A heterogeneous communication protocol fusion management method and system

Abstract

The application relates to the technical field of data processing, in particular to a heterogeneous communication protocol fusion management method and system, which comprises the following steps: obtaining TCP / IP protocol and UDP protocol encapsulated in a communication network application layer, and using the encapsulated TCP / IP protocol and UDP protocol to unpack data packets transmitted through a tunnel; defining a protocol header in the application layer to improve data transmission efficiency; calling corresponding application program interface (API) according to the type of a target network connected, and realizing communication between different types of devices through the corresponding API interface; the type of the target network comprises a Bluetooth network and a ZigBee network; monitoring the communication data volume transmitted at both ends of the API interface and the tunnel, obtaining the data processing efficiency of the API interface and the data processing efficiency of the TCP / IP and UDP protocols; and dynamically managing energy consumption by optimizing the communication efficiency during fusion of the TCP / IP protocol and the UDP protocol and the data processing efficiency of the API interface, so as to reduce the heat generated by the device.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a heterogeneous communication protocol fusion management method and system. Background Art

[0002] The convergence of heterogeneous communication protocols enables direct communication between different devices without complex protocol conversion. This technology is widely used in the Internet of Things, smart homes, industrial automation, and other fields, enabling interoperability between devices from different manufacturers and models. For example, in a smart home, users can control home appliances such as lights and air conditioners using mobile apps or smart wearable devices, even though these devices utilize different communication protocols. Through protocol convergence management, users can operate the same device without having to worry about the underlying communication protocols. When mobile phones or smart wearable devices process data, they generate a significant amount of heat. Therefore, minimizing energy consumption while maintaining data processing efficiency is crucial for improving device battery life.

[0003] Based on this, we propose a method and system to optimize the processing of data from multiple heterogeneous communication protocols. Summary of the Invention

[0004] The present invention integrates and manages multiple heterogeneous communication protocols, thereby reducing energy consumption in the data processing process and reducing the heat generation of the equipment while ensuring the normal data processing efficiency of the corresponding communication protocols.

[0005] The technical solution proposed by the present invention is: a heterogeneous communication protocol fusion management method, the method comprising:

[0006] Obtain the TCP / IP and UDP protocols encapsulated in the application layer of the communication network, and use the encapsulated TCP / IP and UDP protocols to decapsulate data packets transmitted through the tunnel; define the protocol header in the application layer to improve data transmission efficiency;

[0007] Call the corresponding application programming interface (API) according to the type of the target network to be connected, and realize communication between different types of devices through the corresponding API interface; the types of the target network include Bluetooth network and ZigBee network;

[0008] Monitor the amount of communication data transmitted between the API interface and both ends of the tunnel to obtain the data processing efficiency of the API interface and the data processing efficiency of the TCP / IP and UDP protocols;

[0009] By optimizing the communication efficiency when integrating TCP / IP and UDP protocols, as well as the data processing efficiency of the API interface, energy consumption is dynamically managed to reduce the heat generated by the device.

[0010] Preferably, the step of defining a protocol header in the application layer to improve data transmission efficiency comprises the following steps:

[0011] Identify existing protocol headers in the application layer and look for repeated fields;

[0012] Calculate the size of each repeated field and reduce the size of the repeated field through a compression algorithm; set a custom protocol header, extract the necessary fields to support application functions from the existing protocol header, and retain them in the custom protocol header;

[0013] Adjust the field order of the custom protocol header by calculating the relevance of each required field, placing multiple related required fields at the front of the custom protocol header, obtaining compressed repeated fields, and placing the repeated fields after the required fields to reduce data parsing time.

[0014] Modify the data sending logic in the application layer to adapt to the custom protocol header;

[0015] Integrate custom protocol headers into the application layer.

[0016] Preferably, monitoring the API interface and the amount of communication data transmitted at both ends of the tunnel comprises the following steps:

[0017] Monitor the communication data volume of the API interface, including:

[0018] Record the number of calls to each API endpoint through a counter;

[0019] Set up an API dictionary and store the number of calls to each API endpoint in the API dictionary;

[0020] Create a middleware that intercepts incoming requests to each API endpoint and updates the counter on each request.

[0021] When an API endpoint receives a request, the data traffic of each API endpoint is counted; and the statistical value of the data traffic of each endpoint is stored in the API dictionary;

[0022] Set the API data return endpoint to return the number of requests for each endpoint counted by the calculator and the data traffic information corresponding to each endpoint.

[0023] Preferably, the monitoring of the API interface and the amount of communication data transmitted at both ends of the tunnel further includes the following steps:

[0024] Capture interface data from the communication network and obtain TCP / IP and UDP protocol data packets through filters;

[0025] Extract source address, destination address, protocol type and data length from captured data packets;

[0026] Setting a TCP dictionary and a UDP dictionary, wherein the TCP dictionary and the UDP dictionary include a TCP data packet counter and a UDP data packet counter respectively;

[0027] Identify the type of each data packet obtained, and store the data packet in the TCP dictionary or UDP dictionary according to the type of the data packet; and update the corresponding TCP data packet counter and UDP data packet counter at the same time;

[0028] Output the number and length of corresponding data packets counted by the TCP dictionary and UDP dictionary according to the preset output frequency.

[0029] Preferably, the method further comprises the steps of: obtaining the TCP layer load strength and the IP layer load strength, comprising the following steps:

[0030] Retrieve data packets from a communication network;

[0031] By parsing the source address, destination address and protocol type in the data packet, the data packet information belonging to the TCP layer and the data packet information belonging to the IP layer are obtained;

[0032] Count the data lengths of all packets belonging to the TCP layer and obtain the total amount of communication data processed by the TCP layer;

[0033] Count the data lengths of all packets belonging to the IP layer and obtain the total amount of communication data processed by the IP layer;

[0034] Calculate the ratio of the total amount of communication data processed by the TCP layer to the total amount of communication data processed by the IP layer, and determine the load intensity of the TCP layer and the load intensity of the IP layer.

[0035] Preferably, the data processing efficiency of the API interface and the data processing efficiency of the TCP / IP and UDP protocols are obtained, including:

[0036] Calculating the data processing efficiency of the TCP layer and the data processing efficiency of the IP layer based on the judgment results of the load intensity of the TCP layer and the load intensity of the IP layer includes the following steps:

[0037] The judgment of data processing efficiency at the TCP layer includes:

[0038] A load intensity judgment threshold is set. If the ratio of the total amount of communication data processed by the TCP layer to the total amount of communication data processed by the IP layer is greater than the load intensity threshold, the load intensity of the TCP layer is judged to be high. Conversely, if the ratio of the total amount of communication data processed by the IP layer to the total amount of communication data processed by the TCP layer is less than the inverse of the load intensity judgment threshold, the load intensity of the IP layer is judged to be high.

[0039] If the load intensity of the TCP layer is large, the data processing efficiency of the TCP layer is analyzed, including the following steps:

[0040] Obtain TCP packets from the communication network, extract key information, and calculate the throughput of the TCP layer, including the following steps:

[0041] Obtain the transmission time and data length of each TCP data packet, and obtain the total number of TCP data packets within a preset time period;

[0042] Calculate the total transmission time and total number of bytes of the TCP data packet, and then calculate the data throughput B of the TCP layer; compare the calculated data throughput of the TCP layer with the preset TCP data processing threshold B1. If B is greater than B1, the data processing efficiency of the TCP layer is determined to be normal; otherwise, the data processing efficiency of the TCP layer is determined to be abnormal;

[0043] Step 2: If the load intensity of the IP layer is large, the data processing efficiency of the IP layer is analyzed to obtain the data throughput C of the IP layer, and compared with the preset data processing threshold C1 of the IP layer. If C is greater than C1, the data processing efficiency of the IP layer is judged to be normal; otherwise, the data processing efficiency of the IP layer is judged to be abnormal.

[0044] Preferably, the data processing efficiency of the API interface and the data processing efficiency of the TCP / IP and UDP protocols are obtained, further comprising:

[0045] Obtaining the data processing efficiency of the API interface includes the following sub-steps:

[0046] Get the number of requests for each endpoint and the corresponding data traffic information of each endpoint returned by the calculator;

[0047] Get the total number of endpoints of the API interface;

[0048] Calculate the average processing data flow A of each endpoint of the API interface and compare it with the preset API data processing threshold A1. If A is greater than A1, the data processing efficiency of the API interface is judged to be normal; otherwise, the data processing efficiency of the API interface is judged to be abnormal.

[0049] Preferably, the method of dynamically managing energy consumption to reduce heat generated by the device by optimizing the communication efficiency when the TCP / IP protocol and the UDP protocol are integrated and the data processing efficiency of the API interface comprises the following steps:

[0050] Determine whether the API interface data processing efficiency is normal. If normal, proceed to the following steps;

[0051] Optimize the power consumption of the API interface, including:

[0052] Obtaining data processing characteristics of the API interface, including the number of calls, data processing time for each call, and power consumption for each call;

[0053] The obtained call times, data processing time of each call and power consumption data of each call are pre-processed to form an API interface input variable set;

[0054] Feed the API interface input variable set into the pre-trained API interface powered model Output the predicted value of API interface power consumption; where a0, a i , α represent the intercept 1, regression coefficient 1 and error term 1 respectively;

[0055] Calculate the mean square error between the predicted value and the preset API target electricity consumption value; seek the data processing characteristics of the API interface that makes the predicted value closest to the target electricity consumption value as the optimal API interface input variable;

[0056] According to the optimal API interface input variables, adjust the API interface data processing process to optimize the energy consumption of the API interface;

[0057] Obtaining the TCP layer load intensity and the IP layer load intensity. If the TCP layer load intensity is greater than the IP layer load intensity, then: obtaining TCP data processing characteristics, wherein the TCP data processing characteristics include the frequency of establishing and disconnecting connections at the TCP protocol layer, the size of the TCP window and the number of data packets sent before a response, the power consumption during each connection establishment, and the power consumption during each response;

[0058] The frequency of establishing and disconnecting connections at the TCP protocol layer, the size of the TCP window, the number of data packets sent before the response, the power consumption during each connection establishment, and the power consumption during each response are preprocessed to form a TCP input variable set;

[0059] Input the TCP input variable set to the pre-trained TCP powered model Output the predicted value of TCP data processing power consumption; where b0, b i , β represent intercept 2, regression coefficient 2, and error term 2, respectively;

[0060] Calculate the mean square error between the predicted value of TCP data processing power consumption and the preset TCP target power consumption value; find the TCP data processing characteristics that are closest to the TCO target power consumption value as the optimal TCP input;

[0061] Adjust the TCP data processing process based on the optimal TCP input volume to optimize the energy consumption of TCP layer data processing, including:

[0062] Use long connection to reduce the frequency of TCP protocol establishment and disconnection;

[0063] Obtain network bandwidth and network delay data, adjust the TCP window size according to the network bandwidth and network delay, and reduce the frequency of acknowledgement response;

[0064] Adjust the response mechanism of the TCP protocol, use the sliding window mechanism of the TCP protocol, and send multiple data packets before waiting for the acknowledgement response, to improve the efficiency of data transmission;

[0065] At the same time, according to the network bandwidth and network delay data, the size of the UDP protocol data packet is adjusted, and the communication efficiency of the fusion of the UDP protocol and the TCP / IP protocol is improved.

[0066] The application also provides a heterogeneous communication protocol fusion management system, which is used to execute the heterogeneous communication protocol fusion management method.

[0067] The application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the heterogeneous communication protocol fusion management method.

[0068] The application has the following beneficial effects:

[0069] 1、The application, by monitoring the communication data amount transmitted at both ends of the API interface and the tunnel, obtaining the data processing efficiency of the API interface and the data processing efficiency of the TCP / IP and UDP protocols, and finding the optimal data processing characteristics (processing time, TCP window size, etc.) under the condition of ensuring the processing efficiency, the energy consumption during data processing is closest to the preset power consumption value.

[0070] 2、The application fuses TCP / IP and UDP protocols, and simultaneously fuses Bluetooth network protocol and ZigBee network communication protocol using API interface, so that the device can communicate using the above-mentioned networks. BRIEF DESCRIPTION OF DRAWINGS

[0071] Figure 1 The flowchart of the application is a heterogeneous communication protocol fusion management method. DETAILED DESCRIPTION

[0072] The following description is used to disclose the application so that those skilled in the art can implement the application. The preferred embodiments in the following description are only used as examples, and other obvious modifications can be thought of by those skilled in the art. The basic principles of the application defined in the following description can be applied to other embodiments, modifications, improvements, equivalents and other technical solutions without departing from the spirit and scope of the application.

[0073] It is understood that the term "one" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of an element may be one, while in another embodiment, the number of the elements may be multiple, and the term "one" should not be understood as a limitation on the quantity.

[0074] refer to Figure 1 The technical solution provided by the present invention is: a heterogeneous communication protocol fusion management method, comprising the following steps:

[0075] Step 1: Obtain the TCP / IP protocol and UDP protocol encapsulated in the application layer of the communication network, and use the encapsulated TCP / IP protocol and UDP protocol to decapsulate the data packets transmitted through the tunnel; define the protocol header in the application layer to improve data transmission efficiency;

[0076] Defining the protocol header in the application layer includes the following steps:

[0077] Identify existing protocol headers in the application layer and find repeated fields; calculate the size of each repeated field and reduce the size of repeated fields using a compression algorithm; set a custom protocol header, extract the necessary fields to support application functions from the existing protocol header, and retain them in the custom protocol header;

[0078] Adjust the field order of the custom protocol header by calculating the relevance of each required field, placing multiple related required fields at the front of the custom protocol header, obtaining compressed repeated fields, and placing the repeated fields after the required fields to reduce data parsing time.

[0079] Modify the data sending logic in the application layer to adapt to the custom protocol header; integrate the custom protocol header into the application layer.

[0080] Step 2: Call the corresponding application programming interface (API) according to the type of the target network to be connected, and realize communication between different types of devices through the corresponding API interface; the type of the target network includes Bluetooth network and ZigBee network;

[0081] Step 3: Monitor the amount of communication data transmitted between the API interface and both ends of the tunnel to obtain the data processing efficiency of the API interface and the data processing efficiency of the TCP / IP and UDP protocols; including the following steps:

[0082] 3.1. Monitor the communication data volume of the API interface, including:

[0083] Use a counter to record the number of calls to each API endpoint; set up an API dictionary and store the number of calls to each API endpoint in the API dictionary;

[0084] Create a middleware that intercepts incoming requests to each API endpoint and updates the counter on each request.

[0085] When an API endpoint receives a request, the data traffic of each API endpoint is counted; and the statistical value of the data traffic of each endpoint is stored in the API dictionary;

[0086] Set the API data return endpoint to return the number of requests for each endpoint counted by the calculator and the data traffic information corresponding to each endpoint.

[0087] 3.2. Capture interface data from the communication network and obtain TCP / IP and UDP protocol data packets through filters;

[0088] Extracting the source address, destination address, protocol type, and data length from the captured data packets; setting a TCP dictionary and a UDP dictionary, wherein the TCP dictionary and the UDP dictionary include a TCP data packet counter and a UDP data packet counter, respectively;

[0089] Identify the type of each data packet obtained, and store the data packet in the TCP dictionary or UDP dictionary according to the type of the data packet; and update the corresponding TCP data packet counter and UDP data packet counter at the same time;

[0090] Output the number and length of corresponding data packets counted by the TCP dictionary and UDP dictionary according to the preset output frequency.

[0091] 3.3. Obtaining the TCP layer load strength and IP layer load strength includes the following steps:

[0092] Obtain data packets from the communication network; obtain data packets belonging to the TCP layer and data packets belonging to the IP layer by parsing the source address, destination address and protocol type in the data packets;

[0093] Count the data lengths of all packets belonging to the TCP layer and obtain the total amount of communication data processed by the TCP layer;

[0094] Count the data lengths of all packets belonging to the IP layer and obtain the total amount of communication data processed by the IP layer;

[0095] Calculate the ratio of the total amount of communication data processed by the TCP layer to the total amount of communication data processed by the IP layer, and determine the load intensity of the TCP layer and the load intensity of the IP layer.

[0096] 3.4. Calculating the data processing efficiency of the TCP layer and the data processing efficiency of the IP layer based on the judgment results of the load intensity of the TCP layer and the load intensity of the IP layer, including the following steps:

[0097] 3.4.1. Determination of data processing efficiency at the TCP layer, including:

[0098] A load intensity judgment threshold is set. If the ratio of the total amount of communication data processed by the TCP layer to the total amount of communication data processed by the IP layer is greater than the load intensity threshold, the load intensity of the TCP layer is judged to be high. Conversely, if the ratio of the total amount of communication data processed by the IP layer to the total amount of communication data processed by the TCP layer is less than the inverse of the load intensity judgment threshold, the load intensity of the IP layer is judged to be high.

[0099] If the load intensity of the TCP layer is large, the data processing efficiency of the TCP layer is analyzed, including the following steps:

[0100] Obtain TCP packets from the communication network, extract key information, and calculate the throughput of the TCP layer, including the following steps:

[0101] Obtain the transmission time and data length of each TCP data packet, and obtain the total number of TCP data packets within a preset time period;

[0102] Calculate the total transmission time and total number of bytes of the TCP data packet, and then calculate the data throughput B of the TCP layer; compare the calculated data throughput of the TCP layer with the preset TCP data processing threshold B1. If B is greater than B1, the data processing efficiency of the TCP layer is determined to be normal; otherwise, the data processing efficiency of the TCP layer is determined to be abnormal;

[0103] 3.4.2. If the load intensity of the IP layer is high, the data processing efficiency of the IP layer is analyzed to obtain the data throughput C of the IP layer. This is compared with the preset data processing threshold C1 of the IP layer. If C is greater than C1, the data processing efficiency of the IP layer is considered normal; otherwise, the data processing efficiency of the IP layer is considered abnormal.

[0104] 3.4.3. Obtain the data processing efficiency of the API interface, including:

[0105] Get the number of requests for each endpoint and the corresponding data traffic information of each endpoint returned by the calculator;

[0106] Obtain the total number of endpoints of the API interface; calculate the average processing data flow A of each endpoint of the API interface, and compare it with the preset API data processing threshold A1. If A is greater than A1, it is judged that the data processing efficiency of the API interface is normal; otherwise, it is judged that the data processing efficiency of the API interface is abnormal.

[0107] TCP (Transmission Control Protocol) and IP (Internet Protocol) are two key layers in network communications. TCP provides reliable, connection-oriented data transmission, while IP is responsible for packet routing and forwarding. These two layers require different computing resources and power supply voltages when processing data.

[0108] When devices process data, especially wearable devices, these devices need to connect to different networks. When processing heterogeneous data, the devices need to manage the corresponding chips' thermal performance to prevent overheating and burns. Since the battery capacity is limited by the device's physical condition, energy consumption management is also necessary to improve battery life. This can be achieved through the following steps.

[0109] Step 4: Dynamically manage energy consumption to reduce the heat generated by the device by optimizing the communication efficiency when integrating the TCP / IP and UDP protocols and the data processing efficiency of the API interface. This includes:

[0110] 4.1. Determine whether the API interface data processing efficiency is normal. If normal, proceed to the following steps;

[0111] Optimizing the power consumption of the API interface, specifically comprising: obtaining data processing characteristics of the API interface, the data processing characteristics including the number of calls, the data processing time of each call, and the power consumption of each call;

[0112] The obtained call times, data processing time of each call and power consumption data of each call are pre-processed to form an API interface input variable set;

[0113] Feed the API interface input variable set into the pre-trained API interface powered model Output the predicted value of API interface power consumption; where a0, a i , α represent the intercept 1, regression coefficient 1 and error term 1 respectively;

[0114] Calculate the mean square error between the predicted value and the preset API target electricity consumption value; seek the data processing characteristics of the API interface that makes the predicted value closest to the target electricity consumption value as the optimal API interface input variable;

[0115] According to the optimal API interface input variables, the data processing process of the API interface is adjusted to optimize the energy consumption of the API interface.

[0116] Because the IP layer primarily handles packet routing and forwarding, its computational complexity is relatively low, and therefore its power supply voltage requirements are also low. The TCP layer handles complex operations such as data confirmation, retransmission, and flow control, which are computationally more complex and therefore require a higher power supply voltage.

[0117] The current management of equipment supply voltage is usually as follows:

[0118] Set the initial power supply voltage. Then, receive packets through the IP layer, parse the IP header, perform routing based on the destination address, and adjust the power supply voltage to accommodate low-complexity computations. Receive data segments through the TCP layer, parse the TCP header, check the sequence and acknowledgment numbers, adjust the power supply voltage to accommodate high-complexity computations, send an ACK message, and handle retransmissions.

[0119] The above process simply divides the power supply process into two directions: IP layer power supply and TCP layer power supply, and generally categorizes the voltage during low-complexity and high-complexity computations. It does not examine the factors that influence the TCP layer power supply voltage, nor does it provide a method for optimizing data processing while ensuring TCP data processing efficiency. This issue can be addressed by following the steps below.

[0120] 4.2. Obtain the TCP layer load intensity and the IP layer load intensity. If the TCP layer load intensity is greater than the IP layer load intensity, then: Obtain TCP data processing characteristics, wherein the TCP data processing characteristics include the frequency of establishing and disconnecting connections at the TCP protocol layer, the size of the TCP window and the number of data packets sent before a response, the power consumption during each connection establishment, and the power consumption during each response;

[0121] The frequency of establishing and disconnecting connections at the TCP protocol layer, the size of the TCP window, the number of data packets sent before the response, the power consumption during each connection establishment, and the power consumption during each response are preprocessed to form a TCP input variable set;

[0122] Input the TCP input variable set to the pre-trained TCP powered model Output the predicted value of TCP data processing power consumption; where b0, b i , β represent intercept 2, regression coefficient 2, and error term 2, respectively;

[0123] Calculate the mean square error between the predicted value of TCP data processing power consumption and the preset TCP target power consumption value; find the TCP data processing characteristics that are closest to the TCO target power consumption value as the optimal TCP input;

[0124] Adjust the TCP data processing process based on the optimal TCP input volume to optimize the energy consumption of TCP layer data processing, including:

[0125] Use persistent connections to reduce the frequency of TCP connection establishment and disconnection; obtain network bandwidth and network delay data, adjust the TCP window size based on the network bandwidth and network delay, and reduce the frequency of confirmation responses;

[0126] Adjust the response mechanism of the TCP protocol and utilize the sliding window mechanism of the TCP protocol to generate multiple data packets before waiting for confirmation response, thereby improving the efficiency of data transmission.

[0127] 4.3. Adjust the size of UDP protocol data packets based on network bandwidth and network delay data to improve communication efficiency when UDP protocol is integrated with TCP / IP protocol.

[0128] The invention also provides a heterogeneous communication protocol fusion management system, comprising a processor, a protocol parsing module connected to the processor, a protocol conversion engine, and a communication interface module. The system is used to execute the heterogeneous communication protocol fusion management method.

[0129] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the heterogeneous communication protocol fusion management method.

[0130] The embodiments disclosed in the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. The embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part, and / or installed from a removable medium. When the computer program is executed by the central processing unit (CPU), the above-mentioned functions defined in the method of the present application are executed. It should be noted that the computer-readable medium mentioned above in the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more wire segments, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including, but not limited to, an electromagnetic signal, an optical signal, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, electrical wire, optical fiber cable, RF, etc., or any suitable combination thereof.

[0131] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of the systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or portion of code that contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two boxes shown in succession can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, as well as combinations of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified functions or operations, or can be implemented using a combination of dedicated hardware and computer instructions.

[0132] Those skilled in the art should understand that the embodiments of the present invention described above and shown in the accompanying drawings are only examples and do not limit the present invention. The objectives of the present invention have been fully and effectively achieved. The functional and structural principles of the present invention have been demonstrated and explained in the embodiments. Without departing from the principles, the implementation methods of the present invention may be subject to any changes or modifications.

Claims

1. A heterogeneous communication protocol fusion management method, characterized in that: The method comprises: Obtain the TCP / IP and UDP protocols encapsulated in the application layer of the communication network, and use the encapsulated TCP / IP and UDP protocols to decapsulate data packets transmitted through the tunnel; define the protocol header in the application layer to improve data transmission efficiency; Call the corresponding application programming interface (API) according to the type of the target network to be connected, and realize communication between different types of devices through the corresponding API interface; the types of the target network include Bluetooth network and ZigBee network; Monitor the amount of communication data transmitted between the API interface and both ends of the tunnel to obtain the data processing efficiency of the API interface and the data processing efficiency of the TCP / IP and UDP protocols; By optimizing the communication efficiency when the TCP / IP protocol and the UDP protocol are integrated, as well as the data processing efficiency of the API interface, energy consumption is dynamically managed to reduce the heat generated by the device. The method of optimizing the communication efficiency when the TCP / IP protocol and the UDP protocol are integrated, as well as the data processing efficiency of the API interface, energy consumption is dynamically managed to reduce the heat generated by the device, including the following steps: Determine whether the API interface data processing efficiency is normal. If normal, proceed to the following steps; Optimize the power consumption of the API interface, including: Obtaining data processing characteristics of the API interface, including the number of calls, data processing time for each call, and power consumption for each call; The obtained call times, data processing time of each call and power consumption data of each call are pre-processed to form an API interface input variable set; Feed the API interface input variable set into the pre-trained API interface powered model Output the predicted value of API interface power consumption; represent the intercept one, regression coefficient one, and error term one respectively; Calculate the mean square error between the predicted value and the preset API target electricity consumption value; seek the data processing characteristics of the API interface that makes the predicted value closest to the target electricity consumption value as the optimal API interface input variable; According to the optimal API interface input variables, adjust the API interface data processing process to optimize the energy consumption of the API interface; Obtaining the TCP layer load intensity and the IP layer load intensity. If the TCP layer load intensity is greater than the IP layer load intensity, then: obtaining TCP data processing characteristics, wherein the TCP data processing characteristics include the frequency of establishing and disconnecting connections at the TCP protocol layer, the size of the TCP window and the number of data packets sent before a response, the power consumption during each connection establishment, and the power consumption during each response; The frequency of establishing and disconnecting connections at the TCP protocol layer, the size of the TCP window, the number of data packets sent before the response, the power consumption during each connection establishment, and the power consumption during each response are preprocessed to form a TCP input variable set; Input the TCP input variable set to the pre-trained TCP powered model Output the predicted value of TCP data processing power consumption; represent intercept two, regression coefficient two, and error term two, respectively; Calculate the mean square error between the predicted value of TCP data processing power consumption and the preset TCP target power consumption value; find the TCP data processing characteristics that are closest to the TCO target power consumption value as the optimal TCP input; Adjust the TCP data processing process based on the optimal TCP input volume to optimize the energy consumption of TCP layer data processing, including: Use persistent connections to reduce the frequency of TCP connection establishment and disconnection; Obtain network bandwidth and network delay data, adjust the TCP window size based on the network bandwidth and network delay, and reduce the frequency of confirmation responses; Adjust the response mechanism of the TCP protocol and use the sliding window mechanism of the TCP protocol to generate multiple data packets before waiting for confirmation, thereby improving the efficiency of data transmission; At the same time, the size of the UDP protocol datagram is adjusted according to the network bandwidth and network delay data to improve the communication efficiency when the UDP protocol is integrated with the TCP / IP protocol.

2. A heterogeneous communication protocol fusion management method according to claim 1, characterized in that: Defining a protocol header in the application layer to improve data transmission efficiency includes the following steps: Identify existing protocol headers in the application layer and look for repeated fields; Calculate the size of each repeated field and reduce the size of the repeated field through a compression algorithm; set a custom protocol header, extract the necessary fields to support application functions from the existing protocol header, and retain them in the custom protocol header; Adjust the field order of the custom protocol header by calculating the relevance of each required field, placing multiple related required fields at the front of the custom protocol header, obtaining compressed repeated fields, and placing the repeated fields after the required fields to reduce data parsing time. Modify the data sending logic in the application layer to adapt to the custom protocol header; Integrate custom protocol headers into the application layer.

3. A heterogeneous communication protocol fusion management method according to claim 2, characterized in that: The monitoring of the API interface and the amount of communication data transmitted at both ends of the tunnel includes: Monitoring the communication data volume of the API interface includes the following steps: Record the number of calls to each API endpoint through a counter; Set up an API dictionary and store the number of calls to each API endpoint in the API dictionary; Create a middleware that intercepts incoming requests to each API endpoint and updates the counter on each request. When an API endpoint receives a request, the data traffic of each API endpoint is counted; and the statistical value of the data traffic of each endpoint is stored in the API dictionary; Set the API data return endpoint to return the number of requests for each endpoint counted by the calculator and the data traffic information corresponding to each endpoint.

4. A heterogeneous communication protocol fusion management method according to claim 3, characterized in that: The monitoring of the API interface and the amount of communication data transmitted at both ends of the tunnel also includes: Capture interface data from the communication network and obtain TCP / IP and UDP protocol data packets through filters; Extract source address, destination address, protocol type and data length from captured data packets; Setting a TCP dictionary and a UDP dictionary, wherein the TCP dictionary and the UDP dictionary include a TCP data packet counter and a UDP data packet counter respectively; Identify the type of each data packet obtained, and store the data packet in the TCP dictionary or UDP dictionary according to the type of the data packet; and update the corresponding TCP data packet counter and UDP data packet counter at the same time; Output the number and length of corresponding data packets counted by the TCP dictionary and UDP dictionary according to the preset output frequency.

5. A heterogeneous communication protocol fusion management method according to claim 4, characterized in that: The monitoring of the API interface and the amount of communication data transmitted at both ends of the tunnel also includes: Obtaining the TCP layer load strength and IP layer load strength includes the following steps: Retrieve data packets from a communication network; By parsing the source address, destination address and protocol type in the data packet, the data packet information belonging to the TCP layer and the data packet information belonging to the IP layer are obtained; Count the data lengths of all packets belonging to the TCP layer and obtain the total amount of communication data processed by the TCP layer; Count the data lengths of all packets belonging to the IP layer and obtain the total amount of communication data processed by the IP layer; Calculate the ratio of the total amount of communication data processed by the TCP layer to the total amount of communication data processed by the IP layer, and determine the load intensity of the TCP layer and the load intensity of the IP layer.

6. A heterogeneous communication protocol fusion management method according to claim 5, characterized in that: The data processing efficiency of the API interface and the data processing efficiency of the TCP / IP and UDP protocols are obtained, including: Calculating the data processing efficiency of the TCP layer and the data processing efficiency of the IP layer based on the judgment results of the load intensity of the TCP layer and the load intensity of the IP layer includes the following steps: The judgment of data processing efficiency at the TCP layer includes: A load intensity judgment threshold is set. If the ratio of the total amount of communication data processed by the TCP layer to the total amount of communication data processed by the IP layer is greater than the load intensity threshold, the load intensity of the TCP layer is judged to be high. Conversely, if the ratio of the total amount of communication data processed by the IP layer to the total amount of communication data processed by the TCP layer is less than the inverse of the load intensity judgment threshold, the load intensity of the IP layer is judged to be high. If the load intensity of the TCP layer is large, the data processing efficiency of the TCP layer is analyzed, including the following steps: Obtain TCP packets from the communication network, extract key information, and calculate the throughput of the TCP layer, including the following steps: Obtain the transmission time and data length of each TCP data packet, and obtain the total number of TCP data packets within a preset time period; Calculate the total transmission time and total number of bytes of the TCP data packet, and then calculate the data throughput B of the TCP layer; compare the calculated data throughput of the TCP layer with the preset TCP data processing threshold B1. If B is greater than B1, the data processing efficiency of the TCP layer is determined to be normal; otherwise, the data processing efficiency of the TCP layer is determined to be abnormal; Step 2: If the load intensity of the IP layer is large, the data processing efficiency of the IP layer is analyzed to obtain the data throughput C of the IP layer, and compared with the preset data processing threshold C1 of the IP layer. If C is greater than C1, the data processing efficiency of the IP layer is judged to be normal; otherwise, the data processing efficiency of the IP layer is judged to be abnormal.

7. A heterogeneous communication protocol fusion management method according to claim 6, characterized in that: The data processing efficiency of the API interface and the data processing efficiency of the TCP / IP and UDP protocols are obtained, and further includes: Obtaining the data processing efficiency of the API interface includes the following sub-steps: Get the number of requests for each endpoint and the corresponding data traffic information of each endpoint returned by the calculator; Get the total number of endpoints of the API interface; Calculate the average processing data flow A of each endpoint of the API interface and compare it with the preset API data processing threshold A1. If A is greater than A1, the data processing efficiency of the API interface is judged to be normal; otherwise, the data processing efficiency of the API interface is judged to be abnormal.

8. A heterogeneous communication protocol fusion management system, comprising a processor, a protocol parsing module connected to the processor, a protocol conversion engine, and a communication interface module, characterized in that: The system is used to execute a heterogeneous communication protocol fusion management method as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the heterogeneous communication protocol fusion management method according to any one of claims 1 to 7.

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