An event-triggered industrial internet of things low-overhead time synchronization method

Abstract

The application discloses an event-triggered low-overhead time synchronization method for industrial Internet of Things, and belongs to the field of industrial Internet of Things. According to the method, a node updates logical clock drift and offset compensation parameters in a set update period, and uses an estimator to estimate real-time clock states of neighbor nodes to construct a dynamic threshold; state error increases with the accumulation of absolute time until the dynamic threshold is exceeded, thereby triggering broadcast. In addition, a simple trigger condition is added to improve the convergence speed in the early stage. Through continuous update iteration, global consistency of network logical clocks is achieved. The application considers the problems of excessive time-triggered communication overhead and the fact that nodes cannot be stably triggered and triggering is uneven in the event-triggered mechanism under the random topology environment of industrial Internet of Things, improves synchronization accuracy without increasing additional communication overhead, and reduces the congestion probability of a shared network.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of industrial Internet of things, in particular to an event-triggered low-overhead time synchronization method for industrial Internet of things. BACKGROUND

[0002] Time synchronization technology providing a unified time reference for network nodes plays a vital role in industrial Internet of things. The efficient and deep application of industrial Internet of things cannot be achieved without timely and accurate data transmission and collaborative operation among various industrial devices. In actual scenarios, wireless sensor nodes applied in the perception layer of industrial Internet of things will exhibit slight differences in clock rate due to manufacturing process, resulting in time asynchronization. Therefore, clock information exchange between network nodes is inevitable to ensure their consistency in time. The fully distributed time synchronization method is more suitable for large-scale industrial Internet of things due to its high flexibility and strong robustness. However, it is worth noting that the distributed synchronization method requires frequent communication iterations between nodes, which violates the energy-saving design concept of related algorithms in resource-constrained industrial Internet of things environment, greatly limiting the application of fully distributed time synchronization method based on periodic broadcast in time.

[0003] Unlike the time-triggered control mechanism, in the event-triggered control mechanism, broadcast communication is only triggered when specific conditions are met, which can effectively save unnecessary communication overhead. Therefore, designing a time synchronization method based on event-triggered mechanism provides a new idea for reducing the communication overhead of distributed time synchronization method in large-scale industrial Internet of things environment, and prolonging the service life of the network.

[0004] In the event-triggered time synchronization method, nodes only broadcast messages when their state has changed significantly since the last transmission, rather than the traditional frequent periodic broadcast based on time, which significantly reduces the communication energy consumption of industrial Internet of things. However, the existing event-triggered time synchronization method has problems such as unstable and uneven node triggering. That is, in the later stage of the time synchronization phase, the triggering of nodes is prone to stagnation, which is not conducive to improving the accuracy of time synchronization. In addition, the triggering of events by nodes will appear in a non-uniform state, such as frequent triggering in the early stage and sparse triggering in the later stage, which will increase the number of communication broadcasts and increase the probability of blocking the shared network. Therefore, there is an urgent need for an event-triggered time synchronization method that ensures stable and uniform triggering of events without increasing communication energy consumption, and achieves network-wide clock synchronization. SUMMARY

[0005] In view of the above problems existing in the prior art, the technical problem to be solved by the present application is to provide an event-triggered fully distributed time synchronization method applied to an industrial Internet of Things environment, which processes the problems of frequent communication in the time-triggered mechanism and the problems that nodes cannot be stably triggered and triggered unevenly in the event-triggered mechanism; and provides a node interaction strategy based on event triggering suitable for a large-scale industrial Internet of Things scene, which can achieve reasonable time synchronization precision with low communication overhead, and all nodes can stably trigger broadcast, the broadcast interval is uniform, the broadcast tasks are similar, and the probability of network congestion is reduced.

[0006] In order to achieve the above object, the present application provides the following technical scheme:

[0007] The event-triggered low-overhead time synchronization method for the industrial Internet of Things is proposed based on a method of constructing a dynamic threshold based on joint estimation of neighbor clock state errors, in view of the problems of unstable and uneven node triggering in the event-triggered time synchronization method. The state error of the node will increase with the accumulation of absolute time until it exceeds the set dynamic threshold, that is, stable and sparse triggered communication and timely synchronization correction are achieved, so that the global clock tends to be consistent. In addition, an estimator is designed to estimate the real-time clock state of the neighbor, avoiding additional communication.

[0008] The technical scheme of the event-triggered low-overhead time synchronization method for the industrial Internet of Things is as follows:

[0009] The sensor nodes with similar hardware parameters are connected together through a wireless shared network to generate a random topology structure;

[0010] The local node initializes the clock parameters and sets the update period, and all nodes update the logical clock drift and offset compensation parameters according to the period;

[0011] The local node estimates the real-time state information of the neighbor based on the designed estimator using the existing information of itself, and constructs a dynamic threshold. In order to accelerate the convergence speed in the early stage, a constraint of the logical clock offset compensation parameter is added on the basis of the dynamic threshold, that is, a static threshold triggering condition is added;

[0012] The local node judges whether the triggering condition is met, and saves and broadcasts the clock state information of itself in the case of exceeding the triggering threshold;

[0013] The local node adjusts the local clock until the global clock is synchronized.

[0014] The random topology structure refers to that the sensor nodes with the same function are randomly distributed, the neighbor nodes of each sensor node are determined according to the communication radius and bidirectional communication is performed to form a random network topology structure, but it is ensured that each local node has at least one neighbor node.

[0015] The initialization of the clock parameters and the setting of the update period refer to setting the update period of the node as T, the initial update times as k = 1, and setting the initial logical clock drift and offset compensation parameters of all nodes as and setting the relative clock slope η as 1, t k represents the physical time of the kth update of the node.

[0016] The node updating the logical clock drift and offset compensation parameters refers to that the local node updates the local logical clock parameters according to the collected clock information according to the set update period. The specific process is as follows:

[0017] For any sensor node i, the kth update time of the hardware clock of the node can be expressed as When the update times k is greater than 2 and satisfies , the logical clock drift compensation parameter and the offset compensation parameter are updated respectively:

[0018]

[0019] wherein, and respectively represent the logical clock drift compensation parameter and the offset compensation parameter of the node i; η ij represents the relative clock slope of the node i and the node j, that is, wherein, α i and α j respectively represent the hardware clock drift of the node i and j, are respectively the own hardware clock value recorded by the node i when the node i receives the hardware clock value from the node j; is the kth broadcast time of the node j, and the logical clock drift compensation parameter broadcast by the neighbor node j is recorded by the node i as This means that the logical clock drift compensation parameter of the node j recorded by the node i is unchanged between the two broadcast intervals of the node j; |N i | represents the degree of the node i, N i is the neighbor node set of the node i; represents the instantaneous time before the update time , represents the logical clock drift compensation parameter of the node j recorded by the node i before the update, represents the logical clock drift compensation parameter broadcast by the node i last time, and in addition, represents the logical clock estimation value of the node j recorded by the node i at the update time , represents the logical clock estimation value of the node j recorded by the node i at the update time The previous logical clock value of node i.

[0020] The estimator refers to the fact that nodes do not broadcast local clock information at all update times, so they are unaware of the real-time hardware clock and logical clock values ​​of neighboring nodes. In order to improve the accuracy of update parameters without increasing additional communication, this invention designs an estimator to estimate the real-time hardware clock and logical clock values ​​of node j:

[0021]

[0022] in, and These represent the estimated values ​​of the real-time hardware clock and the logical clock of node j, respectively. This indicates the last transmission time of node j. This indicates that node i received the clock information from node j during the last transmission. The local hardware clock value recorded at the time. and These represent the logical clock drift and offset compensation parameters of node j recorded by node i before the update. Under the condition of ideal fixed delay, the real-time hardware clock estimate is consistent with the actual value, while there is an acceptable small error between the real-time logical clock estimate and the actual value.

[0023] The dynamic threshold refers to a threshold constructed based on estimates of the real-time state information of neighbors. To avoid frequent communication, this invention uses the real-time state information of neighbors from the estimator. Simultaneously, a measurement error is constructed and compared with the dynamic threshold. The specific process is as follows:

[0024] Use e i This represents the measurement error at node i. in, This represents the logical clock estimate constructed by node i using the clock information broadcast to its neighboring nodes the last time. and These represent the logical clock drift and offset compensation parameters for the most recent broadcast by node i, respectively; z i This indicates the combined measurement state of node i. Indicates the update time The actual logical clock value of node i, the dynamic threshold is represented as:

[0025] After node i is updated, it is necessary to determine whether the following formula is satisfied:

[0026]

[0027] When the condition is met, the node i broadcasts the clock information packet after updating the clock, wherein sigma is a trade-off parameter, 0 < sigma < 1 is satisfied, and the trade-off parameters of different nodes can be different.

[0028] The static threshold refers to: subtracting the value of the updated logical clock drift compensation parameter from the value before the update , and comparing with the set static threshold:

[0029]

[0030] When the condition is met, the node i broadcasts the clock information packet after updating the clock, wherein c is a set constant; the purpose of setting the static threshold is to improve the early convergence speed, that is, the threshold set by the application is a combination of the dynamic threshold and the static threshold:

[0031] Or

[0032] The saving and broadcasting of the clock state information of the node itself refer to: when the set dynamic or static threshold is exceeded, the node saves the updated logical clock drift and offset compensation parameter, and broadcasts the hardware clock value of the node itself to the neighbor nodes.

[0033] The local node adjusts the local clock until the global clock is synchronized refers to: the local node i adjusts the local logical clock based on the updated logical clock compensation parameter:

[0034] The application has the advantages that:

[0035] 1. The event-triggered industrial Internet of Things low-overhead time synchronization method of the application is a new type of event-triggered method based on a random topology undirected network, which solves the problems of unstable and uneven triggering of wireless sensor nodes in the event-triggered time synchronization method without increasing additional communication.

[0036] 2. The algorithm proposed by the application is completely distributed, that is, without any global information, each node updates by collecting the broadcast information of the neighbor nodes, which significantly reduces the frequent communication of wireless sensor nodes in the industrial Internet of Things.

[0037] 3. The application proposes a new state-dependent dynamic threshold, and the dynamic threshold condition is determined by the clock state error between each node and its neighbor, and the triggering frequency and synchronization accuracy are controlled by adjusting the trade-off parameter.

[0038] 4、The application uses an estimator to estimate the neighbor real-time clock, overcomes the problem that the neighbor node old clock information used by the node update has become inaccurate over time, improves the time synchronization accuracy of the node without increasing the communication energy consumption. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 A random topology structure schematic diagram provided for the embodiment of the application;

[0040] Figure 2 An event-triggered time synchronization flowchart adopted by the application;

[0041] Figure 3 A node-triggered communication event diagram generated by the simulation means adopted by the application;

[0042] Figure 4 A global logical clock synchronization effect diagram generated by the simulation means adopted by the application. DETAILED DESCRIPTION

[0043] The application will be further described in detail below in combination with the drawings and embodiments, but the application is not limited to these embodiments, and each item mentioned in the application can also be well applied in different fields and occasions.

[0044] The application includes the following contents: connecting sensors through a wireless shared network and forming a random topology structure, using an estimator to estimate the real-time clock information of neighbor nodes by the node, combining the information collected in the update interval, and updating the local clock according to the update period timing. In addition, dynamic and static thresholds are set by using the system state around the node, the clock information comparison value exceeds the threshold, and the clock information is broadcasted, and all nodes adjust the local clock until the global clock is synchronized.

[0045] As shown in Figure 1 , a distributed wireless network random topology example considered by the application, an industrial internet of things topology composed of 10 sensor nodes, the topology structure can be described by a graph G∈(V,E), wherein V={1,2,...,n} represents the set of nodes in the internet of things; E represents the edge set between nodes. If (i,j)∈E, it means that node i and node j are adjacent, node i can obtain information from node j, and N i ={j|(i,j)∈E} is the neighbor node set of node i. In the application, the channel between nodes is bidirectional, that is, (i,j)∈E means (j,i)∈E, and the graph G belongs to an undirected graph.

[0046] Each wireless sensor node in the industrial internet of things is equipped with a crystal oscillator, and the output is used to trigger a timing counter. For node i, the hardware clock τi (t) can be expressed as:

[0047] τ i (t) = a i t + β i

[0048] where t represents absolute time, a i and β i represent the hardware clock drift and offset of node i respectively. However, since the node cannot access the absolute time t, it cannot directly obtain and modify the hardware clock parameters. To ensure smooth time synchronization, each node is equipped with a logical clock based on the hardware clock, and the logical clock L i (t) of node i is defined as:

[0049]

[0050] where x and y represent the logical clock drift and offset compensation parameters respectively; and represent the logical clock drift and offset, therefore, the time synchronization target of the present application aims to make the logical clock drift x i and offset y i tend to be globally consistent by updating the logical clock compensation parameters of each node, thereby achieving consistent time synchronization of the entire network, that is:

[0051]

[0052] In the initial stage of the synchronization process, the parameters are initialized, in this embodiment, the number of updates of the node is set to k = 1, the hardware clock drift a and offset β are randomly selected from the intervals [0.9999, 1.0001] and [0, 0.0002] respectively, and the initial logical clock drift and offset compensation parameters are set to The update period is set to T = 1 s, and the actual update time of the node is t k = (kT - β) / a, since there are slight differences in a and β between nodes, the updates of the nodes in the network are not strictly synchronized.

[0053] When the number of updates k = 1 and k = 2, the node cannot update the clock information due to incomplete information collected, and the initial two time nodes only broadcast local clock information, for node i, the kth update time of the hardware clock can be expressed as When the number of updates k is greater than 2 and satisfies At this time, node i will estimate the real-time clock of neighbor node j with estimator and update the logical clock compensation parameters as follows:

[0054] The real-time hardware clock estimation value is:

[0055] The real-time logical clock estimation value is: where, and denote the real-time hardware clock and logical clock of node j estimated by node i. denote the latest transmitted hardware clock of node j received by node i at time The hardware clock of node i at time denotes the time instant before the update time denotes the time instant before the update time and denote the logical clock drift and offset compensation parameters of node j recorded by node i before the update, respectively, and ij denotes the relative clock slope of node i and node j, i.e. where, i and j denote the hardware clock drift of node i and j, respectively, and denote the hardware clock of node i recorded by node i when it receives the hardware clock and of node j, respectively, and after that, node i starts to update the logical clock drift compensation parameter and the offset compensation parameter according to the following formula:

[0056]

[0057] where, i denotes the degree of node i, denotes the logical clock drift compensation parameter of node j recorded by node i before the update, denotes the logical clock drift compensation parameter broadcasted by node i last time, is the logical clock estimation value of node j, denotes the logical clock value of node i before the update.

[0058] After the update, the measurement error is calculated, i.e. where, denotes the logical clock estimation value composed of the clock information broadcasted by node i to neighbor nodes last time, i.e. and denote the logical clock drift and offset compensation parameters broadcasted by node i last time, respectively; and i denotes the combined measurement state of node i, Indicates the update time The actual logic clock value of node i will account for the measurement error. Compare with the dynamic threshold; also update the current logic clock drift compensation parameter. and the value before the update Subtract from the given value and compare with the set static threshold:

[0059] or in, The dynamic threshold is represented by the constant parameter σ, which is a key factor in balancing synchronization accuracy and energy consumption. A smaller σ value results in stricter dynamic threshold triggering conditions, leading to more triggers. Nodes can more frequently replace old information with new broadcast information to update compensation parameters and achieve higher synchronization accuracy, but communication overhead also increases accordingly. In this embodiment, σ is set to 0.05. The static threshold triggering formula can solve the problem of slow convergence speed in the early stages, and choosing a constant as the static threshold will not increase the number of broadcasts triggered in later stages. Considering the hardware parameters of the sensor nodes, the constant c is chosen as 0.000002 in this embodiment.

[0060] When the set dynamic or static threshold is exceeded, the node stores the updated logical clock drift and offset compensation parameters and broadcasts them, along with its own hardware clock value, to neighboring nodes.

[0061] Finally, local node i adjusts its local clock based on the updated logical clock compensation parameters until the global clock is synchronized:

[0062] like Figure 3 The diagram shows the triggering times of the sensor nodes. Each point in the diagram maps to a single communication broadcast by the corresponding node, and the density of points reflects the energy consumption of the communication. As can be seen from the diagram, the method of this invention can stably trigger broadcast events while ensuring the uniformity and sparsity of the broadcasts. Specifically, the number of communication interactions among all nodes is relatively small, the broadcast intervals of the same node are uniform, and the amount of broadcast tasks undertaken by different nodes is similar.

[0063] like Figure 4 The figure shows the variation of the maximum error of the global logic clock. The smaller the maximum error, the higher the time synchronization accuracy. As shown in the figure, the logic clock using the method of this invention gradually converges after about 10 seconds. With the increase of the number of updates, the logic clock can achieve higher convergence accuracy.

[0064] It should be noted that the above is only the embodiment of the application as a technical solution to explain and not limit, although the application is explained in detail with the preferred embodiment, any skilled person in the art needs to know that without departing from the scope of the technical solution of the application, some changes or modifications are made by using the above disclosed technical content, which are equivalent to equivalent embodiments, and are within the scope of the technical solution.

Claims

1. An event-triggered based low-overhead time synchronization method for industrial internet of things, characterized in that, The method comprises the following steps: Sensors with similar hardware parameters are connected together through a wireless shared network to generate a random topology structure; Local nodes initialize clock parameters and set an update period, and all nodes update logical clock drift and offset compensation parameters according to the period; Local nodes estimate real-time state information of neighbors based on a designed estimator using information already available, and construct a dynamic threshold, and in order to accelerate the convergence speed in the early stage, a constraint of the logical clock offset compensation parameter is added to the dynamic threshold, that is, a trigger condition of a static threshold is added; A threshold is constructed based on the estimated value of the real-time state information of neighbors, in order to avoid frequent communication, the real-time state information of neighbors in the estimator is used, and the measurement error is compared with the dynamic threshold; the specific process is as follows: with e i denotes the measurement error of node i, where, denotes the logical clock estimate of node i at the last time it broadcasted the clock information to its neighbors, i.e. and denotes the logical clock drift and offset compensation parameter of node i at the last time it broadcasted the clock information to its neighbors, respectively; z i denotes the combined measurement state of node i, denotes the update time the actual logical clock value of node i, and the dynamic threshold is denoted as After the node i is updated, it is necessary to judge whether the following formula is satisfied: When the condition is satisfied, the node i broadcasts a clock information package after updating the clock, wherein σ is a trade-off parameter, and 0<σ<1, the trade-off parameters of different nodes can be different; The local node judges whether the trigger condition is satisfied, and saves and broadcasts the clock state information of the local node when the trigger threshold is exceeded. The local node adjusts the local clock until the global clock is synchronized.

2. The method of claim 1, wherein, Sensors with similar hardware parameters are connected together through a wireless shared network to generate a random topology structure, specifically including: The same function sensor node position is randomly distributed, the own neighbor node is determined by the communication radius and bidirectional communication is carried out, a random network topology structure is formed, but it is necessary to ensure that each local node has at least one neighbor node.

3. The method of claim 1, wherein, Local nodes initialize clock parameters and set an update period, and all nodes update logical clock drift and offset compensation parameters according to the period, specifically including: The update period of the node is set as T, and the initial update times is k = 1; the initial logical clock drift and offset compensation parameters of all nodes are set as and the relative clock slope η is set as 1, t k the physical time of the kth update of the node; The local node updates the local logical clock parameter by using the collected clock information according to the set update period.

4. The method of claim 3, wherein, The local node updates the local logical clock parameter by using the collected clock information according to the set update period, specifically including: For any sensor node i, the kth update time of its hardware clock can be represented as When the update number k is greater than 2 and satisfies The logical clock drift compensation parameter and the offset compensation parameter are updated respectively: in, and Represent the logic clock drift compensation parameter and offset compensation parameter of node i, respectively; η ij This represents the relative clock slope between node i and node j, i.e. Where, α i and α j These represent the hardware clock drift of nodes i and j, respectively. These are the hardware clock values ​​received by node i from node j. The recorded value of its own hardware clock; For the k-th broadcast time of node j, node i records the logical clock drift compensation parameter for the broadcast of its neighbor node j. This means that during the interval between two broadcasts by node j, the logical clock drift compensation parameter of node j recorded by node i remains unchanged; |N i | represents the degree of node i, N i Let i be the set of neighboring nodes; Indicates the update time In the previous instant, This indicates that the logical clock drift compensation parameters of node j previously recorded by node i have been updated. This represents the logical clock drift compensation parameter for node i's most recent broadcast. Additionally, Indicates the update time The estimated logical clock value of node j recorded by node i. Indicates the update time The previous logical clock value of node i.

5. The method of claim 1, wherein, Based on the designed estimator, the real-time state information of neighbors is estimated using information already available, specifically including: The node does not broadcast the local clock information at all update time, so the real-time hardware clock value and the logical clock value of the neighbor node are not known, in order to improve the accuracy of the update parameter without increasing additional communication, an estimator is designed to estimate the real-time hardware clock and the logical clock value of the node j: wherein, and respectively represent the estimated value of the real-time hardware clock and the logical clock of node j, represents the last transmission time of node j, represents the local hardware clock value recorded when node i receives the last transmission clock information of node j, and and respectively represent the logical clock drift and offset compensation parameters of node j recorded by node i before updating, in the case of considering ideal fixed delay, the estimated value of the real-time hardware clock is consistent with the actual value, and there is an acceptable small error between the estimated value of the real-time logical clock and the actual value.

6. The method of claim 1, wherein, A constraint of the logical clock offset compensation parameter is added to the dynamic threshold, that is, a trigger condition of a static threshold is added, specifically including: Compensate the logical clock offset parameter with the current updated value and the value before the update Subtract, compare with a set static threshold: Wherein c is a set constant, when the condition is satisfied, the node i broadcasts a clock information package after updating the clock; the purpose of setting the static threshold is to improve the convergence speed in the early stage, and the threshold is a combination of the dynamic threshold and the static threshold: or 7. The method of claim 1, wherein, The local node judges whether the trigger condition is satisfied, and saves and broadcasts the clock state information of the local node when the trigger threshold is exceeded. When the set dynamic or static threshold is exceeded, the node saves the updated logical clock drift and offset compensation parameters, and broadcasts them to the neighbor nodes together with the hardware clock value.

8. The method of claim 1, wherein, The local node adjusts the local clock until the global clock is synchronized, specifically comprising: The local node i adjusts the local logical clock based on the updated logical clock drift and offset compensation parameters:

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