A method for self-organizing scheduling of a DALI and wireless communication hybrid network

Abstract

The application discloses a DALI and wireless communication hybrid network self-organizing scheduling method, and aims at the situation that DALI and wireless communication equipment functions cooperate with each other and are hybridly networked in the use of Internet of Things equipment of intelligent buildings, provides a communication scheduling method, selects a core communication node, and solves the communication problem of wireless communication data received by DALI equipment in the wired link of the DALI equipment, and relates to the technical field of hybrid networking of Internet of Things. The DALI and wireless communication hybrid network self-organizing scheduling method solves the sensing and data transmission problem of wireless data in the communication node of the DALI wired link, provides a core basic solution scheme of a communication layer and a scheduling layer for intelligent system deployment and management, improves the communication efficiency of the hybrid networking system, and reduces the overall data transmission operation load of the system.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of Internet of Things hybrid networking, and particularly relates to a DALI and wireless communication hybrid network self-organizing scheduling method. BACKGROUND

[0002] DALI protocol: DALI is a data transmission protocol in the field of lighting control, which defines the communication interface between control devices and lighting devices. A DALI system is composed of distributed intelligent modules, each of which has digital communication capability. The working mode of the DALI system is a master-slave architecture, and one host can mount up to 64 slaves. The host controls the slaves through a DALI bus and communicates according to the DALI protocol. Each slave can be individually addressed, and each slave can store 16 light scenes. The same slave can be programmed in one group or multiple groups, with a maximum of 16 groups. This means that for large systems, multiple DALI buses may be needed to achieve control, increasing the complexity of the system. The maximum device distance of the DALI bus is usually not more than 300 meters, and communication problems may occur beyond this distance. The DALI system requires the use of a specific cable and has certain wiring requirements, which may increase the complexity of installation and maintenance.

[0003] When the wireless communication device is used in a smart building, its communication is affected by interference factors such as concrete walls, fireproof doors, and metals. If the building area is separated by the aforementioned interference factors, wireless communication may fail, resulting in system communication failure.

[0004] DALI can pass through walls through wiring and is not affected by building structures and environmental factors. In view of the foregoing background, a DALI and wireless communication hybrid networking is innovated, which can improve the communication capability in a smart building. However, DALI and wireless communication hybrid networking involves two communication protocols, and there is a scheduling problem when communication is needed between the two protocols. That is, due to the limitations of the DALI communication transmission mechanism, a bus link can only transmit data of a device in the link at the same time. Therefore, a scheduling method is needed to make the communication efficiency optimal and the system data load minimal when hybrid networking. SUMMARY

[0005] (I) Technical problems solved

[0006] In view of the deficiencies of the prior art, the application provides a DALI and wireless communication hybrid network self-organizing scheduling method. In view of the fact that the Internet of Things devices used in a smart building have DALI and wireless communication device functions that cooperate with each other and are hybrid networked, a communication scheduling method is provided to select core communication nodes and solve the problem of communication of wireless communication data received by DALI devices in their own wired links.

[0007] (II) Technical solutions

[0008] To achieve the above object, the application is implemented by the following technical solutions: a DALI and wireless communication hybrid network self-organizing scheduling method, specifically comprising the following steps:

[0009] S1, by using DALI compatible wireless communication equipment as a hybrid network communication node, then automatically running the sensing program of the DALI compatible wireless communication equipment in the same link, according to the set data acquisition window period, using the data in the window period to calculate the eigenvalue;

[0010] S2, the eigenvalues of different communication characteristics are calculated to identify whether the equipment is connected to the same wired link, and then the equipment on the same DALI link is marked as the same DALI block;

[0011] S3, when there are multiple DALI compatible wireless communication equipment in the same DALI block, calculate the score data of each node, and select the equipment with the highest score as the core node of the link;

[0012] S4, select the DALI link of the core node, and use the node as the receiving and transmitting equipment of the wireless communication of the link;

[0013] S5, when the hybrid network system detects new node equipment, replacement or failure of the original core node equipment, the system uses the moving average method to update, automatically collects new eigenvalues, and re-runs the previous program to judge the new core node;

[0014] The step S2 identifies whether the equipment is connected to the same wired link, specifically comprising the following steps:

[0015] T1, first construct a five-dimensional feature vector for each device: V = [μ,σ,S,K,P], wherein: μ is the average time interval, σ is the standard deviation of the time interval, S is the skewness of the time interval, K is the kurtosis of the time interval, and P is the proportion of messages in a specific time interval range;

[0016] T2, then calculate the similarity between two devices, the specific calculation formula is as follows:

[0017] L(V1,V2)=similarity_score(V1,V2,W)>threshold;

[0018] Wherein: L(V1, V2) is a Boolean value, indicating whether the two devices are on the same link, V1 and V2 are the standardized feature vectors of the two devices, W is the feature weight vector, which can be set as [0.3, 0.25, 0.15, 0.15, 0.15], and threshold is the determination threshold, which can be initially set as 0.95.

[0019] T3, finally using Python to implement single-link clustering algorithm for clustering analysis, so that the hybrid networking system can automatically run to calculate the node devices on the same DALI link.

[0020] Preferably, the characteristic values of different communication characteristics in step S2 include: average time interval μ, standard deviation σ of time interval, skewness S of time interval, kurtosis K of time interval and message proportion P in a specific time interval range, and the similarity calculation of characteristic values in step S2 includes: constructing a feature vector with the characteristic values, calculating whether the Boolean value between two devices is greater than the threshold value, and determining that the two devices are on the same link if the threshold value is greater than the threshold value, constructing a similarity matrix for a plurality of pairs of devices with similarity greater than the threshold value, using a single-link clustering algorithm to determine all devices on the same DALI link, and marking as the same block.

[0021] Preferably, the average time interval μ reflects the overall communication frequency of the DALI link, which helps to identify the DALI system under different load conditions, and the calculation function expression is as follows:

[0022] μ = (1 / n) * Σ(t[i]-t[i-1]);

[0023] Where: t[i] is the timestamp of the i-th message, n is the total number of messages, a high-precision timer is used to record the arrival time of each DALI message, and the time difference between adjacent messages is calculated.

[0024] The standard deviation σ of the time interval is used to measure the fluctuation degree of the communication interval, which can distinguish between stable lighting control systems and systems with large fluctuations, and the expression is as follows:

[0025] σ = sqrt((1 / n) * Σ((t[i]-t[i-1]-μ)^2));

[0026] Using the same data as the average time interval, the deviation of each interval from the average value is calculated.

[0027] Preferably, the skewness S of the time interval is used to describe the asymmetry of the time interval distribution, which helps to identify abnormal communication patterns in the DALI system, and the expression of the skewness S of the time interval is as follows:

[0028] S = (1 / n) * Σ(((t[i]-t[i-1]-μ) / σ)^3);

[0029] Using the same data as the previous two features, the cube of the normalized deviation of each interval is calculated.

[0030] The kurtosis K of the time interval is used to reflect the sharpness or flatness of the time interval distribution, and can detect the burst communication behavior in the DALI system, and the expression of the skewness S of the time interval is as follows:

[0031] K=(1 / n)*Σ(((t[i]-t[i-1]-μ / σ)^4))-3;

[0032] Using the same data as the foregoing features, the fourth power of the standardized deviation of each interval is calculated, and then 3 is subtracted;

[0033] Preferably, the proportion of messages in the specific time interval range P, such as the proportion of messages less than 10ms. Used to quantify the frequency of a specific type of communication, which helps to distinguish different types of DALI control strategy, the expression is as follows:

[0034] P=(the number of messages meeting the conditions / the total number of messages)*100%;

[0035] According to the window time interval range, the number of messages falling within the range is counted.

[0036] For devices with a similarity greater than a threshold, a similarity matrix is constructed, and a single-link clustering algorithm is used to determine all devices on the same DALI link, which are marked as the same block. In order to facilitate the construction of the similarity matrix and the calculation, when a link has more than two node devices, these node devices will be pairwise similarity matrix and clustering operation, node devices in the same DALI priority link have very high similarity, and when pairwise clustering analysis is performed, devices with differences can be clearly distinguished. The pair of devices with differences may be that one of them does not belong to the same link, or both do not belong to the same link of other node devices. The specific judgment is made according to the conclusion of the pair of devices and other node devices in the pair clustering analysis.

[0037] Preferably, the node score in step S3 is the data used for node core score, which specifically includes DALI communication quality score, wireless communication connection strength score and topology centrality score. The DALI communication quality score is more helpful to judge whether the node device is in the same link. The wireless communication connection strength score focuses on evaluating the advantages and disadvantages of the node device as a hybrid networking system interface wireless communication function. The combination of the first two kinds of data and the topology centrality score can evaluate the importance of the node position and the comprehensive situation of the communication influence. The topology centrality score uses data including degree centrality, betweenness centrality and closeness centrality. The degree centrality is the most basic centrality index, which measures the number of connections of a node, i.e. the number of edges directly connected to the node. The higher the degree centrality of a node, the more nodes it directly connects.

[0038] Betweenness centrality measures the "bridge" role of a node in the network, i.e., the number of shortest paths that pass through the node connecting other pairs of nodes. The higher the betweenness centrality of a node, the stronger its control over the network and the greater its influence on information flow.

[0039] Closeness centrality measures the average distance of a node to all other nodes in the network. The higher the closeness centrality of a node, the shorter the average distance to all other nodes, and thus the higher the efficiency of information propagation.

[0040] Preferably, the data acquisition window period in step S1 adopts a sliding window method for dynamic data capture, which is used to dynamically capture the time characteristics of DALI communication. The system sets a fixed time window, and the window size should be large enough to capture representative communication patterns, but not too large to reflect recent changes. Within the time window, the arrival time of each DALI message is continuously recorded, and the time interval between adjacent messages is calculated. For example, if the window is set to 10 minutes, and there are 50 data points per minute on average, then the 10-minute window contains about 500 data points. The window slides forward by one position each time a new DALI communication data point is received, and the oldest data point is removed from the window. The new data point is added to the window, and the data in the window is stored using a circular buffer with a size equal to the window size. The new data overwrites the oldest data.

[0041] Preferably, the moving average method in step S5 selects an exponential moving average method.

[0042] The application also provides a DALI and wireless communication hybrid network self-organizing scheduling system for executing the DALI and wireless communication hybrid network self-organizing scheduling method of any one of claims 1-8. The system includes a plurality of wireless communication devices and a plurality of DALI buses. Each DALI bus includes a plurality of DALI devices and a plurality of DALI-compatible wireless communication devices. According to the standard specification of the DALI bus, the number of devices on a link usually does not exceed 64. Therefore, as the application area of a smart building increases, the DALI bus link and DALI devices will also increase. The DALI-compatible wireless communication device is usually connected to the DALI bus link by a signal line. It has a wireless communication module and an embedded wireless communication program, and communicates with other wireless communication devices using the same communication protocol.

[0043] Preferably, each device has a unique and non-repeated device address; when identifying the search device, if the device address identified by the DALI communication and the wireless communication is repeated, the device with the address is marked as a DALI compatible wireless communication device, and the DALI bus is usually deployed as a bus link according to its standard specification, and after the normal operation is completed, the master device in the bus link allocates addresses for other DALI devices on the link. The device with only wireless communication function usually writes the unique and non-repeated device address when the embedded program is burned before leaving the factory. After the DALI compatible wireless communication device allocates the device address in the bus link, the device address of all devices in the link is packaged into a library and sent to the outside, and the address database formed by the device capable of wireless communication is compared. If the address is repeated, the address of the DALI compatible wireless communication device, i.e. the node device, is determined and changed. In the mixed networking system, the data repetition in the device address library within the DALI bus range is not allowed, and the data repetition of the device address in the wireless communication database is not allowed.

[0044] (Three) beneficial effects

[0045] The application provides a DALI and wireless communication mixed network self-organizing scheduling method. Compared with the prior art, the DALI and wireless communication mixed network self-organizing scheduling method has the following beneficial effects: the DALI and wireless communication mixed network self-organizing scheduling method solves the problems of wireless data sensing and data transmission in the communication nodes in the DALI wired link, provides a core basic solution of the communication layer and the scheduling layer for intelligent system deployment and management, improves the communication efficiency of the mixed networking system, and reduces the overall data transmission operation load of the system. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 A mixed networking system schematic diagram for running the DALI and wireless communication mixed network self-organizing scheduling method of the application;

[0047] Figure 2 A mixed networking system schematic diagram for running the DALI and wireless communication mixed network self-organizing scheduling method of the application in the case that the wireless communication is shielded by a wall. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0049] DALI compatible wireless communication device refers to a device such as a sensor circuit board connected with DALI communication and wireless communication component modules, and its embedded program supports the device to carry out DALI wired communication and wireless communication. In a hybrid network, such devices act as communication nodes, which can receive and forward data between devices that only support wireless communication and devices that only support DALI communication. For the convenience of description, the DALI compatible wireless communication device is referred to as node hereinafter.

[0050] There are many types of wireless communication, including Bluetooth BLE, 2.4G, ZigBee, LoRa, etc. Through the method of the application, the wireless communication device only needs to change the parameter value used in part of the method steps according to its own communication characteristics, which can achieve the purpose of the application. For the convenience of description, Bluetooth BLE is used to illustrate the specific embodiments, and other wireless communication methods also belong to the protection scope of the application when using the same or similar method steps and program algorithms.

[0051] As shown in Figure 1 The hybrid networking system running the method has at least one device on each DALI wired communication link that supports both DALI communication and wireless Bluetooth communication. The interaction relationship of wireless communication devices can be established by manual debugging or automatically established by the system running the automatic debugging program. This technical feature is not the core content of the method of the application and will not be explained. It should be noted that even if the wireless communication devices do not establish an interaction relationship with each other, the subsequent method steps can still be run. At this time, when performing subsequent characteristic value analysis and similarity analysis, the node device needs to collect data information of each device that can communicate wirelessly. Figure 1 When the wireless communication devices have formed the interaction connection relationship as shown, the hybrid networking system can analyze the data according to the specific interaction relationship of the wireless communication, saving the calculation example.

[0052] As shown in Figure 1 DALI bus one and DALI bus two are two relatively independent subsystems. In general, if the bus link master does not have the function of communicating with other link masters, for example, the master device is not compatible with PLC. Then the data of the two link information is relatively independent. The node device in the figure can be a master or a normal device such as a lighting fixture, a sensor, etc., and does not necessarily perform all functions of the master.

[0053] DALI bus one is assigned device addresses 1, 2, 3, and 4 by the master. Among them, devices 1 and 3 are found to have duplicate addresses in the comparison of the two address databases of DALI and wireless Bluetooth communication when communicating wirelessly, and then devices 1 and 3 are marked as node devices, i.e. DALI compatible wireless communication devices.

[0054] The devices 1 and 3 can analyze the relevant data of the Bluetooth communication when performing the subsequent method steps, and can analyze only the nearby device addresses 21, 22, 23, 11, 12, 13, and 14 as needed, and other long-distance devices can be excluded even if they can communicate wirelessly, which is based on the fact that the wireless communication devices have already interacted and connected.

[0055] In general, the DALI link of a new project has human body sensors, intelligent lighting devices, and other distributed and evenly spaced devices that are compatible with Bluetooth communication. The retrofit project has already deployed a DALI link without any devices having Bluetooth communication functionality. In the retrofit process, if there are new sensors, lighting devices, controllers, and other functional devices, Bluetooth-compatible functional devices can be used, or a DALI and Bluetooth protocol conversion gateway can be added to achieve the same.

[0056] The system runs the device sensing program on the same DALI wired link to enable nodes with Bluetooth and DALI dual communication capabilities to automatically identify other nodes on the same DALI link.

[0057] First, extract the time characteristics of DALI communication: each node continuously listens to the communication messages on the DALI link. Record the arrival time of each message and calculate the time interval between adjacent messages. Use the sliding window method to calculate the time interval distribution characteristics within a certain time range.

[0058] The sliding window method is used to dynamically capture the time characteristics of DALI communication. The system sets a fixed time window, which should be large enough to capture representative communication patterns, but not too large to reflect recent changes. Within the time window, continuously record the arrival time of each DALI message and calculate the time interval between adjacent messages. For example, if the window is set to 10 minutes and there are 50 data points per minute of DALI communication, the 10-minute window contains approximately 500 data points.

[0059] The window slides, and each time a new DALI communication data point is received, the window slides forward one position, and the oldest data point is removed from the window, and the new data point is added to the window. Use a circular buffer to store the data in the window, and the buffer size is equal to the window size, and the new data covers the oldest data.

[0060] Define the feature value calculation trigger mechanism: calculate every 3 window periods of 30 minutes, or 500 data points to calculate the feature value.

[0061] To determine whether multiple nodes are on the same DALI link, a method based on eigenvalue similarity is proposed. This method uses the following communication eigenvalues: average time interval μ, time interval standard deviation σ, time interval skewness S, time interval kurtosis K, message proportion within a specific time interval range P, to determine the link relationship between devices through the following steps and function expressions.

[0062] Average time interval: reflects the overall communication frequency of the DALI link, and helps identify DALI systems under different load conditions. The calculation function expression is: μ=(1 / n)*Σ(t[i]-t[i-1]), where t[i] is the timestamp of the ith message, and n is the total number of messages. Use a high-precision timer to record the arrival time of each DALI message. Calculate the time difference between adjacent messages.

[0063] Time interval standard deviation: measures the degree of fluctuation of the communication interval, and can distinguish between stable lighting control systems and systems with large fluctuations. Expression: σ=sqrt((1 / n)*Σ((t[i]-t[i-1]-μ)^2)). Use the same data as the average time interval to calculate the deviation of each interval from the average value.

[0064] Skewness and kurtosis of time interval: skewness describes the asymmetry of time interval distribution, which helps identify abnormal communication patterns in DALI systems; kurtosis reflects the sharpness or flatness of time interval distribution, which can detect burst communication behavior in DALI systems.

[0065] Skewness expression: S=(1 / n)*Σ(((t[i]-t[i-1]-μ) / σ)^3). Use the same data as the previous two features to calculate the cube of the normalized deviation of each interval;

[0066] Kurtosis expression: K=(1 / n)*Σ(((t[i]-t[i-1]-μ) / σ)^4)-3. Use the same data as the previous features to calculate the fourth power of the normalized deviation of each interval, then subtract 3.

[0067] Message proportion within a specific time interval range, such as the proportion of messages less than 10ms. Quantify the frequency of a specific type of communication, which helps to distinguish different types of DALI control strategies. Expression: P=(number of messages meeting the condition / total number of messages)*100%. According to the window time interval range, count the number of messages falling within the range.

[0068] First, construct a five-dimensional feature vector V=[μ,σ,S,K,P] for each device.

[0069] Second, calculate the similarity between two devices:

[0070] L(V1,V2) = similarity_score(V1,V2,W) > threshold. Where: L(V1, V2) is a Boolean value indicating whether the two devices are on the same link. V1 and V2 are the normalized feature vectors of the two devices. W is the feature weight vector, which can be set to [0.3, 0.25, 0.15, 0.15, 0.15]. threshold is the decision threshold, which can be initially set to 0.95.

[0071] Finally, the single-linkage clustering algorithm was implemented in Python for cluster analysis. The algorithm implementation code is as follows:

[0072] def cluster_devices_by_link(devices, threshold=0.95, weights=[0.3,0.25, 0.15, 0.15, 0.15]):

[0073] n = len(devices)

[0074] similarity_matrix = np.zeros((n, n))

[0075] # Constructing a similarity matrix

[0076] for i in range(n):

[0077] for j in range(i+1, n):

[0078] sim = similarity_score(devices[i].features, devices[j].features, weights)

[0079] similarity_matrix[i][j]= similarity_matrix[j][i]= sim

[0080] # Clustering based on similarity matrix

[0081] links = []

[0082] unassigned = set(range(n))

[0083] while unassigned:

[0084] current = unassigned.pop()

[0085] current_link = {current}

[0086] for device in unassigned.copy():

[0087] if similarity_matrix[current][device]>threshold:

[0088] current_link.add(device)

[0089] unassigned.remove(device)

[0090] links.append(current_link)

[0091] return links

[0092] Thus the hybrid networking system can automatically run the calculation to obtain the node devices in the same DALI link.

[0093] Each of the foregoing feature values can be updated using an exponential moving average method, which is suitable for adding or replacing a node device in a certain DALI link. The exponential moving average Exponential Moving Average method updates the feature value, which is denoted as EMA in the formula to reflect the dynamic change of the link communication mode. The simple average value of the first window is used as the initial EMA_old. Subsequently, the iteration update is performed according to the system requirement.

[0094] The EMA update formula is EMA_new = a * new feature value + (1-a) * EMA_old, wherein a is a smoothing factor, which can be adjusted as required, and the a value ranges from 0 to 1. A smaller a gives a greater weight to historical data, making the EMA less sensitive to new data changes. A larger a makes the EMA more quickly react to new data. The smoothing factor a is set by the engineers according to the system requirements of the project and implementation experience.

[0095] The selection method of a can be selected as follows: 1 based on time period: a = 2 / (N+1), wherein N is the expected EMA tracking period. 2 adaptive method: dynamically adjust a according to the degree of data fluctuation. When the data fluctuation is large, increase the a value; when the data fluctuation is small, decrease the a value. It can start from 0.1 and be adjusted to the best value through data fluctuation experiments.

[0096] After judging and confirming that a plurality of devices are on the same DALI link, the nodes on the same DALI link generate a DALI block by themselves, and a block core node needs to be selected from the plurality of devices. The DALI link has only one device compatible with DALI and Bluetooth communication, and the device is automatically the block core node.

[0097] In order to select the optimal block core node as the communication bridge between the DALI link and the Bluetooth network, the following method steps can be used:

[0098] First, node scoring calculation is performed, and a comprehensive score is calculated for each node. The following factors need to be considered in this process:

[0099] DALI communication quality score D: calculated based on DALI communication time characteristic values, only between devices on the same link, compatible with Bluetooth and DALI communication, and only considering relevant data of DALI communication.

[0100] Bluetooth connection strength score B, i.e. wireless communication connection strength score: calculated based on signal strength RSSI with other Bluetooth devices, including devices compatible with Bluetooth and DALI communication, and devices only with Bluetooth communication function; only considering relevant data of Bluetooth communication.

[0101] Node centrality score C: reflects the importance of the position of the node in the network.

[0102] DALI communication quality score D calculation includes: using the characteristic values in the aforementioned DALI link awareness mechanism, normalizing each characteristic value to the [0, 1] interval, and using the calculation formula:

[0103] D = w1*(1 / average time interval) + w2*(1 / standard deviation) + w3*specific range message proportion. Where w1, w2, w3 are weight coefficients, and the sum is 1. One embodiment is: the average time interval weight w1 directly reflects the efficiency and response speed of DALI communication, and can be set to 0.4; the standard deviation w2 is set to 0.3 to reflect the stability and consistency of the communication time; the specific range message proportion w3 is set to 0.3.

[0104] Bluetooth connection strength score B calculation includes: collecting RSSI values with all other devices; mapping the RSSI values to the [0, 1] interval, -30 dBm is mapped to 1, and -90 dBm is mapped to 0; B = Σ(mapped RSSI values) / total number of nodes. When applying the method of the present application to devices of other wireless communication protocols, the evaluation of the communication embedded end RSSI value needs to be adapted.

[0105] The node core score C is calculated as C = a*T + b*D + g*B. Wherein: C is the final centrality score of the node, T is the topological centrality score, D is the DALI communication quality score, and B is the Bluetooth connection strength score. a, b, g are weight coefficients which are input into the system according to the actual situation of the engineering project, and a+b+g=1.

[0106] The calculation method of the topological centrality score T is as follows: a network topology graph is constructed, the nodes are vertices, and the Bluetooth connections are edges; the DC of each node is the degree centrality, the BC is the betweenness centrality, and the CC is the closeness centrality. T = z1*DC + z2*BC + z3*CC, z1, z2, z3 are weight coefficients which are input into the system according to the actual situation of the engineering project, and z1+z2+z3=1.

[0107] The degree centrality DC, the betweenness centrality BC, and the closeness centrality CC are three commonly used centrality indexes in network analysis, which are used to evaluate the importance of nodes in the network. They are common technical contents in the field of network analysis, and their specific formulas and calculation methods are not described in detail. In addition to this, eigenvector centrality, Katz centrality, harmonic centrality, and other characteristic data in the field of network analysis and topological centrality can also be used. It should be understood that different characteristic data or different arrangements and combinations of these characteristic data can be selected according to the actual situation of the project. If the process steps described in the method of the present application or similar technical features and formulas are still used, they should also be within the protection scope of the present application.

[0108] The core node selection is as shown in Figure 1 All nodes in the block of the bus 1 exchange their respective node core scores C; the node with the highest score is selected as the block core node; if the scores are the same, the node 1 device with the smallest device address value is selected as the core node.

[0109] The core node selection is as shown in Figure 2 The wireless communication is shielded by the wall, and the Bluetooth devices on both sides of the wall cannot communicate at all. However, the DALI wiring passes through the wall without affecting the communication. Therefore, when scoring, the node 6 has the relevant data characteristic values of the Bluetooth devices 14, 15, 16, and 17, and does not have the relevant data of the devices 21, 22, and 23. Therefore, the ground 6 is evaluated as a core node. Similarly, the nodes 1 and 3 only have the data of the devices 21, 22, and 23. Therefore, on the side below the wall in the figure, one of the nodes 1 or 3 should be selected as a core node to support the Bluetooth communication on that side.

[0110] The core node selection is as shown in Figure 2DALI data transmission is feedback, assuming that the core node 6 and core node 1 received at the same time the wireless communication data of the side, to the other side of the wall when the transfer may exist conflict, can be arranged in order of device address value size transfer, assuming that the data crash failure, core node not in the predetermined time to receive data transmission feedback, then the program randomly a time gap, and then resend the data to be delivered. Random time gap can maximize the possible to avoid data crash again.

[0111] In the system, the device appears malfunction, replacement, new, etc. After the situation, the score is recalculated and the core node is updated. The performance of the core node is monitored, and if there is an abnormality such as an increase in communication delay, a re-election block core node is triggered. The method steps can use the foregoing, but the specific data, characteristic values will change.

[0112] Meanwhile, the contents not described in detail in the specification all belong to the prior art known to those skilled in the art.

[0113] It should be noted that in this paper, such as the first and second relationship terms are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the term "includes", "contains" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device.

[0114] Although embodiments of the present application have been shown and described, it will be understood by those having ordinary skill in the art that various changes, modifications, substitutions and alterations can be made thereto without departing from the principles and spirit of the present application, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for self-organizing scheduling in a hybrid DALI and wireless communication network, characterized in that: Specifically, the following steps are included: S1. By using DALI-compatible wireless communication devices as hybrid network communication nodes, and then automatically running the sensing program for DALI-compatible wireless communication devices on the same link, feature value calculation is performed using the data within the set data acquisition window period. S2. Calculate similarity by combining feature values ​​of different communication characteristics to identify whether devices are connected to the same wired link. Then, devices on the same DALI link are marked as the same DALI block. S3. When there are multiple DALI-compatible wireless communication devices in the same DALI block, calculate the score data of each node and select the device with the highest score as the core node of the link. S4. Select the DALI link of the core node, and use this node as the receiving and transmitting device for external wireless communication of this link; S5. When the hybrid network system detects a new node device, a replacement of the original core node device, or a failure, the system uses the moving average method to update, automatically collects new feature values, and re-runs the aforementioned program to determine the new core node. Step S2, which identifies whether the devices are connected to the same wired link, specifically includes the following steps: T1. First, construct a five-dimensional feature vector for each device: V = [μ,σ,S,K,P], where: μ is the average time interval, σ is the standard deviation of the time interval, S is the skewness of the time interval, K is the kurtosis of the time interval, and P is the proportion of messages within a specific time interval range. T2. Next, the similarity between the two devices is calculated. The specific calculation formula is as follows: L(V1,V2)=similarity_score(V1,V2,W)>threshold; Where: L(V1, V2) is a Boolean value indicating whether the two devices are on the same link, V1 and V2 are the standardized feature vectors of the two devices, W is the feature weight vector, and threshold is the decision threshold; T3. Finally, Python is used to implement the single-link clustering algorithm for cluster analysis, so that the hybrid networking system can automatically calculate the node devices on the same DALI link.

2. The method for self-organizing scheduling in a hybrid DALI and wireless communication network according to claim 1, characterized in that: The feature values ​​of different communication characteristics in step S2 include: average time interval μ, standard deviation of time interval σ, skewness of time interval S, kurtosis of time interval K, and message proportion P within a specific time interval range. The similarity calculation of feature values ​​in step S2 includes: constructing feature vectors with feature values, calculating whether the Boolean value between two devices is greater than a judgment threshold. If it is greater than the threshold, the two devices are determined to be on the same link. A similarity matrix is ​​constructed for multiple pairs of devices with similarity greater than the threshold. A single-link clustering algorithm is used to determine all devices on the same DALI link and mark them as the same block.

3. The method for self-organizing scheduling in a hybrid DALI and wireless communication network according to claim 2, characterized in that: The average time interval μ reflects the overall communication frequency of the DALI link, which helps to identify DALI systems under different load conditions. The calculation function expression is as follows: μ=(1 / n)*Σ(t[i]-t[i-1]); Where: t[i] is the timestamp of the i-th message, n is the total number of messages, a high-precision timer is used to record the arrival time of each DALI message, and the time difference between adjacent messages is calculated; The standard deviation σ of the time interval is used to measure the degree of fluctuation in the communication interval, and the expression is as follows: σ=sqrt((1 / n)*Σ((t[i]-t[i-1]-μ)^2)); Using the same data as the average time interval, calculate the deviation of each interval from the average.

4. The method for self-organizing scheduling in a hybrid DALI and wireless communication network according to claim 2, characterized in that: The skewness S of the time interval is used to describe the asymmetry of the time interval distribution, which helps to identify abnormal communication patterns in the DALI system, and the expression for the skewness S of the time interval is as follows: S=(1 / n)*Σ(((t[i]-t[i-1 -μ) / σ)^3); Using the same data as the first two features, calculate the cube of the standardized deviation for each interval; The kurtosis K of the time interval is used to reflect the steepness or flatness of the time interval distribution, and can detect burst communication behavior in the DALI system. The expression for the skewness S of the time interval is as follows: K=((1 / n)*Σ(((t[i]-t[i-1]-μ / σ)^4))- 3; Using the same data as described above, calculate the fourth power of the standardized deviation for each interval, and then subtract 3.

5. The method for self-organizing scheduling in a hybrid DALI and wireless communication network according to claim 2, characterized in that: The proportion P of messages within the specific time interval is used to quantify the frequency of specific types of communication, which helps to distinguish different types of DALI control strategies. The expression is as follows: P = (Number of messages that meet the criteria / Total number of messages) * 100%; Count the number of messages that fall within the window time interval range.

6. The method for self-organizing scheduling in a hybrid DALI and wireless communication network according to claim 1, characterized in that: The node score in step S3 is the data used for the node coreity score, specifically including DALI communication quality score, wireless communication connection strength score, and topology centrality score. The topology centrality score uses three types of data: degree centrality, betweenness centrality, and proximity centrality.

7. The method for self-organizing scheduling in a hybrid DALI and wireless communication network according to claim 1, characterized in that: In step S1, the data acquisition window period adopts the sliding window method for dynamic data capture. The sliding window method is used to dynamically capture the time characteristics of DALI communication. The system sets a fixed time window. Within the time window, the arrival time of each DALI message is continuously recorded, the time interval between adjacent messages is calculated, and the window slides. When a new DALI communication data point is received, the window slides forward one position. The oldest data point is removed from the window, and the new data point is added to the window. A circular buffer is used to store the data in the window. The size of the buffer is equal to the size of the window. New data overwrites the oldest data.

8. The method for self-organizing scheduling in a hybrid DALI and wireless communication network according to claim 1, characterized in that: In step S5, the moving average method selected is the exponential moving average method.

9. A system for self-organizing scheduling in a hybrid DALI and wireless communication network, characterized in that, The method for self-organizing scheduling of a hybrid DALI and wireless communication network according to any one of claims 1-8, the system comprising a plurality of wireless communication devices and a plurality of DALI buses, each DALI bus comprising a plurality of DALI devices and a plurality of DALI-compatible wireless communication devices.

10. A system for self-organizing scheduling in a hybrid DALI and wireless communication network according to claim 9, characterized in that, Each device has a unique and non-repeating device address; when identifying and searching for devices, if the device address of the DALI communication and wireless communication identifiers is found to be duplicated, the device with that address is marked as a DALI-compatible wireless communication device.

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