implementation manner, if the initial weight is a sum of a static weight and a dynamic weight, the determining the initial weight of the traffic flow queue by using the data transmission success rate includes:
utilizing the data transmission success rate to truly the static weight, wherein the static weight is inversely proportional to the data transmission success rate;
and determining the initial weight by utilizing the static weight and a preset dynamic weight.
In one possible implementation manner, the performing initial weight update processing by using the maximum initial weight and the initial weight of each service flow queue, and determining the updated initial weight of each service flow queue includes:
determining updated dynamic weights of the target service flow queues by utilizing the maximum initial weights, static weights of the initial weights and dynamic weight updating processing of the target service flow queues, wherein the updated dynamic weights are differences between the maximum initial weights and the static weights;
and carrying out initial weight updating processing by using the updated dynamic weights, the dynamic weights of the rest business flow queues except the target business flow queue and the static weights, and determining the updated initial weights of the business flow queues.
In a possible implementation manner, if the device wireless communication device includes a bluetooth device, the determining the data transmission status of each data acquisition device includes:
controlling the Bluetooth equipment to send out a broadcast calling signal;
receiving a recall reply result of the broadcast recall signal returned by each data acquisition device, wherein the recall reply result at least comprises the equipment type, the signal strength and the signal-to-noise ratio of the data acquisition device;
And determining the data transmission state of each data acquisition device according to the equipment type, the signal strength and the signal-to-noise ratio.
In one possible implementation, the method further includes:
counting the service flow request quantity of different service flows, wherein the service flow request quantity is used for reflecting the data reading requirement of the service flows;
and determining a preset value of the second weight according to the service flow request quantity.
In a possible implementation manner, the data acquisition device is configured to acquire operation data of the electrical device, and then the method further includes:
uploading the target transmission queue to a preset upper computer, wherein the upper computer is used for carrying out data analysis according to the target transmission queue and determining the running state of the power equipment.
To achieve the above object, a second aspect of the present invention provides a polling scheduling apparatus for data, the apparatus comprising:
a state determination module: the method comprises the steps that the method is used for determining the data transmission state of each data acquisition device, the data transmission state is used for reflecting the data transmission success rate when the data acquisition devices transmit data to the wireless communication device, each data acquisition device corresponds to one service flow queue, each service flow queue comprises a plurality of packet data and data addresses of each packet data, and the data acquisition devices are in wireless communication connection with the wireless communication device;
And a weight determining module: the method comprises the steps of determining initial weights of the service flow queues by utilizing the data transmission success rate, wherein the initial weights are inversely proportional to the data transmission success rate;
and a polling scheduling module: and the target transmission queue of the current data frame is determined by carrying out weighted polling scheduling processing on the packet data of each service flow queue according to the initial weight of each service flow queue and the data address.
To achieve the above object, a third aspect of the present invention provides a computer-readable storage medium storing a computer program, which when executed by a processor causes the processor to perform the steps as described in the first aspect and any one of the possible implementations.
To achieve the above object, a fourth aspect of the present invention provides a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps as described in the first aspect and any one of the possible implementations.
The embodiment of the invention has the following beneficial effects:
the invention provides a data polling scheduling method, which comprises the following steps: determining a data transmission state of each data acquisition device, wherein the data transmission state is used for reflecting the data transmission success rate when the data acquisition devices transmit data to the wireless communication device, each data acquisition device corresponds to a service flow queue, each service flow queue comprises a plurality of packet data and data addresses of each packet data, and the data acquisition devices are in wireless communication connection with the wireless communication device; determining an initial weight of the service flow queue by utilizing the data transmission success rate, wherein the initial weight is inversely proportional to the data transmission success rate; and carrying out weighted polling scheduling processing on the packet data of each service flow queue according to the initial weight and the data address of each service flow queue, and determining a target transmission queue of the current data frame. By the method, the initial weight of the service flow queue can be obtained according to the data transmission state of the data acquisition device, and then the weighted polling scheduling processing is carried out through the initial weight, so that the target transmission queue of the current data frame is obtained, the weighted polling scheduling according to the weight of the initial weight is realized when the traffic volume is abnormal, the load balancing is realized, and the service transmission efficiency is improved.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Wherein:
FIG. 1 is a block diagram of a data polling scheduling system according to an embodiment of the present invention;
FIG. 2 is a flowchart of a method for scheduling polling of data according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a poll scheduling of a traffic queue according to an embodiment of the present invention;
FIG. 4 is another flow chart of a method for scheduling polling of data according to an embodiment of the present invention;
FIG. 5 is a block diagram of a data polling scheduler according to an embodiment of the present invention;
fig. 6 is a block diagram of a computer device in an embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, fig. 1 is a block diagram of a data polling and scheduling system according to an embodiment of the present invention, where the data polling and scheduling system shown in fig. 1 includes a data acquisition device, a wireless communication device 102 and a host computer 103, and the data acquisition device, the wireless communication device 102 and the host computer 103 are connected by wireless communication, where the number of data acquisition devices may be plural, and therefore, the data acquisition device includes a data acquisition device 1011, a data acquisition device 1012, data acquisition devices 1013, … …, and a data acquisition device 101n; further, the data acquisition device is used for acquiring data of an acquisition object, the data acquisition device comprises but is not limited to an electric signal acquisition device, a temperature acquisition device, a pressure acquisition device, a flow acquisition device and the like, and the acquisition object comprises but is not limited to electric facilities such as a transformer and the like; the wireless communication device 102 is configured to provide a wireless communication connection channel, so that the collected data can be wirelessly transmitted, and the wireless communication device may be a bluetooth communication module; the upper computer is used for receiving the collected data, performing data processing such as monitoring and analysis on the collected data, for example, analyzing the running state information of the collected object through data monitoring, and knowing the running condition.
Referring to fig. 2, fig. 2 is a flowchart of a method for scheduling polling of data according to an embodiment of the present invention, where the method shown in fig. 2 includes the following steps:
201. determining a data transmission state of each data acquisition device, wherein the data transmission state is used for reflecting the data transmission success rate when the data acquisition devices transmit data to the wireless communication device, each data acquisition device corresponds to a service flow queue, each service flow queue comprises a plurality of packet data and data addresses of each packet data, and the data acquisition devices are in wireless communication connection with the wireless communication device;
it should be noted that the method may be applied to a terminal or a server, where the embodiment is applied to a terminal for illustration, where the terminal includes, but is not limited to, a desktop terminal or a mobile terminal, the mobile terminal may specifically be at least one of a mobile phone, a tablet computer, a notebook computer, and the like, the server may be implemented by using an independent server or a server cluster formed by multiple servers, where the data acquisition devices have multiple data acquisition devices, each data acquisition device performs data acquisition on an acquisition object according to a preset sampling period, the acquired data may be cached to generate a service flow queue, each data acquisition device corresponds to one service flow queue FQn one by one, for example, the electrical signal acquisition device corresponds to one electrical signal service flow queue, the temperature acquisition device corresponds to one temperature service flow queue, the pressure acquisition device corresponds to one pressure service flow queue, and the flow acquisition device corresponds to one flow service flow queue. Each traffic queue is composed of sampling data obtained according to a sampling period, where the sampling data may also be called as packet data of the traffic queue, please refer to fig. 3, fig. 3 is a schematic diagram of polling scheduling of the traffic queue in an embodiment of the present invention, and fig. 3 includes four traffic queues: the system comprises a traffic flow queue FQ1, a traffic flow queue FQ2, a traffic flow queue FQ3 and a traffic flow queue FQ4, and a target transmission queue DQ1 obtained through the four traffic flow queues, wherein the traffic flow queue FQ1 comprises packet data A1 and packet data A2 … …; the traffic flow queue FQ2 includes packet data B1 and packet data B2 … …; the traffic queue FQ3 includes packet data C1 and packet data C2 … …; the traffic queue FQ4 includes packet data D1 and packet data D2 … …; the target transmission queue DQ1 includes packet data B1, packet data A1, packet data B1, packet data C1 … …; the packet data of the traffic queue FQn is acquired by a data acquisition device corresponding to the traffic queue FQn, and the packet data of the target transmission queue DQ1 is acquired by the data polling scheduling method shown in the present embodiment.
Illustratively, the first queue FQ1 in fig. 3 is an electrical signal service, and each element A1, A2, etc. therein is an address of data output by the electrical signal sensor; the second queue FQ2 is a temperature service, and each element B1, B2, etc. in the second queue is an address of data output by the temperature sensor; similarly, queues FQ3 and FQ4 are pressure service queues and traffic service queues, respectively. Summarizing, the following is true: each service corresponds to a service queue, the element of the queue is a data address of the corresponding service, and each data address stores corresponding packet data. Each service queue is ordered by a weighted polling algorithm according to each service weight defined in advance and is sent to the leaving queue, and the empty service queue does not participate in the ordering and sending.
It should be understood that, in fig. 3, one target transmission queue DQ1 is taken as an example to describe the present embodiment, but the number of the target transmission queues DQ1 is not limited in the present application, and the number of the target transmission queues DQ1 may be plural.
Further, in order to improve the service transmission efficiency when the plurality of data acquisition devices perform data transmission, it is necessary to determine a data transmission state of each data acquisition device, where the data transmission state is used to reflect a data transmission success rate when the data acquisition device transmits data to the wireless communication device, so as to determine whether the data transmission of each data acquisition device is abnormal when the plurality of data acquisition devices perform data transmission. Further, the data transmission success rate is proportional to the communication success rate, so the data transmission success rate can be measured by the communication success rate, and the following formula is specifically referred to:
Communication success rate= (number of transmissions-number of CRC failures)/number of transmissions×100%.
202. Determining an initial weight of the service flow queue by utilizing the data transmission success rate, wherein the initial weight is inversely proportional to the data transmission success rate;
further, different initial weights are assigned to different traffic queues according to the data transmission success rate determined in step 201, the initial weights are inversely proportional to the data transmission success rates, the data transmission success rates of the data acquisition devices are compared, if the data transmission success rate of a certain data acquisition device is higher, the initial weight of the data acquisition device is lower than the initial weight assignment of other data acquisition devices, otherwise, if the data transmission success rate of a certain data acquisition device is lower, the initial weight of the data acquisition device is higher than the initial weight assignment of other data acquisition devices. The initial weight is used for reflecting the data transmission resources of the service flow queue, and the higher the initial weight is, the more the data transmission resources are.
If the change of the environmental variable is abnormal at a certain time, the terminal needs to increase the traffic to report to each sensor, which may cause reporting abnormal blocking. At this time, the success rate of data transmission of the service flow queue with large data volume is lower than that of other data volumes, and after the weight giving process is performed in step 202, the service flow queue will have higher initial weight, and more data transmission resources are obtained, so as to realize load balancing.
203. And carrying out weighted polling scheduling processing on the packet data of each service flow queue according to the initial weight of each service flow queue and the data address, and determining a target transmission queue of the current data frame.
And outputting the data addresses by different initial weights of different service flow queues to realize data transmission, specifically, performing weighted polling scheduling processing on packet data of each service flow queue according to the initial weights of each service flow queue and the data addresses, and determining a target transmission queue of the current data frame, for example, the service flow queues with high initial weights obtain more data transmission resources, and the service flow queues with low initial weights obtain more data transmission resources.
For example, in the conventional bluetooth communication link transmission mode, when the traffic volume is large and the rate is high, the service transmission efficiency is reduced. When the queue data is very large and the link rate is high, there are many empty queues that do not need to be forwarded. Therefore, in the case that the above situation exists, by adopting the method of the application, the data addresses of the packet data output by the non-empty queue are built by adopting the queue to cache and store the service data when the service data is distributed, numbering the service data according to different services and adopting the polling algorithm, and the separate leaving queue (the transmission queue DQ) is used for storing the data addresses of the packet data output by the non-empty queue. Sensors for different physical parameters can be distinguished as different services.
Although the polling scheduling method gives each non-empty traffic flow queue the same service opportunity to a certain extent, when the traffic volume of some queues is higher and heavier, it is difficult to get more transmission opportunities, and the success rate of communication of the transmission signal is lower. And the weighted polling scheduling algorithm gives higher weight W under the same service flow, so that transmission resources matched with the weight can be obtained, for example, W pieces of packet data of the queue are transmitted, and different service amounts are distributed to different queues according to the light and heavy urgency, so that the load balancing under high service amount is achieved. By setting a smooth weighted polling algorithm, continuous service information acquisition is realized, if the environment state is unchanged, many repeated messages can be generated to cause data redundancy, so that the transmission efficiency is reduced, and a message caching mechanism, a sleep mode and the like are set.
It should be noted that, according to the data transmission rule of the bluetooth link, the sensor service is temporary, and each bluetooth data acquisition service output end needs to configure a buffer memory and also needs to perform service scheduling. In order to improve stability and efficiency of bluetooth data transmission, conventional polling scheduling may give each non-null service the same service opportunity, but when the traffic of some queues is heavy or the transmission success rate of bluetooth signals is low, it is difficult to obtain more transmission opportunities. Therefore, a weighted polling system is added on the basis of polling to enable each non-empty service flow queue, each FQ (service flow) has an integral weight Wi associated with the non-empty service flow queue, and when the service is served to the queue i, wi-block services of the queue are sent, so that different queues are improved to distribute different terminal service volumes.
Further, the weighted round robin scheduling is responsible for scheduling the next data frame transmission by adding two outgoing queues (preset transmission queues), one in an active state and the other in a standby state, and a preset weight value (initial weight) stored by a weight counter. When the service requirement is large, a counter starts a weight when a round of service flow starts, and then two non-empty queues are alternately serviced according to the weight value.
The invention provides a data polling scheduling method, which comprises the following steps: determining a data transmission state of each data acquisition device, wherein the data transmission state is used for reflecting the data transmission success rate when the data acquisition devices transmit data to the wireless communication device, each data acquisition device corresponds to a service flow queue, each service flow queue comprises a plurality of packet data and data addresses of each packet data, and the data acquisition devices are in wireless communication connection with the wireless communication device; determining an initial weight of the service flow queue by utilizing the data transmission success rate, wherein the initial weight is inversely proportional to the data transmission success rate; and carrying out weighted polling scheduling processing on the packet data of each service flow queue according to the initial weight and the data address of each service flow queue, and determining a target transmission queue of the current data frame. By the method, the initial weight of the service flow queue can be obtained according to the data transmission state of the data acquisition device, and then the weighted polling scheduling processing is carried out through the initial weight, so that the target transmission queue of the current data frame is obtained, the weighted polling scheduling according to the weight of the initial weight is realized when the traffic volume is abnormal, the load balancing is realized, and the service transmission efficiency is improved.
Referring to fig. 4, fig. 4 is another flowchart of a method for scheduling polling of data according to an embodiment of the present invention, where the method shown in fig. 4 includes the following steps:
401. determining a data transmission state of each data acquisition device, wherein the data transmission state is used for reflecting the data transmission success rate when the data acquisition devices transmit data to the wireless communication device, each data acquisition device corresponds to a service flow queue, each service flow queue comprises a plurality of packet data and data addresses of each packet data, and the data acquisition devices are in wireless communication connection with the wireless communication device;
it should be noted that, the content of step 401 is similar to that of step 201 shown in fig. 2, and for avoiding repetition, reference may be made to the content of step 201 shown in fig. 2.
In a possible implementation, the wireless communication apparatus of the apparatus includes a bluetooth device, and step 401 may include steps P01-P03:
p01, controlling the Bluetooth device to send out a broadcast calling signal;
p02, receiving a recall reply result of the broadcast recall signal returned by each data acquisition device, wherein the recall reply result at least comprises the equipment type, the signal strength and the signal-to-noise ratio of the data acquisition device;
And P03, determining the data transmission state of each data acquisition device according to the equipment type, the signal strength and the signal-to-noise ratio.
It should be noted that, in order to improve accuracy of determining the data transmission state, the bluetooth device may be controlled to send a broadcast recall signal in real time, so as to determine the data transmission state, where the broadcast recall signal is used to obtain a broadcast recall result of signal transmission characteristics related to signal transmission, such as a device type, a signal strength, a signal to noise ratio, and the like, of the data acquisition device, and a recall reply result of the broadcast recall signal returned by each data acquisition device is received, where the broadcast recall result returned by each data acquisition device includes at least a recall reply result of a signal quantity of the data acquisition device, such as the device type, the signal strength, the signal to noise ratio, and the like, which can reflect the communication state of the bluetooth sensor; and determining the data transmission state of each data acquisition device according to the communication state signal quantity such as the equipment type, the signal strength, the signal-to-noise ratio, the related communication success rate and the like.
And the parameters such as the type of the sensor equipment, the signal strength, the signal to noise ratio and the like are combined to measure the success rate of Bluetooth communication, the initial weight is correspondingly set, the communication success rate is low, the high weight is given, the corresponding polling frequency is increased, and the overall analog quantity acquisition effect of the terminal is improved.
In one round of service period, different state quantities of different sensors, such as equipment types, signal strength RSSI, signal to noise ratio and the like, are identified through broadcasting recall of Bluetooth equipment, recall reply results are written into a terminal Bluetooth equipment storage area through state words, initial weights are set according to signal emission states of different acquisition devices, if signal intensity 4 and signal to noise ratio 10db are represented in data recalled by B equipment (temperature sensor) signals, the signal communication success rate is lower, the B equipment service initial weights are set to be the largest, and therefore, acquisition times of the B equipment are correspondingly increased during polling scheduling of the round of service period, and the purposes of balanced acquisition and omnibearing data acquisition are achieved.
402. Determining an initial weight of the service flow queue by utilizing the data transmission success rate, wherein the initial weight is inversely proportional to the data transmission success rate;
it should be noted that, the step 402 is similar to the step 202 shown in fig. 2, and for avoiding repetition, reference may be made to the step 202 shown in fig. 2.
In one possible implementation, the initial weight is the sum of the static weight and the dynamic weight, and step 402 may include steps I01-I02:
I01, utilizing the data transmission success rate to truly obtain the static weight, wherein the static weight is inversely proportional to the data transmission success rate;
and I02, determining the initial weight by utilizing the static weight and a preset dynamic weight.
It should be noted that, in order to ensure accuracy of the initial Weight during each polling scheduling of the current data frame, the initial Weight W is divided into two parts, i.e., a static Weight and a dynamic Weight currentWeight, where the initial Weight is a sum of the static Weight and the dynamic Weight, the static Weight is not changed due to each polling scheduling, the static Weight is inversely proportional to the success rate of data transmission, the success rate of data transmission is actually used, and the dynamic Weight is changed with each polling scheduling, so that the initial Weight changes once per polling scheduling, the dynamic Weight of the first polling scheduling may be preset, and the preset value of the dynamic Weight may be 0.
In one possible implementation, the initial value of the dynamic weight may not be set to 0, and the preset value of the dynamic weight may be set according to the requirements of the traffic requests of different traffic queues, so the method further includes the following steps U01-U02:
U01, counting the service flow request quantity of different service flows, wherein the service flow request quantity is used for reflecting the data reading requirement of the service flows;
and U02, determining a preset value of the second weight according to the service flow request quantity.
It should be noted that, different service flow requests have different requirements, so different data acquisition devices may be configured with different dynamic weights, and initial dynamic weights may be allocated according to different service requests. Specifically, counting the service flow request quantity of different service flows, wherein the service flow request quantity is used for reflecting the data reading requirement of the service flows; and determining a preset value of the second weight according to the service flow request quantity. For example, if the number of service flow requests is large, the data reading requirement of the service flow is high, and then the preset value (i.e., the initial value) of the dynamic weight of the corresponding service flow queue can be set to a higher value; the number of service flow requests is small, so that the data reading requirement of the service flow is small, and the preset value (i.e. the initial value) of the dynamic weight of the corresponding service flow queue can be set to be a lower value. The distance is not particularly limited herein.
403. Determining a target service flow queue corresponding to the maximum initial weight in the initial weights;
404. reading packet data corresponding to a first data address in the target service flow queue to a preset transmission queue of a current data frame, updating the target service flow queue, and recording polling times i=i+1;
it should be noted that, in order to ensure the service transmission efficiency, the present application performs data reading of each polling scheduling according to the size of the initial weight, so as to obtain a target transmission queue of the current data frame, specifically, since the initial weight is inversely proportional to the data transmission success rate and the data transmission success rate is inversely proportional to the data volume pressure, the target service flow queue corresponding to the maximum initial weight in each initial weight is first determined, the target service flow queue with the maximum data pressure is obtained, the data reading of the current polling scheduling is performed, that is, packet data of the target service flow queue is transmitted to a preset transmission queue, and since the data is already transmitted to the preset transmission queue, the target service flow queue needs to be updated, and the polling times i+1 are recorded. The initial value of the polling number i may be 0 or 1, etc., and is not limited herein.
405. And carrying out initial weight updating processing by using the maximum initial weight and the initial weight of each service flow queue, determining the updated initial weight of each service flow queue, and returning to the step of executing the target service flow queue corresponding to the maximum weight in the determined initial weight until the polling frequency i is equal to a preset polling frequency threshold value, thereby obtaining the target transmission queue of the current data frame.
Further, since the data of the target traffic queue will change after each polling schedule, the initial weight of the next polling schedule needs to be updated, in this embodiment, the static weight is always unchanged and the dynamic weight dynamically changes as the polling times increase in the polling schedule period of one data frame. Specifically, the initial weight updating process is performed by using the maximum initial weight and the initial weights of the service flow queues, the updated initial weights of the service flow queues are determined, and the step of executing the target service flow queues corresponding to the maximum weights in the initial weights is returned until the polling frequency i is equal to a preset polling frequency threshold, so as to obtain a target transmission queue of the current data frame, where the preset polling frequency threshold is a maximum polling frequency value in a polling scheduling period corresponding to one data frame, and may be 10 times or 20 times, and the like, and may be set based on actual conditions.
In one possible implementation, step 405 may include steps Y01-Y02:
y01, utilizing the maximum initial weight, the static weight sum of each initial weight and the dynamic weight updating processing of the target service flow queue, and determining the updated dynamic weight of the target service flow queue, wherein the updated dynamic weight is the difference between the maximum initial weight and the static weight sum;
and Y02, carrying out initial weight updating processing by using the updated dynamic weight, the dynamic weights of the rest business flow queues except the target business flow queue and the static weight, and determining the updated initial weight of each business flow queue.
Since only the packet data address of the target traffic flow queue corresponding to the maximum initial weight is output per polling, after each data output, the dynamic weight of the target traffic flow queue needs to be updated first through step Y01, and the update of the dynamic weight of the target traffic flow queue may be the difference between the maximum initial weight and the sum of the weights of the initial weights. And finally, performing initial weight updating processing by using the updated dynamic weights, the dynamic weights of the rest business flow queues except the target business flow queue and the static weights in the step Y02, and determining the updated initial weights of the business flow queues.
Continuing with fig. 3 as an example, the four traffic queues are traffic queues FQ1 to FQ4, respectively, where the dynamic weights currentWeight are all 0, and the static weights weight are respectively: [ 3,5,1,1 ];
further, the initial weights w=dynamic weights currentweight+static weights weight, so the initial weights W are respectively: since the static weight is unchanged, [ 3,5,1,1 ], the judgment of the weight size can also be regarded as the judgment of the dynamic weight size, wherein the dynamic weight currentweight=dynamic weight currentweight+static weight, and since the initial dynamic weight is 0, the dynamic weight currentWeight is [ 3,5,1,1 ], and at this time, the maximum initial weight MaxcurrentWeight is 5, so that the target traffic queue is the traffic queue FQ2;
so the first time the poll is scheduled: outputting the packet data B1 of FQ2, further updating the dynamic Weight currentWeight of the packet data B1, enabling the dynamic Weight currentWeight to be the maximum initial Weight Maxcurrentweight-static Weight and sum (Weight) =5- (3+5+1+1) = -5, wherein the updated dynamic Weight is [ 5 ], and the dynamic Weight of each service flow queue temporarily becomes [ 3, -5,1,1 ];
further, the initial weight of each service flow queue is updated, namely, the initial weight W=dynamic weight currentweight+static weight; that is, the initial weight of FQ1 is updated to [ 3+3=6 ], the initial weight of FQ2 is updated to [ 5) +5=0 ], the initial weight of FQ3 is updated to [ 1+1=2 ], the initial weight of FQ4 is updated to [ 1+1=2 ], and finally, the initial weight W is [ 6,0,2,2 ].
Further, during the second polling scheduling, the target service flow queue is FQ1, the above process is repeated, and finally, after the data transmission, the initial weight W is [ 1,5,3,3 ]. And the like until the maximum value of the polling times is reached, ending the data polling scheduling of the current data frame.
For example, referring to table 1, table 1 shows the update process of each initial Weight of the four traffic flow queues under the condition that the preset polling frequency threshold is 10 times, the initial dynamic Weight currentWeight in table 1 is 0, the static Weight is 3,5,1, max (currentWeight) flag maximum initial Weight, since the static Weight is unchanged, the maximum Weight essence can also be regarded as the maximum of the dynamic Weight, the update of the initial Weight can also be regarded as the update of the dynamic Weight, result represents the packet data of the target traffic flow queue, sum (Weight) represents the sum of the static weights, and table 1 is as follows:
TABLE 1
Note that, the initial state: a (3), B (5), C (1), D (1), wherein a: an electrical signal; b: a temperature; c: pressure; d: traffic, it can be seen that when 10 polls are performed, the next cycle starts, so the traffic after one round of polling should be: and the BABCABDBAB frame is used for obtaining a target transmission queue of the current data frame, wherein the service duty ratio of the B temperature is the maximum. And then data output can be dynamically realized according to the light and heavy urgency of the initial weight, finally 5 packet data B, 3 packet data A, 5 packet data C and 5 packet data D of the target transmission queue are realized, the weight ratio A: B: C: D=3:5:1:1 of each service is realized, the maximum data acquisition amount of a certain collector which is focused on is achieved, the dynamic weight distribution can be adjusted as required, the purpose of balancing service loads is achieved, and the acquisition stability of the Bluetooth sensor of the terminal is improved.
In a possible implementation manner, the data acquisition device is configured to acquire operation data of the electrical device, and then the method further includes: uploading the target transmission queue to a preset upper computer, wherein the upper computer is used for carrying out data analysis according to the target transmission queue and determining the running state of the power equipment.
It can be understood that after the target transmission queue is obtained, the target transmission queue can be uploaded to a preset upper computer, so that when the collection object is the power equipment, data analysis is performed on the operation data of the collection object, and the operation state is monitored. Early warning can be carried out when the operation state is abnormal. And the system is different from carrier communication of traditional data collection, and adopts a Bluetooth statistical analysis model for analysis, wherein the running state of the station area is analyzed by recording the environment quantity of each Bluetooth sensor, and the potential safety hazards of the running of the station area are checked by each item of data. The Bluetooth system is used for networking to collect characteristic state information of each sensor device, such as temperature, humidity and environment operation safety state. Bluetooth communication technology supports the mobile internet. Each acquisition module receives temperature data through a Bluetooth spiral antenna, is connected with a serial port of an upper computer through a data bus, and uploads various processed parameter data to the upper computer. For example, after the temperature parameters are wirelessly networked by the wireless network communication module, the temperature receiving module and the plurality of temperature acquisition modules are wirelessly networked and transmitted in respective service flows.
Further, each counter initializes its weight in order to begin transmitting a new data frame. When a new data packet arrives, the number of the queue is written to the tail if it is the first packet in the queue and the queue counter is zero. If it is not the first packet in the queue, its memory address is simply added to the corresponding traffic flow queue tail.
The invention provides a data polling scheduling method, which comprises the following steps: determining a data transmission state of each data acquisition device, wherein the data transmission state is used for reflecting the data transmission success rate when the data acquisition devices transmit data to the wireless communication device, each data acquisition device corresponds to a service flow queue, each service flow queue comprises a plurality of packet data and data addresses of each packet data, and the data acquisition devices are in wireless communication connection with the wireless communication device; determining an initial weight of the service flow queue by utilizing the data transmission success rate, wherein the initial weight is inversely proportional to the data transmission success rate; determining a target service flow queue corresponding to the maximum initial weight in the initial weights; reading packet data corresponding to a first data address in a target service flow queue to a preset transmission queue of a current data frame, updating the target service flow queue, and recording polling times i=i+1; and carrying out initial weight updating processing by using the maximum initial weight and the initial weight of each service flow queue, determining the updated initial weight of each service flow queue, and returning to the step of executing the target service flow queue corresponding to the maximum weight in the determined initial weights until the polling times i are equal to a preset polling times threshold value, so as to obtain the target transmission queue of the current data frame. By the method, the weighted polling scheduling of the service flow queue can be realized, the initial weight of the service flow queue is obtained according to the data transmission state of the data acquisition device, the weighted polling scheduling processing is further carried out through the initial weight, the target transmission queue of the current data frame is obtained, the weighted polling scheduling according to the light weight and the heavy weight of the initial weight is realized when the traffic volume is abnormal, the load balancing is realized, and the service transmission efficiency is improved.
Referring to fig. 5, fig. 5 is a block diagram illustrating a data polling scheduling apparatus according to an embodiment of the present invention, where the apparatus shown in fig. 5 includes:
the state determination module 501: the method comprises the steps that the method is used for determining the data transmission state of each data acquisition device, the data transmission state is used for reflecting the data transmission success rate when the data acquisition devices transmit data to the wireless communication device, each data acquisition device corresponds to one service flow queue, each service flow queue comprises a plurality of packet data and data addresses of each packet data, and the data acquisition devices are in wireless communication connection with the wireless communication device;
weight determination module 502: the method comprises the steps of determining initial weights of the service flow queues by utilizing the data transmission success rate, wherein the initial weights are inversely proportional to the data transmission success rate;
the polling scheduling module 503: and the target transmission queue of the current data frame is determined by carrying out weighted polling scheduling processing on the packet data of each service flow queue according to the initial weight of each service flow queue and the data address.
It should be noted that the functions of each module in the apparatus shown in fig. 5 are similar to those of the method shown in fig. 2, and for avoiding repetition, reference may be made to the details of the steps of the method shown in fig. 2.
The invention provides a data polling scheduling method, which comprises the following steps: a state determination module: the data transmission state is used for reflecting the data transmission success rate when the data acquisition device transmits data to the wireless communication device, each data acquisition device corresponds to a service flow queue, each service flow queue comprises a plurality of packet data and data addresses of the packet data, and the data acquisition device is in wireless communication connection with the wireless communication device; and a weight determining module: the method comprises the steps of determining initial weight of a service flow queue by utilizing a data transmission success rate, wherein the initial weight is inversely proportional to the data transmission success rate; and a polling scheduling module: and the target transmission queue of the current data frame is determined by carrying out weighted polling scheduling processing on the packet data of each service flow queue according to the initial weight of each service flow queue and the data address. By the method, the initial weight of the service flow queue can be obtained according to the data transmission state of the data acquisition device, and then the weighted polling scheduling processing is carried out through the initial weight, so that the target transmission queue of the current data frame is obtained, the weighted polling scheduling according to the weight of the initial weight is realized when the traffic volume is abnormal, the load balancing is realized, and the service transmission efficiency is improved.
FIG. 6 illustrates an internal block diagram of a computer device in one embodiment. The computer device may specifically be a terminal or a server. As shown in fig. 6, the computer device includes a processor, a memory, and a network interface connected by a system bus. The memory includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system, and may also store a computer program which, when executed by a processor, causes the processor to implement the method described above. The internal memory may also have stored therein a computer program which, when executed by a processor, causes the processor to perform the method described above. It will be appreciated by those skilled in the art that the structure shown in fig. 6 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method shown in fig. 2 or fig. 4.
In one embodiment, a computer-readable storage medium is provided, storing a computer program that, when executed by a processor, causes the processor to perform the steps of the method shown in fig. 2 or fig. 4.
Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (10)
1. A method for scheduling polling of data, the method comprising:
determining a data transmission state of each data acquisition device, wherein the data transmission state is used for reflecting the data transmission success rate when the data acquisition devices transmit data to the wireless communication device, each data acquisition device corresponds to a service flow queue, each service flow queue comprises a plurality of packet data and data addresses of each packet data, and the data acquisition devices are in wireless communication connection with the wireless communication device;
Determining an initial weight of the service flow queue by utilizing the data transmission success rate, wherein the initial weight is inversely proportional to the data transmission success rate;
and carrying out weighted polling scheduling processing on the packet data of each service flow queue according to the initial weight of each service flow queue and the data address, and determining a target transmission queue of the current data frame.
2. The method of claim 1, wherein said performing a weighted round robin scheduling of packet data for each of said traffic queues based on an initial weight of each of said traffic queues and said data address, determining a target transmission queue for a current data frame, comprises:
determining a target service flow queue corresponding to the maximum initial weight in the initial weights;
reading packet data corresponding to a first data address in the target service flow queue to a preset transmission queue of a current data frame, updating the target service flow queue, and recording polling times i=i+1;
and carrying out initial weight updating processing by using the maximum initial weight and the initial weight of each service flow queue, determining the updated initial weight of each service flow queue, and returning to the step of executing the target service flow queue corresponding to the maximum weight in the determined initial weight until the polling frequency i is equal to a preset polling frequency threshold value, thereby obtaining the target transmission queue of the current data frame.
3. The method of claim 2, wherein the determining the initial weight of the traffic queue using the data transmission success rate if the initial weight is a sum of a static weight and a dynamic weight comprises:
utilizing the data transmission success rate to truly the static weight, wherein the static weight is inversely proportional to the data transmission success rate;
and determining the initial weight by utilizing the static weight and a preset dynamic weight.
4. The method of claim 3, wherein said performing initial weight update processing using said maximum initial weight and initial weights of each of said traffic queues, determining updated initial weights of each of said traffic queues, comprises:
determining updated dynamic weights of the target service flow queues by utilizing the maximum initial weights, static weights of the initial weights and dynamic weight updating processing of the target service flow queues, wherein the updated dynamic weights are differences between the maximum initial weights and the static weights;
and carrying out initial weight updating processing by using the updated dynamic weights, the dynamic weights of the rest business flow queues except the target business flow queue and the static weights, and determining the updated initial weights of the business flow queues.
5. The method of claim 1, wherein the wireless communication device comprises a bluetooth device, and wherein determining the data transmission status of each data acquisition device comprises:
controlling the Bluetooth equipment to send out a broadcast calling signal;
receiving a recall reply result of the broadcast recall signal returned by each data acquisition device, wherein the recall reply result at least comprises the equipment type, the signal strength and the signal-to-noise ratio of the data acquisition device;
and determining the data transmission state of each data acquisition device according to the equipment type, the signal strength and the signal-to-noise ratio.
6. A method according to claim 3, wherein the method further comprises:
counting the service flow request quantity of different service flows, wherein the service flow request quantity is used for reflecting the data reading requirement of the service flows;
and determining a preset value of the second weight according to the service flow request quantity.
7. The method of claim 1, wherein the data acquisition device is configured to acquire operational data of the electrical device, and the method further comprises:
uploading the target transmission queue to a preset upper computer, wherein the upper computer is used for carrying out data analysis according to the target transmission queue and determining the running state of the power equipment.
8. A data polling scheduling apparatus, the apparatus comprising:
a state determination module: the method comprises the steps that the method is used for determining the data transmission state of each data acquisition device, the data transmission state is used for reflecting the data transmission success rate when the data acquisition devices transmit data to the wireless communication device, each data acquisition device corresponds to one service flow queue, each service flow queue comprises a plurality of packet data and data addresses of each packet data, and the data acquisition devices are in wireless communication connection with the wireless communication device;
and a weight determining module: the method comprises the steps of determining initial weights of the service flow queues by utilizing the data transmission success rate, wherein the initial weights are inversely proportional to the data transmission success rate;
and a polling scheduling module: and the target transmission queue of the current data frame is determined by carrying out weighted polling scheduling processing on the packet data of each service flow queue according to the initial weight of each service flow queue and the data address.
9. A computer readable storage medium storing a computer program, which when executed by a processor causes the processor to perform the steps of the method according to any one of claims 1 to 7.
10. A computer device comprising a memory and a processor, wherein the memory stores a computer program which, when executed by the processor, causes the processor to perform the steps of the method of any of claims 1 to 7.
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