Terminal-side load balancing system, method and apparatus based on energy storage device

Abstract

This invention provides a terminal-side load balancing system, method, and apparatus based on energy storage devices. The system includes: a signal conversion module for converting digital traffic signals representing network traffic received from a base station by a communication module into analog traffic signals; a memristor detection circuit connected between the signal conversion module and ground for detecting current changes corresponding to the analog traffic signals to generate feedback signals reflecting network traffic volume; and a main control chip for calculating real-time network bandwidth based on the feedback signals and comparing the real-time network bandwidth with a preset threshold. When the main control chip detects that the real-time network bandwidth is lower than the preset threshold, it generates a load balancing feedback command and reports it to the operator's network side via the communication module to trigger network-side load balancing operations. This achieves high-precision network traffic detection at the terminal side and can proactively trigger network-side load balancing based on the detection results.

Description

Technical Field

[0001] This invention relates to the field of mobile communication technology, and more specifically to a terminal-side load balancing system, method, and apparatus based on energy storage devices. Background Technology

[0002] With the widespread adoption of mobile internet, portable mobile hotspot devices (such as MiFi) have become an important way to access the network. To enhance functionality, some power bank products integrate 4G / 5G communication modules (such as eSIM cards), enabling them to function as mobile hotspots and provide network connectivity for other terminal devices.

[0003] When the network environment in which a device operates deteriorates (e.g., reduced bandwidth, unstable signal), communication quality is affected, and the device can typically only passively accept the network status or perform simple network switching (e.g., dual-SIM switching). The device cannot proactively and accurately provide real-time link quality information to network operators to request targeted bandwidth adjustments or load balancing. Traditional load balancing technologies are primarily deployed on the server side, making it difficult to achieve effective and timely proactive optimization on resource-constrained terminal devices.

[0004] In existing technologies, devices monitor their own network bandwidth primarily through software sampling or hardware circuits based on ordinary resistors. Software monitoring consumes valuable computing resources and suffers from high response latency; while the resistance of ordinary resistors drifts with operating temperature and voltage fluctuations, causing distortion in the collected current / voltage signals and failing to accurately reflect real network traffic fluctuations, thus affecting the reliability of network status assessment.

[0005] Therefore, how to achieve high-precision network traffic detection on the terminal side and proactively trigger network-side load balancing based on the detection results has become an urgent technical problem to be solved. Summary of the Invention

[0006] Based on the above situation, the main objective of this invention is to provide a terminal-side load balancing system, method, and apparatus based on energy storage devices, so as to achieve high-precision network traffic detection at the terminal side and to actively trigger network-side load balancing based on the detection results.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows: In a first aspect, embodiments of the present invention disclose a terminal-side load balancing system based on an energy storage device, wherein the energy storage device integrates mobile hotspot functionality, and the system includes: The communication module is used for wireless communication with the base station; The signal conversion module, connected to the communication module, is used to convert the digital traffic signal representing network traffic received by the communication module from the base station into an analog traffic signal. A memristor detection circuit is connected between the signal conversion module and ground. The memristor detection circuit includes at least one memristor for detecting current changes corresponding to the flow analog signal to generate a feedback signal reflecting the magnitude of network flow. The main control chip is connected to the memristor detection circuit and the communication module respectively. The main control chip is used to calculate the real-time network bandwidth based on the feedback signal and compare the real-time network bandwidth with a preset threshold. When the main control chip detects that the real-time network bandwidth is lower than the preset threshold, it generates a load balancing feedback command and reports it to the operator's network side through the communication module to trigger the load balancing operation on the network side.

[0008] Optionally, the memristor is a multi-state memristor, configured to memorize multiple resistance states, each resistance state corresponding to a different network traffic detection sensitivity range.

[0009] Optionally, the load balancing feedback instruction includes at least one of device identification information, real-time network bandwidth value, and bandwidth increase request.

[0010] Optionally, it also includes: A battery health detection circuit is connected to the USB interface of the energy storage device. The battery health detection circuit includes at least one memristor for monitoring the voltage and current of the energy storage device when it is charging externally, so as to identify the type of the device being charged and the charging status.

[0011] Secondly, embodiments of the present invention disclose a terminal-side load balancing method based on an energy storage device, wherein the energy storage device integrates mobile hotspot functionality, and the method includes: Step S100: Receive wireless communication signals from the base station via the mobile communication module to obtain a traffic digital signal used to characterize network traffic; Step S200: Convert the digital flow signal into an analog flow signal; Step S300: Input the flow analog signal to the memristor detection circuit to detect the current change corresponding to the flow analog signal, so as to generate a feedback signal reflecting the network flow magnitude. Step S400: Calculate the real-time network bandwidth based on the feedback signal; Step S500: When the real-time network bandwidth is lower than a preset threshold, a load balancing feedback instruction is generated. In step S600, the load balancing feedback instruction is reported to the operator's network side through the mobile communication module to trigger the load balancing operation on the network side.

[0012] Optionally, the preset threshold is a dynamic threshold, which is adaptively adjusted according to the normal traffic range of different time periods; Step S500 includes: calculating the traffic change trends at current and historical time points; generating a load balancing feedback instruction only when the real-time network bandwidth is lower than a preset threshold and the change trend indicates that the bandwidth is continuously deteriorating.

[0013] Thirdly, embodiments of the present invention disclose a terminal-side load balancing device based on an energy storage device, wherein the energy storage device integrates mobile hotspot functionality, and the device includes: The wireless communication module is used to receive wireless communication signals from the base station via the mobile communication module in order to obtain a traffic digital signal that characterizes network traffic. The digital-to-analog converter module is used to convert digital flow signals into analog flow signals; The feedback signal generation module is used to input the flow analog signal to the memristor detection circuit, detect the current change corresponding to the flow analog signal, and generate a feedback signal that reflects the size of the network flow. The bandwidth calculation module is used to calculate the real-time network bandwidth based on the feedback signal. The instruction generation module is used to generate load balancing feedback instructions when the real-time network bandwidth is lower than a preset threshold. The load balancing module is used to report load balancing feedback instructions to the operator's network side through the mobile communication module, so as to trigger the load balancing operation on the network side.

[0014] Optionally, the preset threshold is a dynamic threshold, which is adaptively adjusted according to the normal traffic range of different time periods; The instruction generation module is specifically used to calculate the traffic change trends at current and historical points in time. Load balancing feedback instructions are only generated when the real-time network bandwidth is lower than a preset threshold and the trend indicates that the bandwidth is continuously deteriorating.

[0015] Fourthly, embodiments of the present invention disclose a computer-readable storage medium having a computer program stored thereon, the computer program stored in the storage medium being executed by a processor to implement the method disclosed in the second aspect above.

[0016] Fifthly, embodiments of the present invention disclose an energy storage device, including: the terminal-side load balancing system disclosed in the first aspect above, or including the terminal-side load balancing device disclosed in the fourth aspect above.

[0017] Beneficial effects: According to embodiments of the present invention, a terminal-side load balancing system, method, and apparatus based on energy storage devices utilizes the organic combination of a signal conversion module and a memristor detection circuit to convert the digital traffic signal received by the communication module into an analog traffic signal, creating conditions for subsequent hardware detection. Based on this, a detection circuit constructed using a memristor with constant resistance leverages its resistance, which remains unaffected by temperature and voltage fluctuations, to linearly and stably convert changes in the analog signal into a precise current feedback signal. This overcomes the problem of directly and accurately measuring wireless communication digital signals, and eliminates measurement signal distortion caused by temperature drift and voltage sensitivity, providing a highly reliable data foundation for network status assessment. This achieves high-precision and high-stability network traffic detection at the terminal side.

[0018] Based on high-precision traffic data detected by memristors, when the real-time network bandwidth falls below a preset threshold, a load balancing feedback command is automatically generated and reported to the operator's network side. This provides the operator with the most direct and accurate link quality information from the terminal, thereby triggering precise network-side load balancing operations (such as switching to a less loaded base station or frequency band). This effectively solves the technical pain point that terminal devices can only passively accept network conditions and cannot actively request optimization. It enables energy storage devices to actively participate in network optimization.

[0019] Furthermore, the core flow signal sensing is achieved through hardware circuitry (memristor detection circuit), reducing the reliance on software sampling of the main control chip, decreasing CPU computational overhead and system response latency, and improving the overall efficiency and reliability of the system.

[0020] Other beneficial effects of the present invention will be explained in detail through the introduction of specific technical features and technical solutions in specific embodiments. Those skilled in the art should be able to understand the beneficial technical effects brought about by these technical features and technical solutions through the introduction of these technical features and technical solutions. Attached Figure Description

[0021] The embodiments of the present invention will now be described with reference to the accompanying drawings. In the drawings: Figure 1 This is a schematic diagram of an energy storage device structure disclosed in this embodiment; Figure 2 This is a schematic diagram of a terminal-side load balancing system structure based on energy storage devices disclosed in this embodiment; Figure 3 This is a flowchart of a terminal-side load balancing method based on energy storage devices disclosed in this embodiment; Figure 4 This is a schematic diagram of a terminal-side load balancing device based on energy storage equipment disclosed in this embodiment. Detailed Implementation

[0022] The present invention is described below based on embodiments, but the present invention is not limited to these embodiments. In the following detailed description of the present invention, some specific details are described in detail, but well-known methods, processes, procedures, and elements are not described in detail in order to avoid obscuring the essence of the present invention.

[0023] Furthermore, those skilled in the art should understand that the accompanying drawings provided herein are for illustrative purposes only and are not necessarily drawn to scale.

[0024] Unless the context explicitly requires it, the words "comprising," "including," and similar terms throughout the specification and claims should be interpreted as encompassing rather than being exclusive or exhaustive; that is, meaning "including but not limited to."

[0025] In the description of this invention, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0026] To achieve high-precision network traffic detection at the terminal side and proactively trigger network-side load balancing based on the detection results, this embodiment discloses a terminal-side load balancing system based on energy storage devices. Please refer to [link / reference]. Figure 1 , Figure 1 This is a schematic diagram of an energy storage device disclosed in this embodiment. The energy storage device integrates a mobile hotspot function. Specifically, it integrates a 4G / 5G communication module (such as an eSIM card), enabling it to provide network connectivity for other terminal devices. The energy storage device also integrates a USB interface (or a Type-C interface, etc.), thus providing charging power to external devices.

[0027] Please refer to Figure 2 , Figure 2 This is a schematic diagram of a terminal-side load balancing system based on an energy storage device disclosed in this embodiment. The terminal-side load balancing system includes: a communication module 1, a signal conversion module 2, a memristor detection circuit 3, and a main control chip 4, wherein: Communication module 1 is used for wireless communication with the base station. In a specific embodiment, communication module 1 can be a 4G or 5G mobile communication module with integrated eSIM card functionality. This module is responsible for establishing a wireless connection with the base station and receiving and sending network data packets. In this embodiment, communication module 1 can obtain basic data characterizing the current network link quality from the base station side, specifically the rate of the received data stream, signal strength, etc. This information is usually stored internally in the form of digital traffic signals or output through a specific interface.

[0028] Signal conversion module 2 is connected to communication module 1. Signal conversion module 2 converts the digital traffic signal, representing network traffic, received by communication module 1 from the base station into an analog traffic signal. Specifically, since the signal directly from communication module 1 is a digital signal, it cannot be directly processed by analog circuit elements; therefore, signal conversion module 2 is needed for conversion. Signal conversion module 2 is connected to communication module 1. In a specific embodiment, signal conversion module 2 can be a digital-to-analog converter (DAC). The input port of the DAC receives a digital quantity representing the instantaneous network traffic size (e.g., a value proportional to the current bandwidth) from communication module 1. The DAC converts this digital quantity into a corresponding analog voltage signal, i.e., an analog traffic signal. For example, when a bandwidth of 50 Mbps is detected, the DAC can output a 1V voltage; when the bandwidth increases to 100 Mbps, it outputs a 2V voltage. This change in analog voltage signal linearly represents the fluctuation of network traffic.

[0029] Memristor detection circuit 3 is connected between signal conversion module 2 and ground. Memristor detection circuit 3 includes at least one memristor for detecting current changes corresponding to the flow analog signal, thereby generating a feedback signal reflecting the network flow magnitude. Specifically, a memristor is a passive electronic component whose resistance is determined by the amount of charge flowing through it and maintains that resistance after power is off. A key characteristic of a memristor is that its resistance M remains constant at a specific operating point, and this constantness is insensitive to temperature changes and operating voltage fluctuations. In a basic circuit implementation, the memristor is directly connected in series between the output of signal conversion module 2 (providing the input voltage V_flow, i.e., the flow analog signal) and ground. According to Ohm's law, when the resistance M of the memristor is constant, the magnitude of the current I flowing through the loop will be uniquely determined by the input voltage V_flow (i.e., the flow analog signal), i.e., I = V_flow / M. Specifically, the flow analog signal V_flow from signal conversion module 2 is applied to the memristor M. Since the resistance M of the memristor M is constant, changes in V_flow caused by network traffic fluctuations are linearly translated into changes in the loop current I. This current I serves as a feedback signal reflecting the magnitude of network traffic, and by measuring this current I, a precise feedback linearly related to network traffic can be obtained.

[0030] The main control chip 4 is connected to the memristor detection circuit 3 and the communication module 1, respectively. The main control chip 4 calculates the real-time network bandwidth based on the feedback signal and compares it with a preset threshold. When the main control chip 4 detects that the real-time network bandwidth is lower than the preset threshold, it generates a load balancing feedback command and reports it to the operator's network side via the communication module 1 to trigger load balancing operations on the network side. Specifically, the main control chip 4 can be a microcontroller. It reads the magnitude of the feedback signal from the memristor detection circuit 3 (i.e., the voltage value reflecting the current I) through an ADC, or obtains the magnitude of the feedback signal based on the loop current I through an operational amplifier and inputs it to the main control chip 4.

[0031] The main control chip 4 converts the read feedback signal value into a real-time network bandwidth value according to the pre-calibrated relationship. Then, it compares this real-time network bandwidth with a preset threshold. When the real-time network bandwidth is detected to be lower than the preset threshold, the main control chip 4 determines that the current network quality is poor and generates a load balancing feedback command. Finally, the main control chip 4 reports this command to the operator's network side through the communication module 1 to trigger the network side's load balancing operation, thereby enabling the network side to perform load balancing operations such as switching base stations and adjusting resource allocation, thereby actively improving the connection quality.

[0032] In a specific embodiment, the generated load balancing feedback instruction is a structured data packet, which includes at least one of device identification information, real-time network bandwidth value, and bandwidth increase request. Specifically, the device identification information is used to uniquely identify the energy storage device sending the request on the network side. This information may include the device's International Mobile Equipment Identity (IMEI), Integrated Circuit Card Identifier (ICCID), or a unique device ID assigned by the operator. The network side can accurately allocate resources to the corresponding device based on this information; the real-time network bandwidth value directly reflects the precise network bandwidth currently perceived by the terminal device (e.g., 35 Mbps), enabling it to assess the severity of network degradation; the bandwidth increase request explicitly expresses the device's expectations to the network side, for example, it could be a simple "increase bandwidth" flag, or a more specific numerical request, such as "expect bandwidth to be increased to 50 Mbps".

[0033] In this embodiment, structured instructions enable the operator's network side to perform fast and accurate automated processing, thereby efficiently triggering load balancing operations such as switching to a less loaded base station or allocating dedicated radio resource blocks.

[0034] To adaptively adjust the sensitivity and range of network traffic monitoring, in an optional embodiment, the memristor is a multi-state memristor, configured to memorize multiple resistance states, each corresponding to a different range of network traffic detection sensitivity. Specifically, the multi-state memristor can stabilize its resistance in multiple discrete resistance states by applying an electrical pulse of specific amplitude and width, and each state remains stable without external interference. In a specific implementation, under the control of the main control chip 4, an initialization setting pulse can be applied to the multi-state memristor to make it enter a preset resistance state. For example, three resistance states can be set: State 1 (High Sensitivity): Corresponding resistance value R_high (e.g., 1kΩ). In this state, the loop current is very sensitive to changes in the input voltage V_flow, making it suitable for detecting minute fluctuations in network traffic and for scenarios with extremely high network latency requirements.

[0035] State 2 (Standard Sensitivity): Corresponds to resistance value R_mid (e.g., 10kΩ). This is the default operating state, providing balanced detection sensitivity and range, suitable for general network applications.

[0036] State 3 (Wide Range): Corresponds to resistance value R_low (e.g., 100kΩ). In this state, the detectable voltage V_flow range is wider, suitable for scenarios with drastic network traffic fluctuations or where peak traffic monitoring is required.

[0037] In practical applications, the main control chip 4 can dynamically switch the resistance state of the multi-state memristor according to different application scenarios or time strategies, thereby adaptively adjusting the sensitivity and range of network traffic monitoring, making the system more intelligent and flexible.

[0038] To enable battery health monitoring of the device to be charged, in an optional embodiment, the terminal-side load balancing system further includes a battery health monitoring circuit 5, please refer to [reference needed]. Figure 2 The battery health detection circuit 5 is connected to the USB interface of the energy storage device. The battery health detection circuit 5 includes at least one memristor for monitoring the voltage and current of the energy storage device during external charging, in order to identify the type of device being charged and its charging status. Details are as follows: The power supply module of an energy storage device (such as a power bank) charges external devices (such as mobile phones) through its USB interface (or Type-C interface). The battery health monitoring circuit 5 is directly connected between the power output pin (V_BUS) of the energy storage device's USB interface and ground (GND). Utilizing the constant resistance of a memristor, it can monitor voltage and current changes in the charging circuit with high precision and stability, thus overcoming measurement errors caused by component temperature drift in traditional detection methods.

[0039] Please refer to Figure 2The memristor in battery health monitoring circuit 5 is connected in series in the charging circuit. When the energy storage device outputs electrical energy, a charging voltage V_charge is applied across the memristor. According to Ohm's law, I_charge = V_charge / M_batt. Since the resistance M_batt of the memristor is constant, the charging current I_charge flowing through it has a strictly linear relationship with the charging voltage V_charge. By measuring the current I_charge in this circuit (e.g., through an operational amplifier), high-precision voltage and current data can be obtained simultaneously. In specific implementation, its workflow is as follows: 1. Identifying the type of device being charged: Different devices being charged (such as mobile phones, tablets, and earphones) will identify the charging protocols they support (such as QC and PD) through specific voltage and current curves during the initial handshake phase. The battery health detection circuit 5 accurately records the voltage and current change waveforms during this handshake process using a memristor and sends the data to the main control chip 4 for analysis, thereby accurately identifying the type of connected device and the fast charging protocol it supports.

[0040] 2. Monitoring Charging Status: During charging, the battery health detection circuit 5 continuously monitors the charging voltage V_charge and the charging current I_charge. The main control chip 4 plots the charging curve based on this high-precision data.

[0041] 3. Determining Battery Health: For a healthy battery, its charging curve (such as the voltage rise curve over time) will conform to a specific health model. For example, a battery that has been used unhealthily for a long time may not be able to reach its peak full-charge voltage (e.g., the standard is 4.2V, but after degradation it can only reach 3.9V), or there may be abnormal voltage fluctuations during the charging process. By comparing the real-time charging curve with the standard health model, the main control chip 4 can determine the health status of the battery in the device being charged and can provide warnings to the user.

[0042] As can be seen, in this embodiment, the battery health detection circuit (5) achieves battery health diagnosis using energy storage devices by sharing resources such as the main control chip with the core load balancing system with a lower hardware increase cost. Moreover, this health detection reduces the error caused by component temperature drift and improves the detection accuracy.

[0043] This embodiment also discloses a terminal-side load balancing method based on energy storage devices. The energy storage devices integrate mobile hotspot functionality. Please refer to [reference needed]. Figure 3 , Figure 3 This is a flowchart of a terminal-side load balancing method based on energy storage devices disclosed in this embodiment. The terminal-side load balancing method includes steps S100, S200, S300, S400, S500, and S600, wherein: In step S100, a wireless communication signal is received from the base station via the mobile communication module to obtain a traffic digital signal characterizing network traffic. In this step, the communication module of the energy storage device (such as a 4G / 5G modem) establishes a connection with the operator's base station and receives downlink data. The communication module can generate or output a traffic digital signal proportional to the current instantaneous network data transmission rate; for example, this signal can be a numerical value whose magnitude directly corresponds to bandwidth in Mbps. See the description above for details.

[0044] Step S200 involves converting the digital flow signal into an analog flow signal. Specifically, since the digital signal cannot be directly processed by subsequent analog circuit elements, it can be implemented using a digital-to-analog converter (DAC). The DAC linearly converts the digital quantity obtained in step S100 into an analog voltage signal, i.e., the analog flow signal (e.g., V_flow).

[0045] In step S300, the flow analog signal is input to the memristor detection circuit to detect the current change corresponding to the flow analog signal, so as to generate a feedback signal reflecting the network flow magnitude.

[0046] After obtaining the analog signal V_flow in step S200, this analog signal V_flow can be input into a detection circuit containing at least one memristor. Utilizing the physical characteristic that the memristor's resistance M remains constant after being set, the change in the loop current I is strictly linearly proportional to the change in the input voltage V_flow. Therefore, fluctuations in network traffic (manifested as fluctuations in V_flow) are accurately and stably converted into fluctuations in current I. This current I, or its characteristic value (such as the voltage converted through the sampling resistor), is the desired feedback signal.

[0047] In step S400, the real-time network bandwidth is calculated based on the feedback signal. Specifically, the magnitude of the feedback signal generated in step S300 can be read by an analog-to-digital converter (ADC), and then the feedback signal value can be converted into a specific real-time network bandwidth value according to a pre-calibrated conversion relationship (e.g., a certain voltage value corresponds to 50Mbps).

[0048] Step S500: When the real-time network bandwidth is lower than a preset threshold, a load balancing feedback instruction is generated. When it is determined that the real-time bandwidth is lower than this threshold, it indicates that the current network quality does not meet the requirements, and the main control chip generates a load balancing feedback instruction. This instruction is a structured data packet, which may contain information such as device identifier (e.g., IMEI), current bandwidth value, timestamp, and bandwidth upgrade request.

[0049] In step S600, a load balancing feedback instruction is reported to the operator's network side via the mobile communication module to trigger load balancing operations on the network side. After generating the instruction in step S500, it can be sent to the network management system or load balancer on the operator's network side via the communication module. Upon receiving the instruction, the network-side device can trigger corresponding load balancing operations, such as switching the device's connection to a less loaded base station or allocating more wireless resources to it, thereby proactively and accurately improving the network connection quality of the energy storage device.

[0050] To effectively prevent false triggering and reduce unnecessary network signaling overhead, in an optional embodiment, the preset threshold is a dynamic threshold, which is adaptively adjusted based on the normal traffic range of different time periods. Step S500 includes: calculating the traffic change trend at the current and historical time points; generating a load balancing feedback instruction only when the real-time network bandwidth is lower than the preset threshold and the change trend indicates that the bandwidth is continuously deteriorating. Specifically, in this embodiment, the preset threshold is not a fixed value, but a dynamic threshold. This dynamic threshold is generated by the main control chip based on historical learning or pre-configuration strategies. For example, the system can record the average network traffic at different time periods (such as weekday daytime, nighttime, and weekend) over the past week to form a normal traffic range model. The dynamic threshold can then be taken from this model based on the current time period (e.g., the daytime threshold is set to 60Mbps, and the nighttime threshold is set to 30Mbps). In the specific judgment, in addition to knowing the bandwidth value at the current moment, its change trend can also be calculated using algorithms such as linear regression to determine whether the current bandwidth is rising, stable, or continuously declining. The load balancing feedback instruction is finally generated only when the real-time network bandwidth is lower than the preset threshold and the change trend indicates that the bandwidth is continuously deteriorating.

[0051] This embodiment determines whether to generate a load balancing feedback command by setting a dynamic threshold and considering traffic change trends, effectively preventing false triggering. For example, even if the instantaneous bandwidth briefly falls below the threshold but the trend recovers quickly, the system will not rush to report, avoiding unnecessary network signaling overhead. Only when the system confirms that the network condition is indeed continuously deteriorating will it issue a distress signal, making the reporting mechanism more intelligent and the network quality assessment more accurate.

[0052] This embodiment also discloses a terminal-side load balancing device based on an energy storage device. The energy storage device integrates mobile hotspot functionality. Please refer to [link / reference needed]. Figure 4 , Figure 4 This is a schematic diagram of a terminal-side load balancing device based on an energy storage device disclosed in this embodiment. The terminal-side load balancing device includes: a wireless communication module 100, a digital-to-analog conversion module 200, a feedback signal generation module 300, a bandwidth calculation module 400, an instruction generation module 500, and a load balancing module 600, wherein: The wireless communication module 100 is used to receive wireless communication signals from the base station via the mobile communication module to obtain a traffic digital signal for characterizing network traffic; The digital-to-analog converter module 200 is used to convert digital flow signals into analog flow signals; The feedback signal generation module 300 is used to input the flow analog signal to the memristor detection circuit, detect the current change corresponding to the flow analog signal, and generate a feedback signal that reflects the size of the network flow. The bandwidth calculation module 400 is used to calculate the real-time network bandwidth based on the feedback signal; The instruction generation module 500 is used to generate load balancing feedback instructions when the real-time network bandwidth is lower than a preset threshold. The load balancing module 600 is used to report load balancing feedback instructions to the operator's network side through the mobile communication module, so as to trigger the load balancing operation on the network side.

[0053] In an optional embodiment, the preset threshold is a dynamic threshold, which is adaptively adjusted according to the normal traffic range of different time periods. The instruction generation module 500 is specifically used to calculate the traffic change trends at current and historical points in time; a load balancing feedback instruction is generated only when the real-time network bandwidth is lower than a preset threshold and the change trend indicates that the bandwidth is continuously deteriorating.

[0054] This embodiment also discloses an energy storage device, including: the terminal-side load balancing system disclosed in the above embodiments, or including the terminal-side load balancing device disclosed in the above embodiments.

[0055] According to embodiments of the present invention, a terminal-side load balancing system, method, and apparatus based on energy storage devices utilizes the organic combination of a signal conversion module and a memristor detection circuit to convert the digital traffic signal received by the communication module into an analog traffic signal, creating conditions for subsequent hardware detection. Based on this, a detection circuit constructed using a memristor with constant resistance leverages its resistance, which remains unaffected by temperature and voltage fluctuations, to linearly and stably convert changes in the analog signal into a precise current feedback signal. This overcomes the problem of directly and accurately measuring wireless communication digital signals, and eliminates measurement signal distortion caused by temperature drift and voltage sensitivity, providing a highly reliable data foundation for network status assessment. This achieves high-precision and high-stability network traffic detection at the terminal side.

[0056] Based on high-precision traffic data detected by memristors, when the real-time network bandwidth falls below a preset threshold, a load balancing feedback command is automatically generated and reported to the operator's network side. This provides the operator with the most direct and accurate link quality information from the terminal, thereby triggering precise network-side load balancing operations (such as switching to a less loaded base station or frequency band). This effectively solves the technical pain point that terminal devices can only passively accept network conditions and cannot actively request optimization. It enables energy storage devices to actively participate in network optimization.

[0057] Furthermore, the core flow signal sensing is achieved through hardware circuitry (memristor detection circuit), reducing the reliance on software sampling of the main control chip, decreasing CPU computational overhead and system response latency, and improving the overall efficiency and reliability of the system.

[0058] In addition, the present invention provides a computer-readable storage medium, such as a chip, an optical disc, etc., on which an executable program is stored, which, when executed, implements the method described in any of the above-mentioned embodiments.

[0059] It should be noted that the computer-readable storage medium described in the embodiments of this disclosure is not limited to the embodiments given above. For example, it can also be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the embodiments of this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0060] It will be understood by those skilled in the art that the above-described preferred solutions can be freely combined and superimposed without conflict. The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings; for example, two consecutively indicated blocks may actually be executed substantially in parallel, or sometimes in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. The numbering of each step in this document is for ease of explanation and reference only and is not intended to limit the order of execution. The specific execution order is determined by the technology itself, and those skilled in the art can determine various permissible and reasonable orders based on the technology itself.

[0061] It should be noted that the use of step numbers (letters or numbers) to refer to certain specific method steps in this invention is merely for the purpose of convenience and brevity in description, and is by no means intended to restrict the order of these method steps. Those skilled in the art will understand that the order of the relevant method steps should be determined by the technology itself and should not be unduly restricted by the existence of step numbers. Those skilled in the art can determine various permissible and reasonable orderings of steps based on the technology itself.

[0062] Those skilled in the art will understand that, without conflict, the above-mentioned preferred solutions can be freely combined and superimposed.

[0063] It should be understood that the above embodiments are merely exemplary and not restrictive. Various obvious or equivalent modifications or substitutions that can be made by those skilled in the art regarding the above details without departing from the basic principles of the present invention will be included within the scope of the claims of the present invention.

Claims

1. A terminal-side load balancing system based on an energy storage device, wherein the energy storage device integrates mobile hotspot functionality, characterized in that, The system includes: Communication module (1) is used for wireless communication with the base station; The signal conversion module (2) is connected to the communication module (1). The signal conversion module (2) is used to convert the traffic digital signal used to characterize network traffic received by the communication module (1) from the base station into a traffic analog signal. A memristor detection circuit (3) is connected between the signal conversion module (2) and ground. The memristor detection circuit (3) includes at least one memristor for detecting the current change corresponding to the flow analog signal to generate a feedback signal reflecting the size of the network flow. The main control chip (4) is connected to the memristor detection circuit (3) and the communication module (1) respectively. The main control chip (4) is used to calculate the real-time network bandwidth according to the feedback signal and compare the real-time network bandwidth with a preset threshold. When the main control chip (4) detects that the real-time network bandwidth is lower than the preset threshold, it generates a load balancing feedback instruction and reports it to the operator network side through the communication module (1) to trigger the load balancing operation on the network side.

2. The terminal-side load balancing system as described in claim 1, characterized in that, The memristor is a multi-state memristor, configured to memorize multiple resistance states, each of which corresponds to a different network traffic detection sensitivity range.

3. The terminal-side load balancing system as described in claim 1, characterized in that, The load balancing feedback instruction includes at least one of the following: device identification information, real-time network bandwidth value, and bandwidth increase request.

4. The terminal-side load balancing system as described in any one of claims 1-3, characterized in that, Also includes: The battery health detection circuit (5) is connected to the USB interface of the energy storage device. The battery health detection circuit (5) includes at least one memristor for monitoring the voltage and current of the energy storage device charging externally, so as to identify the type of the device being charged and the charging status.

5. A terminal-side load balancing method based on an energy storage device, wherein the energy storage device integrates mobile hotspot functionality, characterized in that, The method includes: Step S100: Receive wireless communication signals from the base station via the mobile communication module to obtain a traffic digital signal used to characterize network traffic; Step S200: Convert the digital flow signal into an analog flow signal; Step S300: Input the flow simulation signal to the memristor detection circuit to detect the current change corresponding to the flow simulation signal, so as to generate a feedback signal reflecting the network flow size; Step S400: Calculate the real-time network bandwidth based on the feedback signal; Step S500: When the real-time network bandwidth is lower than a preset threshold, a load balancing feedback instruction is generated. In step S600, the load balancing feedback instruction is reported to the operator network side through the mobile communication module to trigger the load balancing operation on the network side.

6. The terminal-side load balancing method as described in claim 5, characterized in that, The preset threshold is a dynamic threshold, which is adaptively adjusted according to the normal traffic range of different time periods. Step S500 includes: calculating the current and historical traffic change trends at multiple time points; The load balancing feedback instruction is generated only when the real-time network bandwidth is lower than the preset threshold and the trend of change indicates that the bandwidth is continuously deteriorating.

7. A terminal-side load balancing device based on an energy storage device, wherein the energy storage device integrates mobile hotspot functionality, characterized in that, The device includes: The wireless communication module (100) is used to receive wireless communication signals from the base station through the mobile communication module to obtain a traffic digital signal for characterizing network traffic; Digital-to-analog converter module (200) is used to convert the digital flow signal into an analog flow signal; The feedback signal generation module (300) is used to input the flow analog signal to the memristor detection circuit, detect the current change corresponding to the flow analog signal, and generate a feedback signal reflecting the size of the network flow. A bandwidth calculation module (400) is used to calculate the real-time network bandwidth based on the feedback signal; The instruction generation module (500) is used to generate a load balancing feedback instruction when the real-time network bandwidth is lower than a preset threshold. The load balancing module (600) is used to report the load balancing feedback instruction to the operator network side through the mobile communication module to trigger the load balancing operation on the network side.

8. The terminal-side load balancing device as described in claim 7, characterized in that, The preset threshold is a dynamic threshold, which is adaptively adjusted according to the normal traffic range of different time periods. The instruction generation module (500) is specifically used to calculate the traffic change trends at current and historical points in time; The load balancing feedback instruction is generated only when the real-time network bandwidth is lower than the preset threshold and the trend of change indicates that the bandwidth is continuously deteriorating.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program stored in the storage medium is used to be executed by a processor to implement the method as described in claim 5 or 6.

10. An energy storage device, characterized in that, include: The terminal-side load balancing system as described in any one of claims 1-4, or including the terminal-side load balancing device as described in claim 7 or 8.

Images