A micro-power consumption and computation-free distributed flash memory end-bit encryption and anti-congestion communication method

Abstract

The present invention discloses a micro-power consumption and computation-free distributed flash memory end-bit encryption and anti-congestion communication method, which belongs to the field of communication. The scheduling method of the present invention includes: for the gateway command downlink transmission process, a computation-free passive communication node scheduling framework is used to realize a simple command control node; before uploading data, a simple logic circuit is used to realize data XOR encryption and extract key bit information in the sensor node data; in the data uplink process, data is transmitted by alternating frequencies to be packaged, and the gateway effectively avoids network congestion through a programmable congestion control algorithm based on hardware implementation. The present invention can significantly reduce the communication overhead of the downlink with extremely low power consumption and without increasing the data rate, increase the carrying capacity of the uplink information, realize efficient extraction and transmission of sensor data, and avoid conflicts when sensor nodes upload data at the same time, thereby accommodating the access of more sensor nodes under the same network resources.

Description

Technical Field

[0001] The invention belongs to the field of communications, and in particular relates to a micro-power consumption and calculation-free distributed flash memory end-bit encryption and anti-congestion communication method. Background Art

[0002] The rapid development of IoT applications requires lightweight IoT sensor nodes with low power consumption and high performance. High performance enables perception sensing nodes to adapt to a wider range of diverse application scenarios, while low power consumption helps to extend battery life and reduce maintenance costs. However, in the current architecture, the task performance of IoT sensor nodes is tightly coupled with their power consumption, so most IoT applications must make a trade-off between them. On existing sensor nodes, all tasks are performed using general-purpose MCUs, so the optimization of power consumption is essentially at the expense of high MCU operating speed.

[0003] The power consumption of sensor nodes is composed of communication, sensing and computing. With the continuous development of existing technologies, only the computing power of sensor nodes is high, mainly due to the high power consumption of microprocessors. Under the constraint of extremely low power consumption, sensor nodes cannot choose hardware with high response rate for communication, which limits the communication data rate and task execution efficiency of sensor nodes. In addition, with the rapid advancement of IoT technology, the era of the Internet of Everything has arrived. The traditional method of centrally storing massive IoT data may not meet the requirements of real-time, reliability and security.

[0004] In the process of implementing the technical solution of the present invention, the inventor found that the IoT terminal node uses local distributed flash memory to store perception data, which not only ensures the persistence of data and avoids the risk of data loss, but also significantly reduces the network burden and reduces the data transmission cost. By buffering commonly used instructions and data at the sensor node, control commands can be transmitted on the downlink with minimized data volume; based on the encryption of sensor node output data without processor assistance, the key bit extraction method of data information, and the packaging and uploading of sensor node output data to reduce the information load of the uplink, the security of data transmission can be guaranteed and the task throughput rate of the sensor node can be improved under extremely low power consumption, thereby effectively solving the problem of lack of security performance and insufficient task performance of traditional perception sensor nodes in low power consumption scenarios, and also realizing efficient extraction and transmission of sensor data, avoiding conflicts in data uploaded by sensor nodes at the same time, thereby accommodating the access of more sensor nodes under the same network resources, and finally promoting the large-scale deployment of sensor nodes. Summary of the invention

[0005] The present invention provides a micro-power consumption and computation-free distributed flash memory end-bit encryption and anti-congestion communication method, which is used to realize the gateway scheduling of sensor nodes through simple control commands; at the same time, the output data of the sensor nodes is securely encrypted, efficiently extracted and transmitted, thereby ensuring the security of sensor data transmission and accommodating the access of more sensor nodes under the same network resources and avoiding conflicts when sensor nodes upload data, and finally promoting large-scale deployment of the system.

[0006] The technical solution adopted by the present invention is:

[0007] A micro-power consumption and computation-free distributed flash memory end-bit encryption and anti-congestion communication method, the process comprising:

[0008] For the collected data of the sensor nodes, distributed flash memory is used to store the data in multiple storage nodes for backup.

[0009] For the gateway command downlink transmission process, a computation-free passive communication sensor chip scheduling framework is used to implement simple command control of the sensor chip.

[0010] For the uplink transmission process of sensor node data, the sensor node data is first XOR-encrypted, then the key bit information in the sensor node data is extracted, and finally the data is packaged and uploaded.

[0011] Furthermore, a computation-free passive communication sensor node scheduling framework is designed based on state machine logic, which enables the gateway to control the sensor nodes through some simple commands, thereby allowing the sensor nodes to adopt multiple access modes.

[0012] Furthermore, the access modes include: waiting state, instruction writing, random scheduling, loop scheduling, and priority scheduling, and each mode can be switched through simple commands.

[0013] The waiting state means that the sensor node listens to the command signal transmitted by the gateway; instruction writing means that the control sequence of the sensor chip is written into the cache to facilitate subsequent state scheduling; random scheduling, cyclic scheduling, and priority scheduling are three ways to control the sensor chip of the sensor node for different scheduling.

[0014] Before data uplink transmission, a pseudo-random bit sequence is generated by a linear feedback shift register (LFSR) as a key, and then the sensor node output data is XORed with the key generated by the LFSR to achieve data encryption; finally, the positions of two adjacent changes in the sensor node output data are compared through a simple logic circuit of an XOR gate, thereby extracting the key bit information in the sensor node output data.

[0015] Furthermore, the sensor node last bit transmission optimization and security encryption logic circuit includes: shift register No. 1 for storing the key, which adopts the serial input and parallel output method; shift register No. 2 for storing the current sensor chip output data, which adopts the serial input and parallel output method; XOR gate No. 1 for XOR encrypting the data; shift register No. 3 for storing the current encrypted data, which adopts the serial input and parallel output method; shift register No. 4 for storing the previous encrypted data, which adopts the serial input and parallel output method; XOR gate No. 2 for comparing the number of bits changed between two data.

[0016] For data packaging upload, when the sensor node uploads the sensor chip output data to the gateway, different clock frequencies are alternately selected to transmit the key bit information of the sensor chip output data.

[0017] Furthermore, after the gateway receives the data packet uploaded by the sensor node, it can split the key bit information of the sensor chip output data of random length in the data packet according to the different degrees of frequency shift generated by the reflected signal of the sensor node; the gateway then uses the LFSR key generator and XOR gate same as the sensor node to decrypt and obtain the initial data.

[0018] During this process, the gateway uses a programmable congestion control algorithm to avoid network congestion. The programmable flow control unit (PCC) divides data streams into different priorities through traffic generation and classification, and compresses and encodes the data to optimize transmission efficiency. Then the data packets are placed in the corresponding queues according to the priority and traffic shaping strategy. The congestion control engine continuously monitors the network status, uses multi-path detection to evaluate the congestion of different paths, and executes the congestion control algorithm. Once congestion is detected, the node will generate and send a CNP message as a feedback signal. The refined flow control module adjusts the transmission rate and window size according to this feedback information to achieve more refined traffic management.

[0019] The technical solution provided by the present invention brings at least the following beneficial effects: during the downlink transmission of gateway commands, the gateway can enable the sensor nodes to adopt multiple access modes through simple commands. During the uplink transmission of sensor node data, the information load of the uplink is reduced based on the encryption of sensor node output data without processor assistance, the extraction method of key bits of data information, and the packaging and uploading of sensor node output data, so that the limited uplink bandwidth can bear the transmission of more valid data. In this way, the secure encryption, efficient extraction and transmission of sensor data are realized, which effectively solves the problems of lack of security and insufficient task performance of traditional perception sensor nodes in low-power scenarios, and realizes more intelligent and efficient data communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 A basic schematic diagram of a micro-power consumption and computation-free distributed flash memory end-bit encryption and anti-congestion communication method provided by an embodiment of the present invention;

[0022] Figure 2 A schematic diagram of the last bit encryption of a micro-power consumption and no-computation distributed flash memory provided by an embodiment of the present invention;

[0023] Figure 3 A schematic diagram of the sensor node scheduling operation logic in an embodiment of the present invention;

[0024] Figure 4 A schematic diagram of sensor node data encryption and key bit information extraction in an embodiment of the present invention;

[0025] Figure 5 This is a schematic diagram of an embodiment of the present invention, in which a sensor node alternately selects different clock frequencies to control the output of a data signal when uploading a data packet.

[0026] Figure 6 This is a schematic diagram of a programmable congestion control algorithm based on a gateway in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0028] In order to realize the large-scale deployment of sensor nodes in the Internet of Things, in an embodiment of the present invention, by optimizing the transmission of downlink commands in the Internet of Things system, that is, a micro-power consumption and computation-free distributed flash memory end-bit encryption and anti-congestion communication method provided by an embodiment of the present invention, low communication overhead control of remote sensor nodes is realized. In addition, by optimizing the uplink data transmission in the Internet of Things system, that is, the sensor node output data security encryption, key bit information extraction and sensor node data packaging and uploading provided by an embodiment of the present invention, the secure transmission of data is realized and the amount of data actually transmitted is reduced, so that the effective amount of information that can be carried by the uplink is increased without increasing the communication power consumption and data rate, thereby realizing the efficient extraction and transmission of sensor data.

[0029] The core idea of ​​a micro-power consumption and computation-free distributed flash memory end-bit encryption and anti-congestion communication method provided by an embodiment of the present invention is to reduce the communication overhead of the gateway remote control sensor node; securely encrypt the uplink output data of the sensor node and reduce the amount of transmitted data; at the same time, increase the amount of effective information without increasing the communication power consumption, and finally achieve safer, smarter and more efficient communication.

[0030] For various independent functions on the sensor nodes, such as data reading and data processing, the gateway is prevented from sending complete command control downlink every time. To this end, in the embodiment of the present invention, a set of computation-free passive communication sensor node task scheduling framework based on state machine logic is designed, so that the gateway can control the sensor nodes through some simple commands, so that the sensor nodes can adopt multiple access modes. Specifically, the framework has five different states, each state corresponds to a specific function execution mode, and the framework can flexibly jump between these states, thereby meeting the sensor node's needs for diversified task scheduling.

[0031] like Figure 2 As shown, the five states and state conversions of the computation-free passive communication sensor node task scheduling framework based on state machine logic provided by the embodiment of the present invention are:

[0032] (1) Waiting state (Tag = 000). As the initialization state, it waits for the command from the gateway. After receiving the command from the gateway, it executes the corresponding instructions and enters the corresponding other states. At the same time, the gateway can also control the sensor nodes from other states to jump to the waiting state by issuing a waiting WS (WaitingState) command.

[0033] (2) Instruction Write (Tag = 001). Receiving the command IW (Instruction Write) in the waiting state will jump to the instruction write state. This state is to write the control sequence of the sensor node into the cache to facilitate subsequent state scheduling. In addition, the configuration of the key bits for sensor data extraction in the uplink is also written by the gateway in this state. By issuing the instruction write (IW) command, the gateway can transfer the target sensor node to the buffer write state; after that, the corresponding sensor chip can be operated by minimizing the communication overhead.

[0034] (3) Priority Scheduling (Tag=010). In the priority scheduling state, different priorities can be set for different types of sensor nodes so that the sensor nodes of this type are scheduled preferentially. This state can be jumped to by receiving the PS (Priority Scheduling) command from other states.

[0035] (4) Random Scheduling (Tag=011). In the random scheduling state, the gateway can schedule sensor nodes by arranging queues with extremely low overhead. Correspondingly, other states can jump to this state through the command RS (Random Schedule).

[0036] (5) Cyclic Scheduling (Tag = 100). In the cyclic scheduling state, the gateway can allow the target sensor node to cyclically schedule a certain function of it for a specified period. After executing the specified cycle, it will jump to the waiting state and wait for the next command from the gateway. Correspondingly, other states can jump to this state through the command CS (Cyclic Scheduling). In addition, the gateway can issue a WS command, a priority scheduling (PS) or a random scheduling (RS) command to interrupt the sensor node reading and convert the sensor node state to standby, priority scheduling or random scheduling respectively.

[0037] In the uplink of sensor node data, in order to achieve secure data transmission and reduce the amount of data actually transmitted in the uplink data, an embodiment of the present invention generates a pseudo-random bit sequence through a linear feedback shift register (LFSR) as a key, and then performs an XOR operation on the sensor node output data and the key generated by the LFSR to achieve data encryption; finally, the positions of two adjacent changes in the sensor node output data are compared through a simple logic circuit of an XOR gate, thereby extracting key bit information in the sensor node output data.

[0038] Specifically, Figure 3 As shown in the figure, a pseudo-random bit sequence is generated by a linear feedback shift register (LFSR) as a key, and then the sensor node output data is XORed with the key generated by the LFSR to achieve data encryption. The specific extraction process is as follows: First, according to the polynomial M(x) = x 12 +x 4 +x 2 +x 1 +1 linear feedback coefficient C0=C1=C2=C4=C 12 =1, and the other coefficients are 0. Where D i Represents the value in the shift register. The resulting 12-level linear feedback function is as follows:

[0039] f(D 12 ,…,D0)=C0+C1D 11 +C2D 10 +C4D8+C 12 D0

[0040] Among them, S i =x n-i , n represents the number of bits of LFSR.

[0041] Finally, a 12-bit output sequence can be generated and stored in shift register 2. At the same time, the initial data of the sensor node is stored in shift register 1. Then, due to the serial input and parallel output structure of the shift register, the data can be input into the XOR gate in the form of independent data bits for XOR encryption and output and stored in shift register 3.

[0042] Finally, the XOR gate is used to extract the changed part of the chip's output before and after for uplink transmission, thereby greatly improving the efficiency of data upload by the sensor node. The specific extraction process is as follows: First, the encrypted data output by the sensor node is stored in shift register 3, and the data is transferred to shift register 4 after the new encrypted data output is generated. Then, due to the serial input and parallel output structure of the shift register, the data can be input into the XOR gate in the form of independent data bits for comparison. Finally, when the output of the sensor changes between the previous and the next two times, the XOR gate outputs 1 on the changed data bit and outputs 0 on the unchanged data bit. Thus, shift register 1 can extract the key bits that have changed in the current data. Although the number of bits that change is only the 4th to 5th bits in the valid data, all bits 1 to 5 need to be uploaded when actually uploading, otherwise the location information of the data change needs to be carried, which brings additional information transmission.

[0043] In addition, the gateway can also send commands with data format information to control the XOR gate to narrow the range of data comparison, so as to further improve the efficiency of data extraction of key bit information.

[0044] Specifically, the data output by the sensor node is directly related to the monitored physical quantity, but most of the data is redundant, and only a few bits contain key information. Only when the monitored physical quantity changes by more than half of the range, all valid bits of the output data will change. If the change during the monitoring process is much less than half of the range, only a few bits will change. Assuming that the range of the target physical quantity that the sensor chip can detect is L0, the resolution of the sensor to the target physical quantity, δ0, that is, the minimum measurable change, can be expressed as:

[0045]

[0046] Among them, the total length of the effective bits of the output data is n, and the data range represented is N=2 n .

[0047] Furthermore, the resolution δ0 of the sensor node for the target physical quantity represents the minimum change that the sensor can distinguish, that is, the minimum value of the change in the target physical quantity corresponding to a 1-bit change in the output data. Assume that the amplitude change of the target physical quantity is L1 during two consecutive measurements. We need to find the number of bits D that change in the sensor output data in this case. change The output data will change only when the change in the target physical quantity exceeds the resolution δ0 of the sensor. Therefore, if L1 is greater than or equal to δ0, all valid bits will change; if L1 is less than δ0, only some of the valid bits will change. change It indicates the proportional relationship between the change amplitude of the target physical quantity and the sensor resolution, and multiplying it by the effective number of bits gives the number of bits of change. This indicates the minimum change that the sensor can distinguish. When the monitored change is less than this value, the output data of the sensor will not change because these changes are regarded as noise and are not recorded.

[0048]

[0049] Among them, the total length of the effective bits of the output data is n, and the data range represented is N=2 n , the resolution of the sensor is δ0, and the amplitude change of the target physical quantity is L1.

[0050] In the sensor node data uplink, in order to reduce the number of times of uploading data, the embodiment of the present invention adopts the method of uploading sensor node data in a package, and the gateway adopts a method based on the frequency shift when the sensor node reflects the gateway signal. Specifically, Figure 4 As shown, three clocks of different frequencies are used to alternately transmit the sensor data in the data packet. When uploading the data packet, the sensor node will alternately select different clock frequencies to control the output of the data signal, so that the reflected signal of the sensor node when uploading adjacent sensor data will produce different degrees of frequency shift. Therefore, the gateway can split the data of random length in the data packet according to the frequency characteristics of the reflected signal of the sensor node. Finally, the gateway uses the same LFSR key generator and XOR gate as the sensor node to perform XOR decryption to obtain the initial data. In addition, in order to effectively avoid the cumulative errors caused by communication errors and provide the gateway with more accurate data recovery basis, the sensor node will regularly upload complete sensor data.

[0051] During this process, the gateway uses programmable congestion control methods to avoid network congestion, such as Figure 6As shown. The programmable flow control unit (PCC) is a programming interface provided to adapt to various business scenarios and traffic models. It replaces or designs new congestion control algorithms through a variety of customized congestion detection signals. The default is the DCQCN flow control method. Specifically, the DCQCN algorithm and the HPCC algorithm dynamically adjust the transmission rate and queue depth of the data flow according to the network status to prevent or alleviate network congestion; the ADPG algorithm and the NDP algorithm focus on further traffic optimization and congestion avoidance to ensure efficient transmission of data flows in the network. The NDP algorithm distinguishes out-of-order packets and lost packets well, and can be used together with packet scattering technology to achieve extremely low latency.

[0052] Furthermore, the congestion control engine makes intelligent decisions based on real-time collected congestion information (such as timestamps, congestion levels, etc.) to adjust the data flow processing strategy. At the same time, the CNP message control method ensures real-time communication between the source and the target, timely transmission of congestion notification information, and bidirectional flow control. The upstream data flow pipeline and the downstream data flow pipeline represent the data sending and receiving paths respectively. In these paths, the data will be processed by priority queues and traffic shaping to ensure that critical data is given priority, while optimizing the utilization of network resources and avoiding unnecessary congestion.

[0053] In order to further enhance the reliability and flexibility of the system, auxiliary functions such as RTT measurement, flow database and multi-path detection are also integrated into the process. RTT measurement can understand the network delay in real time and provide accurate data support for flow control; the flow database is used to store and manage relevant information of data flow, providing comprehensive data support for the system; and multi-path detection allows the system to dynamically select the optimal transmission path according to the network status, improving the efficiency and reliability of data transmission. Finally, before sending data, the system performs data compression and encoding processing to reduce the occupancy of transmission bandwidth and improve data transmission efficiency.

[0054] According to actual measurements, the computation-free high-throughput sensor node scheduling method provided by the embodiment of the present invention controls the communication overhead generated by remote sensor node control to within 1.6%, which is only slightly higher than the traditional localized control method. In addition, by extracting the key bits of the sensor node output data through a simple logic circuit, the actual amount of data transmitted is reduced to about 30% of the original data output of the sensor node; the amount of effective information that can be carried by the uplink is increased by 3 times without increasing the communication power consumption and data rate.

[0055] In summary, the micro-power consumption and computation-free distributed flash memory end-bit encryption and anti-congestion communication method provided by the embodiment of the present invention can reduce the communication overhead in the downlink transmission control command, can greatly reduce the amount of information transmitted on the basis of ensuring the correctness of the transmitted information, and can greatly increase the effective information volume of the link without increasing the communication consumption. At the same time, a programmable congestion control method is used to avoid network congestion, ultimately promoting the large-scale deployment of sensors and efficient and intelligent communication transmission.

[0056] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0057] The above are only some embodiments of the present invention. For those skilled in the art, several modifications and improvements can be made without departing from the creative concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A micro-power consumption and computation-free distributed flash memory end-bit encryption and anti-congestion communication mechanism, characterized in that: The following steps are involved: For the collected data of sensor nodes, distributed flash memory is used to store the data in multiple storage nodes for backup; For the gateway command downlink transmission process, a computation-free passive communication sensor chip scheduling framework is used to implement simple command control of the sensor chip; Before uplinking the sensor data, XOR encryption of the data is implemented through a simple logic circuit and key bit information in the sensor node data is extracted; For the uplink transmission process of sensor node data, the data is packaged and uploaded by frequency alternation. In this process, the gateway uses a programmable congestion control algorithm to avoid network congestion.

2. The method according to claim 1, characterized in that A computation-free passive communication sensor node scheduling framework is designed based on state machine logic, which enables the gateway to control the sensor nodes through some simple commands, thereby allowing the sensor nodes to adopt multiple access modes.

3. The method according to claim 2, characterized in that The gateway only needs to transmit a complete control flow to the sensor node once when accessing the control sensor node for the first time. The subsequent control process can achieve efficient control by buffering the control logic of each sensor node.

4. The method according to claim 2, characterized in that Access modes include: waiting state, instruction writing, random scheduling, loop scheduling, and priority scheduling. Each mode can be switched through simple commands.

5. The method according to claim 4, characterized in that The waiting state means that the sensor node listens to the command signal transmitted by the gateway; instruction writing means that the control sequence of the sensor chip is written into the cache to facilitate subsequent state scheduling; random scheduling, cyclic scheduling, and priority scheduling are three ways to control the sensor nodes to perform different scheduling.

6. The method according to claim 1, characterized in that A pseudo-random bit sequence is generated by a linear feedback shift register (LFSR) as a key, and then the sensor node output data is XORed with the key generated by the LFSR to achieve data encryption. Finally, the positions of two adjacent changes in the sensor node output data are compared through a simple XOR gate logic circuit to extract the key bit information in the sensor node output data.

7. The method according to claim 6, characterized in that The sensor node last bit transmission optimization and security encryption logic circuit includes: shift register No. 1 for storing the key, which adopts the serial input and parallel output method; shift register No. 2 for storing the current sensor chip output data, which adopts the serial input and parallel output method; XOR gate No. 1 for XOR encryption of data; shift register No. 3 for storing the current encrypted data, which adopts the serial input and parallel output method; shift register No. 4 for storing the previous encrypted data, which adopts the serial input and parallel output method; XOR gate No. 2 for comparing the number of bits changed between two data.

8. The method according to claim 1, characterized in that When the sensor node uploads the sensor chip output data to the gateway, it alternately selects different clock frequencies to transmit the key bit information of the sensor chip output data. During this process, the gateway uses a programmable congestion control algorithm to avoid network congestion.

9. The method according to claim 8, characterized in that After the gateway receives the data packet uploaded by the sensor node, it can split the key bit information of the sensor chip output data of random length in the data packet according to the different degrees of frequency shift generated by the reflected signal of the sensor node; the gateway then uses the same LFSR key generator and XOR gate as the sensor node to decrypt and obtain the initial data.

10. The method according to claim 8, characterized in that The programmable flow control unit PCC divides data streams into different priorities through traffic generation and classification, and compresses and encodes the data to optimize transmission efficiency; then the data packets are placed in the corresponding queues according to the priority and traffic shaping strategy, the congestion control engine continuously monitors the network status, uses multi-path detection to evaluate the congestion of different paths, and executes the congestion control algorithm; once congestion is detected, the node will generate and send a CNP message as a feedback signal, and the refined flow control module will adjust the transmission rate and window size according to this feedback information to achieve more refined traffic management.

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