CN108599975A - a kind of intelligent building management system - Google Patents

Abstract

The invention belongs to the technical field of building intelligence, and discloses an intelligent building management system, which includes a central monitoring system, a wireless access control subsystem, an air conditioning subsystem, an elevator automatic control subsystem, a lighting subsystem, and a transformer Distribution subsystem, water supply and drainage subsystem, security subsystem, garage management subsystem, TV monitoring subsystem, environmental monitoring subsystem, smart home subsystem. In the present invention, the power supply system supplies power to each subsystem and the central monitoring system respectively; the system is advanced in technology, economical and practical, safe and reliable, excellent in quality, and widely used; the simulation experiment and data results of the present invention show that the HP2P network load balancing method is very good Solved the problem of unbalanced load between groups and within groups of HP2P network. If this invention is applied to the HP2P-based network, the performance of the HP2P-based network software will be greatly improved.

Description

An Intelligent Building Management System

technical field

The invention belongs to the technical field of building intelligence, and in particular relates to an intelligent building management system.

Background technique

At present, with the continuous development of society, home safety is the basis for people to live and work in peace and contentment, and it is also an important link in building a harmonious society. Especially in residential areas that are relatively scattered, remote, and with a relatively complex environment, the security situation is not optimistic. Traditional security management methods such as guard duty and security patrols can no longer meet the needs of residential security under the new situation. Therefore, in order to meet the needs of residential community users for safety and scientific and systematic management, and to fully and timely understand and grasp the situation that occurs at any time, it can quickly make correct judgments on unexpected situations and give correct and rapid instructions and processing. Establishing an intelligent building management system to contain some hazards and hidden dangers in the bud, prevent property loss, and ensure the safety of personnel is of great significance for building a safe and harmonious residential community. However, the existing intelligent building management system mainly has the following disadvantages: the price is expensive, and there is no intelligent building management system that is suitable for the needs of ordinary residential quarters and can be widely popularized. It is impossible for the subsystems to share information, which makes it impossible for the administrator to monitor the subsystems in the building when managing the building. The management cost is high and the management is inefficient. The system linkage is poor, not perfect, not comprehensive enough, the control mechanism is relatively complicated, the response time is relatively long, and it is inconvenient to use. Common access control identification cards use radio frequency identification technology, generally the recognition distance is very short, and users need to bring the access control card close to the sensing area to pass the verification, which is inconvenient in practical applications.

In recent years, with the rapid development of peer-to-peer network technology, software based on peer-to-peer (Peer-to-Peer, P2P) network technology has been favored by a large number of Internet users. The problem of network balance management in building management is becoming more and more prominent; the existing technology only solves it by increasing the transmission power; but it causes a waste of resources; it cannot be effectively balanced in use.

Now some domestic popular network software such as Xunlei, Tencent QQ, PPTV, Kugou Music, etc. all use P2P network technology. In P2P network software, due to the unbalanced resource demand of users and the heterogeneity of computer capabilities in the network, the load imbalance of nodes (computers in the P2P network) always exists in the P2P network. In recent years, with the rapid growth of P2P network software users, the phenomenon of node load imbalance in the network has become more and more obvious, which in turn causes problems such as request delay and network congestion, which seriously affects the overall performance of the P2P network.

Currently, the research on load balancing in P2P networks is mainly concentrated in the field of structured P2P networks, and some representative methods to solve this problem have appeared. For example, the virtual server method (VirtualServer), the multi-hash selection method (Power of Two Choices), the address space balancing method (Address-Space Balancing), and the storage file balancing method (Item Balancing). in:

Virtual server method: In a P2P network, each physical node is virtualized into multiple virtual servers, and each virtual server maintains an address space independently. Each virtual server has its own independent routing table and data objects. When data objects need to be located, the positioning process is initiated on the virtual server, not on the actual node. When the load of a node is too heavy or too light, the virtual server is the smallest load migration unit. The virtual node on one physical node "leaves the network", and at the same time in another physical node, the "leaved" virtual node rejoins the network, and finally receives the data object responsible for the virtual node to complete the load migration. Since each virtual server needs to maintain its own routing table, this is equivalent to a physical node needing to maintain multiple routing tables, which will waste a lot of bandwidth. At the same time, since a physical node manages multiple virtual servers in the P2P network, when a physical node joins or leaves the network, it is equivalent to having multiple virtual servers join or leave the network, which will greatly increase the jitter of the network, which will It has a fatal impact on the already poorly structured P2P network.

Multi-hash selection method: This method assumes that there are d>=2 well-known hash functions h1(),...,hd(). When a node in a structured P2P network needs to add a resource x to the network, the node will calculate d hash values h1(x),...,hd(x) for the resource x according to d hash functions. Then the node will ask the nodes responsible for maintaining the d hash values in the structured P2P network about their current load conditions, and select a node A with the lightest load from the d nodes to be responsible for maintaining the index of resource x, At the same time, the other d-1 nodes will store a pointer to node A. At the same time, each node in the network has a load trigger. When the load of a node is too large, the trigger event will be triggered. The trigger event selects resource indexes to be migrated, and then transfers these resources to other nodes by rejoining the network.

Address space balance method: This method assumes that each node in the network has O(logN) potential IDs in the structured P2P network, but only one ID is active at a time. The node determines its own ID according to the current load situation of the entire network to complete the migration between loads, so as to realize the load balance of the P2P network.

Unstructured P2P networks based on flooding and structured P2P networks based on Distributed Hash Table (DHT) are popular P2P networks in the current P2P application field. Among them, the unstructured P2P network structure is relatively simple, easy to implement, and has high stability, but its network load is high and its scalability is poor; the structured P2P network has a small network load and high query efficiency, but its stability is low. Difference. Hybrid Hierarchical P2P Network (HP2P for short) combines the respective advantages of structured P2P and unstructured P2P to obtain a new type of P2P network with high stability, high query efficiency and good scalability.

In HP2P, the nodes in the network are firstly organized in the form of a cluster, and the cluster internally uses the flooding method in the unstructured P2P network to transmit messages. The group consists of a small number of super nodes and a large number of ordinary nodes. Groups are organized into a structured P2P network using the improved Chord protocol. Each group exists as a virtual node on Chord, and the routing table of the virtual node is jointly maintained by several super nodes in the group. The communication between ordinary nodes in the group and the upper Chord network needs to be forwarded through these super nodes.

Due to the particularity of the HP2P network topology, none of the current load balancing methods for structured P2P networks can solve the problem of load balancing among HP2P network groups. At the same time, due to the heterogeneity of node capabilities in the group and the need to maintain the metadata (resource index) published by other nodes in the network, the load balancing problem of the network in the group is very different from the traditional unstructured P2P network load balancing problem. .

Due to the complex and changeable noise environment of space communication and the increasingly serious interference problem, the signal is easily affected by it and presents a weak state. Therefore, improving the detection and parameter estimation of weak signals under low SNR conditions in deep space communication is an urgent problem to be solved. PSK signal is a digitally modulated signal with phase modulation and constant amplitude. Because of its strong anti-interference ability and the advantages of widening the bandwidth of the signal, it is often used as a signal type commonly used in communication, and is widely used in pulse compression signal transmission.

But the prior art has poor signal estimation ability.

In summary, the problems in the prior art are: expensive, and there is no intelligent building management system that is suitable for the needs of ordinary residential quarters and can be widely popularized. It is impossible for the subsystems to share information, which makes it impossible for the administrator to monitor the subsystems in the building when managing the building. The management cost is high and the management is inefficient. The system linkage is poor, not perfect, not comprehensive enough, the control mechanism is relatively complicated, the response time is relatively long, and it is inconvenient to use. Common access control identification cards use radio frequency identification technology, generally the recognition distance is very short, and users need to bring the access control card close to the sensing area to pass the verification, which is inconvenient in practical applications.

Contents of the invention

Aiming at the problems existing in the prior art, the invention provides an intelligent building management system.

The present invention is realized in this way. An intelligent building management system includes a central monitoring system, a wireless access control subsystem, an air-conditioning subsystem, an elevator automatic control subsystem, a lighting subsystem, a distribution electronic system, Water supply and drainage subsystem, security subsystem, garage management subsystem, TV monitoring subsystem, environmental monitoring subsystem, smart home subsystem. Each subsystem is wirelessly connected to the central monitoring system via Ethernet. The power supply system supplies power to each subsystem and the central monitoring system respectively.

The security subsystem is integrated with a building HP2P network load balancing module and a carrier frequency estimation module for PSK signals under network signal distribution noise; the building HP2P network load balancing module and carrier frequency estimation module are all wirelessly connected to the central monitoring system;

The building HP2P network load balancing method of the building HP2P network load balancing module includes:

1) The method of load balancing among HP2P network groups: the load transfer between groups is realized through group splitting and the movement of groups in the network address space, and the splitting and merging of groups is induced by adding new nodes to groups with larger loads, so that the load The number of larger address space groups increases, and the number of address space groups with smaller loads decreases, where the load is defined as the average number of messages that nodes in the group need to process per unit time;

2) The method of load balancing in the HP2P network group. Through the effective scheduling of the load in the group by super nodes, the nodes with a lower load rate in the group can find the nodes with a higher load rate in the group. According to the characteristics of the HP2P network, the load is approximately defined is the number of metadata that nodes in the group need to maintain, the load rate is defined as the ratio of load to node capability, and the metadata is the index of resources;

In the carrier frequency estimation method of the PSK signal under the network signal distribution noise of the described carrier frequency estimation module, the PSK signal is a signal in the HP2P network; specifically includes:

Calculate the cyclic covariant function for the received PSK signal containing distributed noise;

Carry out Fourier transform to described cyclic covariation function, seek its cyclic covariation spectrum;

Extracting a cross-section with a cyclic frequency ε=0 Hz through the cyclic covariation spectrum;

Search for the peak values of the positive and negative semi-axes of the section, find the positive and negative frequency values corresponding to the peak values, take the absolute value and calculate the mean value as the estimated value of the carrier frequency.

Further, the method for load balancing between the HP2P network groups includes:

Step (1) The supernode S of group A randomly sends a group load request message to the surrounding k·log ₂ N groups, obtains the load information of the k·log ₂ N groups, and calculates the k·log ₂ N The average load of each group is used to estimate the average load Load _avg of the entire HP2P network, where k is an integer in the interval [1, N/log ₂ N], and N is the number of groups in the network;

Step (2) If the current load of group A is Load>γ·Load _avg , and the number of nodes in the two small groups that the group splits into is both greater than the lower limit of the number of nodes in the HP2P network group, split the group into two groups, where γ is A real number greater than 1, the execution of the method for load balancing between HP2P network groups ends this time; otherwise, go to step (A3);

Step (3) Construct the Chord ring in the HP2P network. Group A sends a load request message to its predecessor group and successor group to obtain the current load conditions of the predecessor group and successor group. The predecessor group is the closest outlier A in the Chord ring of the HP2P network. The previous group of , and the successor group is the next group closest to outlier A in the Chord ring of the HP2P network;

Step (4) If the current load of group A is Load>Load _avg , then go to step (A5), if Load<Load _avg , then go to step (A8); otherwise, the method of load balancing between HP2P network groups ends;

Step (5) If the load of group A is Load≥Load _light /(1-2·β), reduce its own load by β, where β is a real number with a value in the interval (0,0.5), and go to step (A6 ); Otherwise, go to step (A8); wherein Load _light is the load of the group with the smaller load in the predecessor group and the successor group of the group;

Step (6) If the Load _light is the load of the predecessor group of group A, then group A notifies its predecessor group to move clockwise along the Chord ring, and the length of the moving address space is (Load-Load _light )×Length/(2×Load ), and transfer the corresponding metadata to the predecessor group, the execution of the method for load balancing between HP2P network groups ends this time, where Length is the length of the address space maintained by group A in the Chord ring; otherwise, go to step (A7) ;

Step (7) Load _light is the load of the successor group of group A, then the group moves counterclockwise along the Chord ring, the address space length of the move is (Load-Load _light )×Length/(2×Load), and the corresponding The metadata of the HP2P network group is transferred to the successor group, and then the execution of the method of load balancing between the HP2P network groups ends this time;

Step (8) If Load≤(1-2·β)·Load _heavy , go to step (A9); where Load _heavy is the load of the group with the heavier load in the predecessor group and the successor group of the group, and β is a load in The interval (0,0.5) is a real number, otherwise the execution of the HP2P network inter-group load balancing method ends;

Step (9) If Load _heavy is the load of the predecessor group of group A, then group A notifies its predecessor group to move counterclockwise along the Chord ring, and the length of the moving address space is (Load _heavy -Load)×Length _predecessor /(2× Load _heavy ), and obtain the corresponding metadata from the predecessor group, where Length _predecessor is the length of the address space maintained by the predecessor group in the Chord ring, and then the execution of the HP2P network inter-group load balancing method ends; otherwise, go to step (A10 );

Step (10) Load _heavy is the load of the successor group of group A, then group A moves clockwise along the Chord ring, and the length of the moving address space is (Load _heavy -Load)×Length _successor /(2×Load _heavy ), and The corresponding metadata is obtained from the successor group, where the Length _successor is the length of the address space maintained by the successor group in the Chord ring, and at this time, the execution of the load balancing method between HP2P network groups ends.

Further, the load balancing method in the common node group includes:

Step (1) Ordinary nodes obtain the current average load rate of the group from super nodes

Step (2) If the load rate of the node It is considered that the load rate of the node is high. At this time, the node will notify the super node in the group of its own load rate and the number of metadata that needs to be transferred to other nodes in the group. Then the execution of the load balancing method in the ordinary node group ends this time, where capacity is the capacity of the node, and α is a real number between the interval (1,2); otherwise, go to step (3);

Step (3) If the load rate of the node It is considered that the load rate of the node is low; at this time, the node notifies the super nodes in the group of its own load rate and the maximum number of metadata that can be received from other nodes in the group Among them, capacity is the capacity of the node, and the execution of the load balancing method in the common node group is completed this time.

Further, the cyclic covariation function of the received signal includes:

The signal contains an MPSK signal subject to SαS distributed noise, which can be expressed as:

where E is the average power of the signal, M=2 ^k , m=1,2,...M, q(t) represents the rectangular pulse waveform, T represents the symbol period, f _c represents the carrier frequency, φ ₀ represents the initial phase, if w(t) obeys SαS distribution of non-Gaussian noise, then its self-covariation function is defined as:

Where (x(t-τ)) ^<p - ^1> = |x(t-τ)| ^p-2 x*(t-τ), γ _x(t-τ) is the dispersion coefficient of x(t), Then the cyclic covariation of x(t) is defined as:

Among them, ε is called the cycle frequency, and T is a symbol period.

Further, the cyclic covariation spectrum of the received signal is performed as follows:

The cyclic covariation spectrum is the Fourier transform of the cyclic covariation function, expressed as:

Its cyclic covariation spectrum is derived as:

When M≥4, in place,

When M=2,

where Q(f) is the Fourier transform of q(t), and

Further, the carrier frequency estimation is realized by extracting the cross-section of cyclic frequency ε=0Hz in the cyclic covariation spectrum, as follows:

The envelope of the cyclic covariation spectrum on the n=0, ie, ε=0Hz section is:

When f=±f _c , the envelope takes the maximum value.

Further, the wireless access control subsystem includes two parts: an access control management module and an access control card, wherein the access control management module includes a reader, a terminal controller, and a transceiver antenna. The access control card includes a transceiver antenna and a transponder.

Further, the various subsystems are connected to the central monitoring system through Ethernet.

Further, the environmental monitoring subsystem includes an environmental monitoring host and temperature and humidity sensors, inhalable gas concentration detectors and harmful gas concentration detectors connected to it.

The advantages and positive effects of the present invention are: the system is advanced in technology, economical and practical, safe and reliable, excellent in quality and widely used.

The network load balancing method of the present invention draws by simulation:

Use PEERSIM simulation software to simulate the load balancing effect and parameter values of the present invention. Each experiment was repeated 20 times, and the experimental results are the average value.

For the simulation of the HP2P network load balancing method, we use different network configurations to simulate the present invention to determine whether the present invention is effective for HP2P networks under different conditions. The network simulation parameters are shown in Table 1.

Table 1 Simulation parameter setting of HP2P network load balancing method

After the present invention is added to the HP2P network, no matter in different network scales, different numbers of resources in the network, and different resource request rates, the relationship between the load of the most loaded group in the network and the average network load changes from 5 times to 2 times At the same time, the relative standard deviation of the group load dropped from about 1.0 to about 0.2. Therefore, after adding the load balancing method between HP2P network groups, the load balancing degree between HP2P network groups is greatly improved.

When the network scale keeps decreasing or remains unchanged, the group load balance degree and the number of metadata movement in the HP2P network are mainly determined by the value of the parameter β, and decrease with the increase of β; when β∈[0.4 ,0.5), the group load balance degree in the network decreases sharply with the increase of β, and when β∈[0.1,0.2], the amount of metadata movement also decreases rapidly with the increase of β; When the value is small, the group with large scale and heavy load can quickly reduce the load through group splitting, and basically will not introduce more metadata movement; therefore, the network scale is continuously reduced or generally remains the same , γ should take 2.0, and β can take a value in the interval [0.2,0.4]. When the network scale expands rapidly, the overall group load balance is relatively high, so γ takes 2.0, and β takes a value in the interval [0.4,0.5).

After adding the present invention in the HP2P network, regardless of different network scales and different numbers of resources in the network, the load rate of the node with the largest load rate in the HP2P network group is 4 to 7 times the average load rate in the group and falls below 2 times . The relative standard deviation of the load within the group also dropped from 0.7 to 1.1 to about 0.3. Therefore, the present invention also well improves the load balancing degree in the HP2P network group.

The ratio of the load rate of the node with the highest load rate in the group to the average load rate in the group and the relative standard deviation of the load rate in the group increase with the increase of parameter α, and the growth rate slows down with the increase of α . When the size of the network grows rapidly, the amount of metadata movement is much larger than the other two cases. This is because when a large amount of metadata is added to the network, the overall number of metadata in the entire network increases and in order for these newly released metadata to be placed to the appropriate location in the group, additional metadata transfer is required. When α is 1.2, the standard deviation of the load rate in the group is still greater than 0.2, which shows that the relative standard deviation of the load rate in the group is difficult to control within 0.2 because the nodes in the group continue to join and leave the network. Therefore, when α is set to 1.2, it will cause a large amount of node load information to be stored in the super node's hash table and ordered linked list. Therefore, the parameter α should take a value within the interval [1.4, 1.8], and the specific value can be determined according to the actual requirements for HP2P network software load balancing.

The above simulation experiments and data results show that the HP2P network load balancing method can well solve the problem of unbalanced load between groups and within groups of HP2P network. If this invention is applied to the HP2P-based network, the performance of the HP2P-based network software will be greatly improved.

The present invention can estimate the carrier frequency of the PSK signal under the distributed noise; The present invention has better estimation performance under the low SNR environment; In the same simulation experiment environment and the same symbol rate, carrier frequency, sampling frequency, Under the setting conditions of signal parameters such as number of sampling points and signal-to-noise ratio, the present invention has better estimation performance than existing methods. Provide guarantee for intelligent building network management.

Description of drawings

Fig. 1 is a schematic structural diagram of an intelligent building management system provided by an embodiment of the present invention.

Detailed ways

In order to further understand the content, features and effects of the present invention, the following examples are given, and detailed descriptions are given below with reference to the accompanying drawings.

The structure of the present invention will be described in detail below in conjunction with the accompanying drawings.

As shown in Figure 1, the intelligent building management system provided by the embodiment of the present invention includes a central monitoring system, a wireless access control subsystem, an air conditioning subsystem, an elevator automatic control subsystem, a lighting subsystem, and a distribution electronics subsystem respectively connected to the central monitoring system. System, water supply and drainage subsystem, security subsystem, garage management subsystem, TV monitoring subsystem, environmental monitoring subsystem, smart home subsystem. Each subsystem is wirelessly connected to the central monitoring system via Ethernet. There is a power supply system to supply power to each subsystem and the central monitoring system.

The security subsystem is integrated with a building HP2P network load balancing module and a carrier frequency estimation module for PSK signals under network signal distribution noise; the building HP2P network load balancing module and carrier frequency estimation module are all wirelessly connected to the central monitoring system;

The building HP2P network load balancing method of the building HP2P network load balancing module includes:

1) The method of load balancing among HP2P network groups: the load transfer between groups is realized through group splitting and the movement of groups in the network address space, and the splitting and merging of groups is induced by adding new nodes to groups with larger loads, so that the load The number of larger address space groups increases, and the number of address space groups with smaller loads decreases, where the load is defined as the average number of messages that nodes in the group need to process per unit time;

2) The method of load balancing in the HP2P network group. Through the effective scheduling of the load in the group by super nodes, the nodes with a lower load rate in the group can find the nodes with a higher load rate in the group. According to the characteristics of the HP2P network, the load is approximately defined is the number of metadata that nodes in the group need to maintain, the load rate is defined as the ratio of load to node capability, and the metadata is the index of resources;

In the carrier frequency estimation method of the PSK signal under the network signal distribution noise of the described carrier frequency estimation module, the PSK signal is a signal in the HP2P network; specifically includes:

Calculate the cyclic covariant function for the received PSK signal containing distributed noise;

Carry out Fourier transform to described cyclic covariation function, seek its cyclic covariation spectrum;

Extracting a cross-section with a cyclic frequency ε=0 Hz through the cyclic covariation spectrum;

Search for the peak values of the positive and negative semi-axes of the section, find the positive and negative frequency values corresponding to the peak values, take the absolute value and calculate the mean value as the estimated value of the carrier frequency.

The method for load balancing between the HP2P network groups includes:

Step (1) The supernode S of group A randomly sends a group load request message to the surrounding k·log ₂ N groups, obtains the load information of the k·log ₂ N groups, and calculates the k·log ₂ N The average load of each group is used to estimate the average load Load _avg of the entire HP2P network, where k is an integer in the interval [1, N/log ₂ N], and N is the number of groups in the network;

Step (2) If the current load of group A is Load>γ·Load _avg , and the number of nodes in the two small groups that the group splits into is both greater than the lower limit of the number of nodes in the HP2P network group, split the group into two groups, where γ is A real number greater than 1, the execution of the method for load balancing between HP2P network groups ends this time; otherwise, go to step (A3);

Step (3) Construct the Chord ring in the HP2P network. Group A sends a load request message to its predecessor group and successor group to obtain the current load conditions of the predecessor group and successor group. The predecessor group is the closest outlier A in the Chord ring of the HP2P network. The previous group of , and the successor group is the next group closest to outlier A in the Chord ring of the HP2P network;

Step (4) If the current load of group A is Load>Load _avg , then go to step (A5), if Load<Load _avg , then go to step (A8); otherwise, the method of load balancing between HP2P network groups ends;

Step (5) If the load of group A is Load≥Load _light /(1-2·β), reduce its own load by β, where β is a real number with a value in the interval (0,0.5), and go to step (A6 ); Otherwise, go to step (A8); wherein Load _light is the load of the group with the smaller load in the predecessor group and the successor group of the group;

Step (6) If the Load _light is the load of the predecessor group of group A, then group A notifies its predecessor group to move clockwise along the Chord ring, and the length of the moving address space is (Load-Load _light )×Length/(2×Load ), and transfer the corresponding metadata to the predecessor group, the execution of the method for load balancing between HP2P network groups ends this time, where Length is the length of the address space maintained by group A in the Chord ring; otherwise, go to step (A7) ;

Step (7) Load _light is the load of the successor group of group A, then the group moves counterclockwise along the Chord ring, the address space length of the move is (Load-Load _light )×Length/(2×Load), and the corresponding The metadata of the HP2P network group is transferred to the successor group, and then the execution of the method of load balancing between the HP2P network groups ends this time;

Step (8) If Load≤(1-2·β)·Load _heavy , go to step (A9); where Load _heavy is the load of the group with the heavier load in the predecessor group and the successor group of the group, and β is a load in The interval (0,0.5) is a real number, otherwise the execution of the HP2P network inter-group load balancing method ends;

Step (9) If Load _heavy is the load of the predecessor group of group A, then group A notifies its predecessor group to move counterclockwise along the Chord ring, and the length of the moving address space is (Load _heavy -Load)×Length _predecessor /(2× Load _heavy ), and obtain the corresponding metadata from the predecessor group, where Length _predecessor is the length of the address space maintained by the predecessor group in the Chord ring, and then the execution of the HP2P network inter-group load balancing method ends; otherwise, go to step (A10 );

Step (10) Load _heavy is the load of the successor group of group A, then group A moves clockwise along the Chord ring, and the length of the moving address space is (Load _heavy -Load)×Length _successor /(2×Load _heavy ), and The corresponding metadata is obtained from the successor group, where the Length _successor is the length of the address space maintained by the successor group in the Chord ring, and at this time, the execution of the load balancing method between HP2P network groups ends.

The load balancing method in the common node group includes:

Step (1) Ordinary nodes obtain the current average load rate of the group from super nodes

Step (2) If the load rate of the node It is considered that the load rate of the node is high. At this time, the node will notify the super node in the group of its own load rate and the number of metadata that needs to be transferred to other nodes in the group. Then the execution of the load balancing method in the ordinary node group ends this time, where capacity is the capacity of the node, and α is a real number between the interval (1,2); otherwise, go to step (3);

Step (3) If the load rate of the node It is considered that the load rate of the node is low; at this time, the node notifies the super nodes in the group of its own load rate and the maximum number of metadata that can be received from other nodes in the group Among them, capacity is the capacity of the node, and the execution of the load balancing method in the common node group is completed this time.

Further, the cyclic covariation function of the received signal includes:

The signal contains an MPSK signal subject to SαS distributed noise, which can be expressed as:

where E is the average power of the signal, M=2 ^k , m=1,2,...M, q(t) represents the rectangular pulse waveform, T represents the symbol period, f _c represents the carrier frequency, φ ₀ represents the initial phase, if w(t) obeys SαS distribution of non-Gaussian noise, then its self-covariation function is defined as:

Where (x(t-τ)) ^<p-1> = |x(t-τ)| ^p-2 x*(t-τ), γ _x(t-τ) is the dispersion coefficient of x(t), Then the cyclic covariation of x(t) is defined as:

Among them, ε is called the cycle frequency, and T is a symbol period.

The cyclic covariation spectrum of the received signal is performed as follows:

The cyclic covariation spectrum is the Fourier transform of the cyclic covariation function, expressed as:

Its cyclic covariation spectrum is derived as:

When M≥4, in place,

When M=2,

where Q(f) is the Fourier transform of q(t), and

The carrier frequency estimation is realized by extracting the section of cyclic frequency ε=0Hz in the cyclic covariation spectrum, as follows:

The envelope of the cyclic covariation spectrum on the n=0, ie, ε=0Hz section is:

When f=±f _c , the envelope takes the maximum value.

The working principle of the present invention is: the system includes a central monitoring system, a wireless access control subsystem, an air-conditioning subsystem, an elevator automatic control subsystem, a lighting subsystem, a distribution electronic system, a water supply and drainage subsystem, a security subsystem, and a garage management subsystem. , TV monitoring subsystem, environmental monitoring subsystem, smart home subsystem. These subsystems are connected with the central monitoring system via Ethernet. The data collected by the subsystems is transmitted to the central data through the Ethernet for processing and storage, and the information of each subsystem is displayed through the display device, and the alarm information can be sent out when a certain subsystem fails through the alarm device. The system is advanced in technology, economical and practical, safe and reliable.

Simulation experiments and data results of the present invention show that the HP2P network load balancing method well solves the problem of unbalanced loads between groups and within groups of the HP2P network. If this invention is applied to the HP2P-based network, the performance of the HP2P-based network software will be greatly improved.

The present invention can estimate the carrier frequency of the PSK signal under the distributed noise; The present invention has better estimation performance under the low SNR environment; In the same simulation experiment environment and the same symbol rate, carrier frequency, sampling frequency, Under the setting conditions of signal parameters such as number of sampling points and signal-to-noise ratio, the present invention has better estimation performance than existing methods. Provide guarantee for intelligent building network management.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention in any form. All simple modifications, equivalent changes and modifications made to the above embodiments according to the technical essence of the present invention belong to this invention. within the scope of the technical solution of the invention.

Claims (7)

1. An intelligent building management system, characterized in that, the intelligent building management system comprises a central monitoring system, a wireless access control subsystem, an air-conditioning subsystem, an elevator automatic control subsystem, a lighting subsystem, Distribution electronic system, water supply and drainage subsystem, security subsystem, garage management subsystem, TV monitoring subsystem, environmental monitoring subsystem, smart home subsystem; Wireless access control subsystem, air conditioning subsystem, elevator automatic control subsystem, lighting subsystem, variable distribution electronic system, water supply and drainage subsystem, security subsystem, garage management subsystem, TV monitoring subsystem, environmental monitoring subsystem, smart home subsystem The system is wirelessly connected to the central monitoring system through Ethernet; the power supply system supplies the wireless access control subsystem, the air conditioning subsystem, the elevator automatic control subsystem, the lighting subsystem, the distribution electronic system, the water supply and drainage subsystem, the security subsystem, and the garage management. Subsystem, TV monitoring subsystem, environmental monitoring subsystem and central monitoring system power supply; The security subsystem is integrated with a building HP2P network load balancing module and a carrier frequency estimation module for PSK signals under network signal distribution noise; the building HP2P network load balancing module and carrier frequency estimation module are all wirelessly connected to the central monitoring system; The building HP2P network load balancing method of the building HP2P network load balancing module includes: 1) The method of load balancing among HP2P network groups: the load transfer between groups is realized through group splitting and the movement of groups in the network address space, and the splitting and merging of groups is induced by adding new nodes to groups with larger loads, so that the load The number of larger address space groups increases, and the number of address space groups with smaller loads decreases, where the load is defined as the average number of messages that nodes in the group need to process per unit time; 2) The method of load balancing in the HP2P network group. Through the effective scheduling of the load in the group by super nodes, the nodes with a lower load rate in the group can find the nodes with a higher load rate in the group. According to the characteristics of the HP2P network, the load is approximately defined is the number of metadata that nodes in the group need to maintain, the load rate is defined as the ratio of load to node capability, and the metadata is the index of resources; In the carrier frequency estimation method of the PSK signal under the network signal distribution noise of the described carrier frequency estimation module, the PSK signal is a signal in the HP2P network; specifically includes: Calculate the cyclic covariant function for the received PSK signal containing distributed noise; Carry out Fourier transform to described cyclic covariation function, seek its cyclic covariation spectrum; Extracting a cross-section with a cyclic frequency ε=0 Hz through the cyclic covariation spectrum; Search for the peak values of the positive and negative semi-axes of the section, find the positive and negative frequency values corresponding to the peak values, take the absolute value and calculate the mean value as the estimated value of the carrier frequency. 2. The intelligent building management system as claimed in claim 1, wherein the method for load balancing between the HP2P network groups comprises: Step (1) The supernode S of group A randomly sends a group load request message to the surrounding k·log ₂ N groups, obtains the load information of the k·log ₂ N groups, and calculates the k·log ₂ N The average load of each group is used to estimate the average load Load _avg of the entire HP2P network, where k is an integer in the interval [1, N/log ₂ N], and N is the number of groups in the network; Step (2) If the current load of group A is Load>γ·Load _avg , and the number of nodes in the two small groups that the group splits into is both greater than the lower limit of the number of nodes in the HP2P network group, split the group into two groups, where γ is A real number greater than 1, the execution of the method for load balancing between HP2P network groups ends this time; otherwise, go to step (A3); Step (3) Construct the Chord ring in the HP2P network. Group A sends a load request message to its predecessor group and successor group to obtain the current load conditions of the predecessor group and successor group. The predecessor group is the closest outlier A in the Chord ring of the HP2P network. The previous group of , and the successor group is the next group closest to outlier A in the Chord ring of the HP2P network; Step (4) If the current load of group A is Load>Load _avg , then go to step (A5), if Load<Load _avg , then go to step (A8); otherwise, the method of load balancing between HP2P network groups ends; Step (5) If the load of group A is Load≥Load _light /(1-2·β), reduce its own load by β, where β is a real number with a value in the interval (0,0.5), and go to step (A6 ); Otherwise, go to step (A8); wherein Load _light is the load of the group with the smaller load in the predecessor group and the successor group of the group; Step (6) If the Load _light is the load of the predecessor group of group A, then group A notifies its predecessor group to move clockwise along the Chord ring, and the length of the moving address space is (Load-Load _light )×Length/(2×Load ), and transfer the corresponding metadata to the predecessor group, the execution of the method for load balancing between HP2P network groups ends this time, where Length is the length of the address space maintained by group A in the Chord ring; otherwise, go to step (A7) ; Step (7) Load _light is the load of the successor group of group A, then the group moves counterclockwise along the Chord ring, the address space length of the move is (Load-Load _light )×Length/(2×Load), and the corresponding The metadata of the HP2P network group is transferred to the successor group, and then the execution of the method of load balancing between the HP2P network groups ends this time; Step (8) If Load≤(1-2·β)·Load _heavy , go to step (A9); where Load _heavy is the load of the group with the heavier load in the predecessor group and the successor group of the group, and β is a load in The interval (0,0.5) is a real number, otherwise the execution of the HP2P network inter-group load balancing method ends; Step (9) If Load _heavy is the load of the predecessor group of group A, then group A notifies its predecessor group to move counterclockwise along the Chord ring, and the length of the moving address space is (Load _heavy -Load)×Length _predecessor /(2× Load _heavy ), and obtain the corresponding metadata from the predecessor group, where Length _predecessor is the length of the address space maintained by the predecessor group in the Chord ring, and then the execution of the HP2P network inter-group load balancing method ends; otherwise, go to step (A10 ); Step (10) Load _heavy is the load of the successor group of group A, then group A moves clockwise along the Chord ring, and the length of the moving address space is (Load _heavy -Load)×Length _successor /(2×Load _heavy ), and The corresponding metadata is obtained from the successor group, where the Length _successor is the length of the address space maintained by the successor group in the Chord ring, and at this time, the execution of the load balancing method between HP2P network groups ends. 3. The intelligent building management system according to claim 1, wherein the load balancing method in the common node group comprises: Step (1) Ordinary nodes obtain the current average load rate of the group from super nodes Step (2) If the load rate of the node It is considered that the load rate of the node is high. At this time, the node will notify the super node in the group of its own load rate and the number of metadata that needs to be transferred to other nodes in the group. Then the execution of the load balancing method in the ordinary node group ends this time, where capacity is the capacity of the node, and α is a real number between the interval (1,2); otherwise, go to step (3); Step (3) If the load rate of the node It is considered that the load rate of the node is low; at this time, the node notifies the super nodes in the group of its own load rate and the maximum number of metadata that can be received from other nodes in the group Among them, capacity is the capacity of the node, and the execution of the load balancing method in the common node group is completed this time. 4. The intelligent building management system according to claim 1, wherein the cyclic covariant function of the received signal comprises: The signal contains an MPSK signal subject to SαS distributed noise, which can be expressed as: where E is the average power of the signal, M=2 ^k , m=1,2,...M, q(t) represents the rectangular pulse waveform, T represents the symbol period, f _c represents the carrier frequency, φ ₀ represents the initial phase, if w(t) obeys SαS distribution of non-Gaussian noise, then its self-covariation function is defined as: Where (x(t-τ)) ^<p-1> = |x(t-τ)| ^p-2 x*(t-τ), γ _x(t-τ) is the dispersion coefficient of x(t), Then the cyclic covariation of x(t) is defined as: Among them, ε is called the cycle frequency, and T is a symbol period. 5. The intelligent building management system as claimed in claim 1, wherein the cyclic covariation spectrum of the received signal is carried out as follows: The cyclic covariation spectrum is the Fourier transform of the cyclic covariation function, expressed as: Its cyclic covariation spectrum is derived as: When M≥4, in place, When M=2, where Q(f) is the Fourier transform of q(t), and 6. The intelligent building management system as claimed in claim 1, wherein said carrier frequency estimation is realized by extracting the section of cyclic frequency ε=0Hz in the cyclic covariation spectrum, as follows: The envelope of the cyclic covariation spectrum on the n=0, ie, ε=0Hz section is: When f=±f _c , the envelope takes the maximum value. 7. The intelligent building management system as claimed in claim 1, wherein the wireless access control subsystem comprises two parts, an access control management module and an access control card, wherein the access control management module comprises a reader, a terminal controller, and a transceiver antenna; The access control card includes a transceiver antenna and a transponder; The environmental monitoring subsystem includes an environmental monitoring host computer, a temperature and humidity sensor, an inhalable gas concentration detector and a harmful gas concentration detector connected to the host computer, all of which are connected to the central monitoring system.