A gateway central control scheduling system and method

Abstract

The application relates to the technical field of gateway scheduling, and discloses a gateway central control scheduling system and method, which comprises an online device receiving module, a first detection module, an instruction determining module, a data acquisition module, a processing module and a distribution judgment module. The data acquisition module is used for acquiring the device type of the online device, the required applied network bandwidth and the running state information after the corresponding instruction information is determined, and generating corresponding online device basic information. The processing module is used for quantitatively processing the online device basic information into corresponding numerical values and then transmitting the numerical values into the gateway. The distribution judgment module is used for performing corresponding decryption on the numerical values received by the gateway, performing distribution judgment of the network resources of the current gateway to the online device according to the decrypted data, the instruction information and the current gateway distribution data retrieved from the database, generating corresponding distribution results, and distributing the corresponding network resources to the online device according to the distribution results.

Description

TECHNICAL FIELD

[0001] The present application relates to the gateway scheduling technical field, and in particular to a gateway central control scheduling system and method. BACKGROUND

[0002] With the continuous progress of science and technology, the home is gradually approaching to intelligent, and the gateway corresponding to the smart home is the key to the home intelligent, and the control of the system is realized through the gateway.

[0003] The gateway used in the current market only has general machine connection, or passively obtains some data information, and cannot make a judgment on the state of the front-end device, the used network resource, and the use scene or environment of the current device, and cannot obtain the state information (running state, battery capacity, network state, power consumption, health state) of the node running, and the gateway cannot effectively manage the front-end node and allocate the resource state. SUMMARY

[0004] The present application aims to provide a gateway central control scheduling system and method, which can solve the problem that the gateway corresponding to the home intelligent in the prior art cannot effectively manage the device on the front-end node and allocate the resource state.

[0005] To achieve the above-mentioned purpose, the technical scheme adopted by the present application is as follows: a gateway central control scheduling system, comprising:

[0006] An online device receiving module is configured to receive the joining application information of the online device applying to join the gateway;

[0007] A first detection module is configured to check whether the online device is a legal device after receiving the joining application information of the online device;

[0008] An instruction determination module is configured to issue a corresponding authentication certificate when the online device is a legal device, and determine the instruction information of the online device applying to join the gateway;

[0009] A data acquisition module is configured to acquire the device type of the current online device, the required network bandwidth to be applied for, and the running state information after determining the corresponding instruction information, and generate corresponding online device basic information;

[0010] A processing module is configured to quantitatively process the acquired online device basic information into corresponding numerical values and then transmit the numerical values into the gateway;

[0011] The distribution judgment module is configured to, on the gateway, decrypt the numerical value received by the gateway, and according to the decrypted data, the instruction information, and the current gateway distribution data retrieved from the database, make a distribution judgment of the network resources of the current gateway to the online device, generate a corresponding distribution result, and allocate the corresponding network resources to the online device according to the distribution result.

[0012] The principle and advantages of the present scheme are as follows: in the present scheme, the online device sends the corresponding joining application information when applying to join the gateway, so that the gateway receiving the joining application information of the online device checks whether the online device is a legal device, and if not, the joining of the gateway is not allowed, and the application information is directly rejected; if it is a legal device, the online device is issued with an authentication certificate, and the instruction information of the online device applying to join the gateway is determined, and the basic information of the online device is obtained, so that the state and basic information of the online device are obtained.

[0013] The subsequent encoding and decryption of the basic information of the online device realize uploading of the obtained data to the gateway, and the data is judged and compared on the gateway, and the current gateway distribution data is obtained, so as to realize the distribution of the network resources of the gateway corresponding to the online device, and the effective distribution of the resources of the device is realized.

[0014] Preferably, as an improvement, the distribution judgment module comprises:

[0015] The decryption module is configured to decrypt the numerical value received by the gateway and restore the information;

[0016] The comparison module is configured to compare the restored information with the instruction information, and if the comparison is consistent, the current online device is determined to be a usable device;

[0017] The retrieval module is configured to, after determining that the current online device is a usable device, retrieve the current gateway distribution data corresponding to the current gateway from the database; the current gateway distribution data comprises the current network bandwidth surplus, the other device information corresponding to the other nodes applying to join the gateway, and the total network bandwidth;

[0018] The first judging module is configured to judge whether the current applied network bandwidth is less than or equal to the current network bandwidth margin according to the current gateway allocation data and the network bandwidth applied by the device in the restored information.

[0019] The first allocation module is configured to, when the judging result is that the current applied network bandwidth is less than or equal to the current network bandwidth margin, issue the corresponding device online requirement to the online device, wherein the device online requirement comprises a transmission channel number, a bandwidth size and a data synchronization mode; and the online device performs online operation of the gateway according to the device online requirement.

[0020] The second judging module is configured to, when the judging result is that the current applied network bandwidth is greater than the current network bandwidth margin, calculate a percentage between a value corresponding to the current applied network bandwidth exceeding the current network bandwidth margin and the total network bandwidth, obtain a corresponding exceeding bandwidth percentage value, and judge whether the current exceeding bandwidth percentage value is less than or equal to a preset threshold value.

[0021] The second allocation module is configured to, when it is judged that the current exceeding bandwidth percentage value is less than or equal to the preset threshold value, issue the corresponding device online requirement to the online device without affecting other devices.

[0022] The optimal module is configured to, when it is judged that the current exceeding bandwidth percentage value is greater than the preset threshold value, obtain, from a database, basic information of other devices corresponding to other nodes currently applying to join the gateway and necessary degree information corresponding to each device, generate an optimal network bandwidth allocation scheme for the other devices and the online device to connect to the gateway based on an improved genetic algorithm.

[0023] The third allocation module is configured to allocate the current total network bandwidth corresponding to the gateway to the other devices and the online device according to the optimal network bandwidth allocation scheme, and issue corresponding online device requirements.

[0024] Beneficial effects: In the scheme, in order to reasonably allocate the network bandwidth on the gateway, the corresponding values are decrypted after being received, so as to realize restoration of the school, and through comparison between the restored information and the instruction information, it can be quickly determined whether the online device currently applying to join is an available device, i.e., the device meets the basic requirements for joining the gateway. Then, the current gateway allocation data corresponding to the current gateway is called from the database, and through the data, the current network bandwidth margin, the number of connected nodes and the corresponding other device information, and the total network bandwidth and other information can be judged.

[0025] Then the network bandwidth required by the current online device can be compared with the current network bandwidth margin, and corresponding bandwidth allocation is performed according to the comparison result. Specifically, there are three cases. In one case, the current network margin is relatively large, so the device online requirement can be directly issued. In another case, the excess bandwidth ratio is less than or equal to the preset threshold, which is acceptable for the entire gateway. In this case, the device online requirement can be issued without affecting the operation of other devices. In the last case, the excess bandwidth ratio is greater than the preset threshold, so a large amount of bandwidth may be exceeded. In this case, the optimal bandwidth allocation scheme is generated based on the improved genetic algorithm according to the basic information of other devices connected to the current gateway and the online device information corresponding to the current online device, so as to achieve optimal bandwidth allocation. Through the optimal allocation scheme, the linkage between devices is greatly improved, and the gateway bandwidth resources are reasonably utilized.

[0026] Preferably, as an improvement, the optimal module comprises:

[0027] The calling module is configured to, when it is determined that the excess bandwidth ratio is greater than the preset threshold, call the basic information of other devices corresponding to other nodes applying to join the gateway from the database.

[0028] The service set determination module is configured to determine a service set of the other devices and the online device connecting to the gateway and the network bandwidth allocation path of the gateway to the service set according to the other devices corresponding to the current gateway and the online device.

[0029] The constraint condition determination module is configured to determine the constraint condition corresponding to each service in the service set.

[0030] The objective function establishment module is configured to establish the objective function corresponding to each service in the service set.

[0031] The mathematical model module is configured to realize multi-objective optimization of the network bandwidth allocation path in the service set based on the improved genetic algorithm and the determined objective function and constraint condition.

[0032] The allocation optimization module is configured to optimize the network bandwidth allocation path scheme of the service set according to the result of multi-objective optimization.

[0033] Beneficial effects: By determining the constraint condition and the objective function, the accuracy of optimization is greatly improved.

[0034] Preferably, as an improvement, the mathematical model module comprises:

[0035] The first screening module is configured to randomly generate an initial population with a size of N, individuals of the initial population being network bandwidth allocation paths corresponding to the selected other devices and the online device, and to perform judgment screening on the individuals of the initial population by using constraint conditions, the constraint conditions including a network bandwidth total constraint condition and an allocation repetition constraint condition; if the constraint conditions are met, the corresponding network bandwidth allocation path is a feasible solution, and if the constraint conditions are not met, the corresponding network bandwidth allocation path is an infeasible solution;

[0036] The fitness calculation module is configured to perform first fitness and second fitness calculation on the screened population respectively.

[0037] The selection module is configured to, within a first preset number of iterations, select a population with a first fitness greater than or equal to a first fitness threshold according to the first fitness of the population, and select the first three populations with the largest second fitness from the population that is eliminated at this time, and save the first three populations to a backup library.

[0038] After the second preset number of iterations is exceeded, the population at this time and the population in the backup library are combined to form a new population, and a population with a second fitness greater than a preset second fitness threshold is selected from the population at this time.

[0039] The crossover and mutation module is configured to obtain a child population by using a genetic algorithm to cross and mutate the selected population.

[0040] The loop module is configured to continue to execute the fitness calculation module after the child population is obtained, until a preset number of iterations is met.

[0041] The output module is configured to output the child population as a set of optimal solutions of multi-objective optimization.

[0042] Advantages: In the scheme, the constraint conditions, i.e., the network bandwidth total constraint condition and the allocation repetition constraint condition, are used to realize judgment on whether each individual in the initial population meets the requirements, i.e., whether the total bandwidth corresponding to the network bandwidth allocation of all devices in the population is excessive, and whether there is a problem of repeated allocation, i.e., each device can only be allocated once and cannot be repeated, so as to realize the refinement and preliminary screening of the initial population, make the initial population more excellent, and greatly increase the globality of the initial population.

[0043] When selecting the population, the first fitness of the population is mainly investigated within a first preset number of iterations, that is, the influence degree of the network bandwidth allocated to each device on the use of each device in the current time period is calculated and judged to obtain a population with a good corresponding use influence degree, and then whether the network bandwidth allocated to the population is wasted and the waste amount is judged to realize the screening of the population and greatly improve the accuracy and effectiveness of the population screening.

[0044] Preferably, as an improvement, the first fitness is calculated as follows:

[0045]

[0046]

[0047] D1 is the sum of the influence degrees of each device in the initial population, X i is the influence degree of the network bandwidth allocated to device i on the use of device i at the current time, and f1 is the first fitness.

[0048] Beneficial effect: The first fitness is screened according to the device influence degree, which greatly reduces the influence of the allocated network bandwidth on the device.

[0049] Preferably, as an improvement, the second fitness is calculated as follows:

[0050]

[0051]

[0052] D2 is the sum of the waste degrees of the network bandwidth allocated to each device in the initial population, Y j is the waste degree of the network bandwidth allocated to device j on the use of device j at the current time, and f2 is the second fitness.

[0053] Beneficial effect: The second fitness is screened according to the waste degree, which greatly avoids waste after allocation and ensures that the selected allocation scheme has a small waste degree.

[0054] The application also provides a gateway central control scheduling method, comprising the following steps:

[0055] S1, receiving the joining application information of an online device applying to join the gateway;

[0056] S2, after receiving the joining application information of the online device, the gateway checks whether the online device is a legal device;

[0057] S3, when the online device is a legal device, issuing a corresponding authentication certificate, and determining the instruction information for the online device to apply to join the gateway;

[0058] S4, after determining the corresponding instruction information, obtaining the device type of the current online device, the network bandwidth required to be applied for, and the running state information, and generating corresponding online device basic information;

[0059] S5, quantizing the obtained online device basic information into corresponding numerical values and transmitting them into the gateway;

[0060] S6, on the gateway, decrypting the numerical values received by the gateway, and according to the decrypted data, the instruction information, and the current gateway allocation data retrieved from the database, making a network resource allocation judgment for the online device, generating a corresponding allocation result, and allocating the corresponding network resource to the online device according to the allocation result. BRIEF DESCRIPTION OF DRAWINGS

[0061] Figure 1 The logic block diagram of the gateway central control scheduling system in the first embodiment of the application.

[0062] Figure 2 The logic block diagram of the allocation judgment module in the first embodiment of the application.

[0063] Figure 3 The logic block diagram of the optimal module in the first embodiment of the application.

[0064] Figure 4 The logic block diagram of the mathematical model module in the first embodiment of the application.

[0065] Figure 5 The flow chart of the gateway central control scheduling method in the first embodiment of the application. DETAILED DESCRIPTION

[0066] The following will be further described in detail through specific embodiments:

[0067] The embodiment is basically as shown in the accompanying drawings: a gateway central control scheduling system, comprising: Figure 1

[0068] An online device receiving module for receiving the joining application information of the online device applying to join the gateway.

[0069] ​The first detection module is configured to check whether the online device is a legal device after receiving the joining application information of the online device; in the judgment of whether the online device is a legal device, the device ID and the device type ID of each device are mainly used, the legal ID is placed in the corresponding server position in advance, the received ID is compared, and if the comparison is successful, the online device is determined to be a legal device.

[0070] The instruction determination module is configured to determine the instruction information of the online device applying to join the gateway when the online device is a legal device, and issue the corresponding authentication certificate.

[0071] The data acquisition module is configured to acquire the device type of the current online device, the required network bandwidth to be applied for, and the running state information after the corresponding instruction information is determined, and generate the corresponding online device basic information.

[0072] The processing module is configured to quantitatively process the obtained online device basic information into a corresponding numerical value and then input the numerical value into the gateway; in this embodiment, specifically, the device type, the device bandwidth (which will be encoded according to the data image coding code stream, code rate, resolution), the device power, the node (AP connection number), the online state, and the running time are combined into an 18-bit byte number, which includes an encryption bit, a data synchronization bit, and a 2-bit reserved bit. Each index will be quantified into an index value, such as the device power, which is obtained by using a 12-bit AD acquisition port on the hardware (the AD acquisition value is 1 / 2 of the actual battery voltage, and the 12-bit AD measured voltage value = measured value / 4096*reference voltage; the actual voltage value = measured voltage value*2) to obtain a power value, which is then quantified into a two-bit ASICC character. The bandwidth calculation is combined in the above coding rule. According to the current H.265 video compression method, the file size (GBps) = code stream (Kbps) ÷ 8 x 3600 x daily recording time (hour) ÷ 1024 ÷ 1024: 720P: 1 Mbps; 1080P: 2 Mbps;... to obtain the data size, which is then quantified into a two-bit ASICC character combined in the above coding rule, and the remaining values are converted into corresponding ASICC characters according to the corresponding coding information rule.

[0073] The distribution judgment module is configured to, on the gateway, decrypt the value received by the gateway, and according to the decrypted data, the instruction information, and the current gateway distribution data retrieved from the database, make a distribution judgment of the network resources of the current gateway to the online device, generate a corresponding distribution result, and allocate the corresponding network resources to the online device according to the distribution result. In this embodiment, the decryption is specifically: first, the corresponding decoding channel number is obtained, and then the combination of data information is re-performed, so as to realize the restoration of the message.

[0074] As shown in Figure 2 , the distribution judgment module comprises:

[0075] The decryption module is configured to decrypt the value received by the gateway and restore the information.

[0076] The comparison module is configured to compare the restored information with the instruction information, and if the comparison is consistent, it is judged that the current online device is a usable device.

[0077] The retrieval module is configured to, after judging that the current online device is a usable device, retrieve the current gateway distribution data corresponding to the current gateway from the database; the current gateway distribution data comprises the current network bandwidth surplus, other device information corresponding to other nodes applying to join the current gateway, and the total network bandwidth.

[0078] The first judgment module is configured to, according to the current gateway distribution data and the network bandwidth applied by the device in the restored information, judge whether the current applied network bandwidth is less than or equal to the current network bandwidth surplus.

[0079] The first distribution module is configured to, if the judgment result is that the current applied network bandwidth is less than or equal to the current network bandwidth surplus, issue the corresponding device online requirement to the online device; the device online requirement comprises a transmission channel number, a bandwidth size, and a data synchronization mode; and the online device performs the online operation of the gateway according to the device online requirement.

[0080] The second judgment module is configured to, if the judgment result is that the current applied network bandwidth is greater than the current network bandwidth surplus, calculate the percentage between the value corresponding to the excess of the current applied network bandwidth over the current network bandwidth surplus and the total network bandwidth, obtain the corresponding excess bandwidth ratio value, and judge whether the current excess bandwidth ratio value is less than or equal to a preset threshold value; in this embodiment, the preset threshold value is 1% of the total network bandwidth.

[0081] The second distribution module is configured to, if it is judged that the current excess bandwidth ratio value is less than or equal to the preset threshold value, issue the corresponding device online requirement to the online device without affecting other devices.

[0082] An optimal module is configured to, when it is determined that the current bandwidth-occupying ratio exceeds the preset threshold, acquire, from a database, basic information of other devices corresponding to other nodes currently applying to join the gateway and necessity information corresponding to each device, and generate an optimal network bandwidth allocation scheme for the other devices and the current online device to connect to the gateway based on an improved genetic algorithm.

[0083] As shown in Figure 3 , the optimal module includes:

[0084] An invoking module is configured to, when it is determined that the current bandwidth-occupying ratio exceeds the preset threshold, invoke, from a database, basic information of other devices corresponding to other nodes currently applying to join the gateway.

[0085] A service set determination module is configured to determine, according to the other devices corresponding to the current gateway and the current online device, a service set of the other devices and the online device to connect to the gateway and a network bandwidth allocation path of the gateway.

[0086] A constraint condition determination module is configured to determine constraint conditions corresponding to each service in the service set.

[0087] A target function establishment module is configured to establish target functions corresponding to each service in the service set.

[0088] A mathematical model module is configured to, based on the improved genetic algorithm and the determined target functions and constraint conditions, realize multi-objective optimization of the network bandwidth allocation path in the service set.

[0089] As shown in Figure 4 , the mathematical model module includes:

[0090] A first screening module is configured to randomly generate an initial population with a size of N, the individual of the initial population being a network bandwidth allocation path corresponding to the selected other devices and the online device, and to judge and screen the individual of the initial population through constraint conditions, the constraint conditions including a total network bandwidth constraint condition and an allocation repetition constraint condition; if the constraint conditions are met, the corresponding network bandwidth allocation path is a feasible solution, and if the constraint conditions are not met, the corresponding network bandwidth allocation path is an infeasible solution.

[0091] An adaptability calculation module is configured to calculate a first adaptability and a second adaptability of the screened population respectively, the first adaptability calculation being as follows:

[0092]

[0093]

[0094] The D1 is a total influence degree of each device in the initial population, and the X iThe network bandwidth allocated to the device i has an influence on the use of the device i at the current time, f1 is a first fitness;

[0095] In the embodiment, the calculation formula of the influence of the network bandwidth allocated to the device i on the use of the device i at the current time is specifically:

[0096]

[0097] M i is the historical average network bandwidth of the device i at the current time, m i is the allocated network bandwidth of the gateway of the device i at the current time, and f d is the network bandwidth influence coefficient corresponding to the device i at the current time, in order to make the corresponding f d more real, in the embodiment, the corresponding network bandwidth influence coefficient is obtained by pre-statistics on a table according to the influence of the device i at the current time.

[0098] The second fitness is calculated as follows:

[0099]

[0100]

[0101] The D2 is the total waste degree of the network bandwidth allocated to each device in the initial population, and Y j is the waste degree of the network bandwidth allocated to the device j on the device j at the current time, and f2 is the second fitness;

[0102] In the embodiment, the calculation formula of the waste degree of the network bandwidth allocated to the device j on the device j at the current time is specifically:

[0103]

[0104] M i is the historical average network bandwidth of the device i at the current time, m i is the allocated network bandwidth of the gateway of the device i at the current time. In other embodiments of the application, in order to better calculate the waste degree, considering that when the network bandwidth of the device is allocated, the allocated network bandwidth at the current time is greater than the historical average network bandwidth, not all the excess network bandwidth is wasted, and there is still a part of the benefit, in order to more accurately calculate the real waste degree of each device, the excess network bandwidth calculated at this time and the excess benefit at this time are calculated to obtain the final waste value.

[0105] The selecting module is configured to select, within a first preset number of iterations, a population with a first fitness greater than or equal to a first fitness threshold according to the first fitness of the population, and select the first three populations with the second fitness from the population removed at this time and save them to a backup library;

[0106] After the second preset number of iterations is exceeded, the population at this time is combined with the population in the backup library to form a new population, and the population with a second fitness greater than a preset second fitness threshold is selected according to the second fitness of the population at this time;

[0107] The crossover and mutation module is configured to obtain a child population by crossing and mutating the selected population through a genetic algorithm.

[0108] The cycle module is configured to continue to execute the fitness calculation module after the child population is obtained until a preset number of iterations is met.

[0109] The output module is configured to output the child population as a set of optimal solutions of multi-objective optimization.

[0110] The allocation optimization module is configured to optimize the network bandwidth allocation path scheme of the service set according to the result of multi-objective optimization.

[0111] The third allocation module is configured to allocate the total amount of current network bandwidth corresponding to the gateway to other devices and the online device according to the optimal network bandwidth allocation scheme, and to the corresponding online device requirements.

[0112] As shown in Figure 5 The embodiment also provides a gateway central control scheduling method, which comprises the following steps:

[0113] S1, receiving the joining application information of an online device applying to join a gateway;

[0114] S2, after receiving the joining application information of the online device, checking whether the online device is a legal device by the gateway;

[0115] S3, when the online device is a legal device, issuing a corresponding authentication certificate, and determining the instruction information of the online device applying to join the gateway;

[0116] S4, after determining the corresponding instruction information, obtaining the device type, the required network bandwidth, and the running state information of the current online device to generate the corresponding online device basic information;

[0117] S5, quantizing the obtained online device basic information into corresponding numerical values and then inputting them into the gateway;

[0118] S6. On the gateway, the received values ​​are decrypted accordingly, and based on the decrypted data, instruction information, and current gateway allocation data retrieved from the database, the network resources of the current gateway are allocated to the connected device, the corresponding allocation result is generated, and the corresponding network resources are allocated to the connected device according to the allocation result.

[0119] Example 2

[0120] Compared with Example 1, the difference in this example is:

[0121] To ensure a more efficient allocation of network bandwidth for each device, after adding the connected devices,

[0122] The historical data analysis module is used to obtain the network bandwidth usage of each device in different historical time periods, and to analyze and determine the time points corresponding to the nodes where the network bandwidth of each device changes, and generate the corresponding bandwidth mutation time points of each device.

[0123] The clustering module is used to cluster the bandwidth mutation time points corresponding to all devices based on the corresponding bandwidth mutation time points using a clustering algorithm, thereby obtaining the corresponding final mutation time point. In this embodiment, the final mutation time point corresponding to the same cluster is the latest time node in that cluster. For example, if the corresponding time points in a certain cluster are 4:00, 4:05, and 4:10, then the corresponding final mutation time point in that cluster is 4:10. In this embodiment, an existing clustering algorithm can be used.

[0124] Of course, in this embodiment, in order to make the final mutation time points more representative, the final mutation time points formed at this time will be further processed. For example, a threshold limit will be set for the time span of each category. For example, the time span between time points in the same category cannot exceed 20 minutes. Once the corresponding time span exceeds the threshold, the time points will be re-divided. For example, those that have not exceeded the time span will be divided into one category, and then the next time span will be divided after an interval of one time span. This is to ensure the rationality and effectiveness of the classification.

[0125] The optimal module is also used to reallocate network bandwidth to each device at the current moment when each final mutation time point is reached.

[0126] In the embodiment, not only the network bandwidth is redistributed when the corresponding online device joins and the network bandwidth corresponding to the device exceeds the range, but also the network bandwidth is distributed at the bandwidth mutation point corresponding to each device. Considering that there are more bandwidth mutation points corresponding to each device, and the distribution frequency is faster as the number of devices increases, in order to more reasonably distribute, the bandwidth mutation time points corresponding to all devices are clustered, so that the bandwidth mutation points corresponding to all devices can be concentrated, thereby appropriately reducing the distribution frequency while ensuring the feasibility of distribution. The clustering algorithm is used for clustering, thereby obtaining a set of final mutation time points after clustering. When each final mutation time point is reached, a network bandwidth redistribution is performed according to the current situation of each device, so as to realize the rationalization of the bandwidth distribution of each device.

[0127] The above is only an embodiment of the present application, and the specific technical solutions and / or common knowledge of the scheme are not described in detail. It should be noted that, for those skilled in the art, without departing from the technical solutions of the present application, a number of modifications and improvements can be made, which should also be considered as the protection scope of the present application, and these will not affect the effect and practicality of the present application. The protection scope of the present application should be subject to the content of its claims, and the specific implementation mode and the like recorded in the specification can be used to explain the content of the claims.

Claims

1. A gateway master control scheduling system, characterized by: The application relates to a network resource allocation method and device for a gateway. The method comprises the following steps: An online device receiving module is used for receiving the joining application information of an online device applying to join the gateway; A first detection module is used for checking whether the online device is a legal device after the joining application information of the online device is received; An instruction determination module is used for issuing corresponding authentication certificates and determining the instruction information of the online device applying to join the gateway when the online device is a legal device; A data acquisition module is used for acquiring the device type, the required network bandwidth and the running state information of the current online device after the corresponding instruction information is determined, and generating corresponding online device basic information; A processing module is used for quantitatively processing the acquired online device basic information into corresponding numerical values and then transmitting the numerical values into the gateway; 2. The gateway central control scheduling system according to claim 1, characterized in that: An allocation judgment module is used for decrypting the numerical values received by the gateway, judging the allocation of the network resources of the gateway to the online device according to the decrypted data, the instruction information and the current gateway allocation data retrieved from the database, generating corresponding allocation results, and allocating the corresponding network resources to the online device according to the allocation results. The allocation judgment module comprises: A decryption module is used for decrypting the numerical values received by the gateway and restoring the information; A comparison module is used for comparing the restored information with the instruction information, and if the comparison is consistent, the current online device is judged to be a usable device; A retrieval module is used for retrieving the current gateway allocation data corresponding to the current gateway from the database after the current online device is judged to be a usable device; the current gateway allocation data comprises the current network bandwidth surplus, other device information corresponding to other nodes applying to join the gateway and the total network bandwidth; A first judgment module is used for judging whether the currently applied network bandwidth is less than or equal to the current network bandwidth surplus according to the current gateway allocation data and the network bandwidth applied by the device in the restored information; A first allocation module is used for issuing the corresponding device online requirement to the online device when the judgment result is that the currently applied network bandwidth is less than or equal to the current network bandwidth surplus; the device online requirement comprises a transmission channel number, a bandwidth size and a data synchronization mode; the online device performs the online operation of the gateway according to the device online requirement; A second judgment module is used for calculating the percentage between the value corresponding to the network bandwidth exceeding the current network bandwidth surplus and the total network bandwidth when the judgment result is that the currently applied network bandwidth is greater than the current network bandwidth surplus, obtaining the corresponding exceeding bandwidth percentage value, and judging whether the current exceeding bandwidth percentage value is less than or equal to a preset threshold value; A second allocation module is used for issuing the corresponding device online requirement to the online device without affecting other devices when the current exceeding bandwidth percentage value is judged to be less than or equal to the preset threshold value. The optimal module is configured to, when it is determined that the current bandwidth-occupying ratio exceeds the preset threshold, obtain, from a database, basic information of other devices corresponding to other nodes currently applying to join the gateway and necessity information corresponding to each device, and generate, based on an improved genetic algorithm, an optimal network bandwidth allocation scheme for the other devices and the current online device to connect to the gateway. The third allocation module is configured to allocate, according to the optimal network bandwidth allocation scheme, the total current network bandwidth corresponding to the gateway to the other devices and the online device and to the corresponding online device requirement.

3. The gateway central control scheduling system according to claim 2, characterized in that: The optimal module includes: The calling module is configured to, when it is determined that the current bandwidth-occupying ratio exceeds the preset threshold, call, from a database, basic information of other devices corresponding to other nodes currently applying to join the gateway. The service set determination module is configured to determine, according to the other devices corresponding to the current gateway and the current online device, a service set of the other devices and the online device to connect to the gateway and a network bandwidth allocation path of the gateway. The constraint condition determination module is configured to determine constraint conditions corresponding to each service in the service set. The objective function establishment module is configured to establish objective functions corresponding to each service in the service set. The mathematical model module is configured to realize multi-objective optimization of the network bandwidth allocation path in the service set based on an improved genetic algorithm and the determined objective functions and constraint conditions. The allocation optimization module is configured to optimize the network bandwidth allocation path scheme of the service set according to a result of the multi-objective optimization.

4. The gateway central control scheduling system according to claim 3, characterized in that: The mathematical model module includes: The first screening module is configured to randomly generate an initial population with a scale of N, the individual of the initial population being a network bandwidth allocation path corresponding to the selected other devices and the online device, and to judge and screen the individual of the initial population through constraint conditions, the constraint conditions including a total network bandwidth constraint condition and an allocation repetition constraint condition; if the constraint conditions are met, the corresponding network bandwidth allocation path is a feasible solution, and if the constraint conditions are not met, the corresponding network bandwidth allocation path is an infeasible solution. The fitness calculation module is configured to calculate first fitness and second fitness of the screened population respectively. The selection module is configured to, within a first preset number of iterations, select, according to the first fitness of the population, the population with the first fitness greater than or equal to a first fitness threshold, and select, from the population eliminated at this time, the first three populations with the second fitness being the largest and save the first three populations to a backup library. After a second preset number of iterations, the population at this time and the population in the backup library are combined to form a new population, and the population with the second fitness greater than a preset second fitness threshold is selected. The crossover and mutation module is configured to obtain a child population by crossing and mutating the selected population through a genetic algorithm. The cycle module is configured to, after obtaining the child population, continue to execute the fitness calculation module until a preset number of iterations is met. The output module is configured to output the child population as an optimal solution set of the multi-objective optimization.

5. The gateway central control scheduling system according to claim 4, characterized in that: The first fitness is calculated as follows: D1 is the sum of the influence degree of each device in the initial population, X i is the network bandwidth allocated to device i, and fi is the first fitness.

6. The gateway central control scheduling system according to claim 5, wherein: The second fitness is calculated as follows: The D2 is the sum of the waste degrees of network bandwidth allocated to each device in the initial population, and the Y j The D2 is the sum of the waste degrees of network bandwidth allocated to each device in the initial population, and the Y j The D2 is the sum of the waste degrees of network bandwidth allocated to each device in the initial population, and the Y j The D2 is the sum of the waste degrees of network bandwidth allocated to each device in the initial population, and the Y j The D2 is the sum of the waste degrees of network 7. A method for gateway central control scheduling, applied to the gateway central control scheduling system according to any one of claims 1-6, characterized in that: The method includes the following steps: S1, receiving the joining application information of the online device applying to join the gateway; S2, after receiving the joining application information of the online device, the gateway checks whether the online device is a legal device; S3, when the online device is a legal device, the corresponding authentication certificate is issued, and the instruction information of the online device applying to join the gateway is determined; S4, after determining the corresponding instruction information, the device type, the required network bandwidth and the running state information of the current online device are obtained, and the corresponding online device basic information is generated; S5, the obtained online device basic information is quantitatively processed into corresponding numerical values and transmitted into the gateway; S6, on the gateway, the numerical values received by the gateway are decrypted, and according to the decrypted data, the instruction information, and the current gateway allocation data retrieved from the database, the allocation of the network resources of the current gateway to the online device is judged, the corresponding allocation result is generated, and the corresponding network resources are allocated to the online device according to the allocation result.

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