CN114124730A - Communication method, device and system - Google Patents

Abstract

The invention provides a communication method, a device and a system, wherein the method comprises the following steps: the branch node determines that a first emergency occurs; the branch node determines carbon consumption prediction information corresponding to the first burst event; the branch node transmits carbon consumption prediction information corresponding to the first burst event. By adopting the method, the central node can be informed of the carbon consumption prediction information corresponding to the first burst event.

Description

Communication method, device and system

Technical Field

The present invention relates to the field of communications technologies, and in particular, to a communication method, apparatus, and system.

Background

Global warming is a consequence of earth climate change caused by human behavior. "carbon" is a natural resource composed of carbon elements such as petroleum, coal, wood, etc. The "carbon" is much more consumed and the very powerful "carbon dioxide" that causes the earth to become warm is also much more produced. With human activities, global warming is also changing (affecting) people's lifestyle, bringing about more and more problems.

The carbon dioxide emission is reduced by means of carbon sequestration, wherein carbon dioxide in the air is absorbed and stored mainly by natural carbon in soil, forests, oceans and the like, and specifically, carbon sequestration can be realized by human beings through afforestation; and secondly, carbon offset, namely reducing the carbon dioxide emission of one industry to offset the carbon dioxide emission of another industry by investing and developing renewable energy sources and low-carbon cleaning technology, wherein the calculation unit of the carbon dioxide offset can be carbon dioxide equivalent tonnage.

In particular, when an emergency occurs, how to know the carbon consumption demand of the user is a considerable problem.

Disclosure of Invention

The invention provides a communication method, a communication device and a communication system, which are used for solving the problem of how to know the carbon consumption requirement of a user when an emergency occurs.

In a first aspect, the present application provides a communication method, including: the branch node determines that a first emergency occurs; the branch node determines carbon consumption prediction information corresponding to the first emergency; and the branch node sends the carbon consumption prediction information corresponding to the first emergency.

By adopting the method, the branch node can report the carbon consumption prediction information corresponding to the first emergency, and further the central node can know the carbon consumption requirement of the branch node.

In one possible design, when the branch node determines the carbon consumption prediction information corresponding to the first emergency, the branch node determines the carbon consumption prediction information corresponding to the first emergency according to a carbon consumption prediction database corresponding to the first emergency, where the branch node stores the carbon consumption prediction databases corresponding to at least one emergency respectively, and the at least one emergency includes the first emergency.

By adopting the design, the branch node can determine the corresponding carbon consumption prediction information simply and conveniently according to the carbon consumption prediction database corresponding to the first emergency.

In one possible design, when the branch node determines the carbon consumption prediction information corresponding to the first emergency according to the carbon consumption prediction database corresponding to the first emergency, the branch node determines the carbon consumption prediction information corresponding to the first emergency according to the carbon consumption prediction database corresponding to the first emergency and the device type of the branch node at a first time, where the first time is the occurrence time of the first emergency determined by the branch node.

By adopting the design, the branch node can determine the corresponding carbon consumption prediction information more simply and conveniently according to the carbon consumption prediction database corresponding to the first emergency, the equipment type of the branch node and the first time.

In one possible design, the branch node sends information indicating the first time and/or a device type of the branch node.

In one possible design, the carbon consumption prediction database corresponding to each of the at least one emergency event is determined based on historical data associated with the emergency event.

In one possible design, further comprising: after the branch node determines the carbon consumption prediction information corresponding to the first emergency, the branch node switches from a non-burst operation state to a burst operation state corresponding to the first emergency.

In one possible design, further comprising: the first emergency event includes but is not limited to any one of the following events: fires, earthquakes, explosions, carbon energy leaks, terrorist attacks, interruptions in the supply of carbon energy, theft of carbon energy, major system failures.

In one possible design, further comprising: the branch node determining that the first incident has been resolved; the branch node sends notification information indicating that the first emergency has been resolved.

In a second aspect, the present application provides a communication apparatus, which is a branch node or an apparatus having a function of a branch node, the apparatus comprising: a processing unit and a transceiver unit; the processing unit is used for determining that a first emergency occurs; determining carbon consumption prediction information corresponding to the first emergency; the transceiver unit is configured to send the carbon consumption prediction information corresponding to the first emergency.

In a possible design, when determining the carbon consumption prediction information corresponding to the first emergency, the processing unit is configured to determine the carbon consumption prediction information corresponding to the first emergency according to a carbon consumption prediction database corresponding to the first emergency, where the branch node stores the carbon consumption prediction databases corresponding to at least one emergency respectively, where the at least one emergency includes the first emergency.

In a possible design, when determining the carbon consumption prediction information corresponding to the first emergency according to the carbon consumption prediction database corresponding to the first emergency, the processing unit is configured to determine the carbon consumption prediction information corresponding to the first emergency according to the carbon consumption prediction database corresponding to the first emergency, the device type of the branch node, and a first time, where the first time is an occurrence time of the first emergency determined by the branch node.

In one possible design, the branch node sends information indicating the first time and/or a device type of the branch node.

In one possible design, the carbon consumption prediction database corresponding to each of the at least one emergency event is determined based on historical data associated with the emergency event.

In one possible design, further comprising: after determining the carbon consumption prediction information corresponding to the first emergency, the processing unit is configured to switch from a non-emergency operation state to an emergency operation state corresponding to the first emergency.

In one possible design, further comprising: the first emergency event includes but is not limited to any one of the following events: fires, earthquakes, explosions, carbon energy leaks, terrorist attacks, interruptions in the supply of carbon energy, theft of carbon energy, major system failures.

In one possible design, further comprising: the processing unit is used for determining that the first emergency is relieved; the transceiver unit is configured to send notification information, where the notification information indicates that the first emergency is resolved.

In a third aspect, the present application further provides an apparatus. The device can execute the method design. The apparatus may be a chip or a circuit capable of executing the corresponding functions of the above method, or a device including the chip or the circuit.

In one possible implementation, the apparatus includes: a memory for storing computer executable program code; and a processor coupled with the memory. Wherein the program code stored in the memory comprises instructions which, when executed by the processor, cause the apparatus or a device in which the apparatus is installed to perform the method of any of the above possible designs.

Wherein the apparatus may further comprise a communication interface, which may be a transceiver, or, if the apparatus is a chip or a circuit, an input/output interface of the chip, such as an input/output pin or the like.

In one possible embodiment, the device comprises corresponding functional units for carrying out the steps of the above method. The functions may be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more units corresponding to the above functions.

In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon a computer program for performing the method of any one of the above possible designs when the computer program runs on an apparatus.

In a fifth aspect, the present application provides a computer program product comprising a computer program for performing the method of any one of the above possible designs when the computer program runs on an apparatus.

In a sixth aspect, the present application provides a communication system comprising at least one branch node and at least one central node, wherein the branch node is configured to perform the method of any one of the possible designs of the first aspect.

In addition, for technical effects brought by any one implementation manner of the second aspect to the sixth aspect, reference may be made to technical effects brought by different implementation manners of the first aspect to the second aspect, and details are not described here.

Drawings

Fig. 1 is a schematic structural diagram of a communication system according to an embodiment of the present invention;

fig. 2 is a second schematic structural diagram of a communication system according to an embodiment of the present invention;

fig. 3 is a flowchart illustrating an overview of a communication method according to an embodiment of the present invention;

fig. 4 is a schematic structural diagram of a communication device according to an embodiment of the present invention;

fig. 5 is a second schematic structural diagram of a communication device according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The application scenario described in the embodiment of the present invention is for more clearly illustrating the technical solution of the embodiment of the present invention, and does not form a limitation on the technical solution provided in the embodiment of the present invention, and it can be known by a person skilled in the art that with the occurrence of a new application scenario, the technical solution provided in the embodiment of the present invention is also applicable to similar technical problems. In the description of the present invention, the term "plurality" means two or more unless otherwise specified.

The technical concept related to the embodiments of the present application is explained below:

1. carbon neutral (carbon neutral):

the term of energy conservation and emission reduction refers to that enterprises, groups or individuals measure and calculate the total amount of greenhouse gas emission generated directly or indirectly within a certain time, and the emission of carbon dioxide generated by the enterprises, the groups or the individuals is counteracted through the forms of afforestation, energy conservation and emission reduction and the like, so that the zero emission of the carbon dioxide is realized.

Carbon peak of

The term of energy conservation and emission reduction refers to that carbon emission enters a steady decline stage after entering a plateau stage.

2. Energy source prediction:

the situation of energy consumption in a future period of time is predicted, and specific conditions can include power, total consumption and the like.

3. Cellular network (cellular network), also called mobile network (mobile network)

Is a mobile communication hardware architecture, which is divided into an analog cellular network and a digital cellular network. The signal coverage of each communication base station forming the network coverage is hexagonal, so that the whole network is named like a honeycomb. Common types of cellular networks are: global system for mobile communications (GSM) networks, Code Division Multiple Access (CDMA) networks, 3rd-Generation mobile communication technology (3G) networks, Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), Personal Digital Cellular (PDC), total access network communication system Technology (TACS), advanced mobile phone system (advanced mobile phone system, AMPS), fourth Generation mobile communication technology (4-Generation, 4G) networks, fifth Generation mobile communication technology (5-Generation, 5G) networks, and so forth.

The cellular network mainly comprises the following three parts: mobile station, base station subsystem, network subsystem. The mobile station is our network terminal equipment, such as a mobile phone or some cellular industrial control equipment. The base station subsystem comprises a mobile base station (a large iron tower), wireless transceiver equipment, a special network (generally an optical fiber), a myriad of digital equipment and the like which are daily seen. We can see the base station subsystem as a switch between a wireless network and a wired network.

4. Wireless local area network

The method is characterized in that computer equipment is interconnected by applying a wireless communication technology to form a network system which can communicate with each other and realize resource sharing. The wireless local area network is essentially characterized in that a communication cable is not used for connecting a computer with a network, but the computer is connected in a wireless mode, so that the network construction and the terminal movement are more flexible. Common types of wireless local area networks are: wireless communication technology (WiFi), and the like.

It is a convenient data transmission system, it utilizes Radio Frequency (RF) technology, uses electromagnetic wave, replaces the old local area network formed by twisted copper (coaxial) wires which are obstructive to hands and feet, and makes communication connection in the air, so that the wireless local area network can make users penetrate it by using simple access structure, and achieves the ideal field of 'information portability and convenience for walking down in the sky'.

Wireless Local Area Network (WLAN) began in 1997. In 6 months of the year, the first Institute of Electrical and Electronics Engineers (IEEE) 802.11 wlan standard promulgated to implement provides a unified standard for wlan technology, but the transmission rate at that time is only 1-2 Mbit/s. Subsequently, IEEE has begun to enact new WLAN standards, named IEEE802.11a and IEEE802.11 b, respectively. The IEEE802 llb standard was first promulgated in the year 1999, 9, at a rate of 11 Mbit/s. The improved IEEE802.11a standard is promulgated only in 2001, and the transmission rate of the standard can reach 54 Mbit/s, which is almost 5 times of the IEEE802.llb standard. However, the WLAN application does not really start because the entire WLAN application environment is not mature.

The real evolution of WLAN began with the first introduction of an express processor with a WLAN wireless network card chip module in 3 months Intel (Intel) 2003. Although the wireless network environment at the time was still largely immature, the most developed united states was no exception. However, due to the binding sale of Intel and the obvious advantages of high performance, low power consumption and the like of the fast chip, many wireless network service providers see business opportunities, and meanwhile, the access rate of 11 Mbit/s can be daily applied to a common small local area network, so that the wireless network service providers of various countries start to provide access hotspots in public places (such as airports, hotels, coffee shops and the like), and actually, some wireless Access Points (APs) are arranged to facilitate wireless internet access of mobile commerce.

After the development of more than two years, wireless network products and applications based on the IEEE802.llb standard are quite mature, but the access rate of 11 Mbit/s is far from meeting the application requirements of the actual network.

In 6 months of 2003, after more than two years of development and many improvements, a new standard IEEE802.11 g, which is compatible with the original IEEE802 llb standard and can also provide 54 Mbit/s access rate, was promulgated in the effort of IEEE.

The most used at present are the 802.11n (fourth generation) and 802.11ac (fifth generation) standards, which can work in the 2.4 GHz band and the 5 GHz band, and the transmission rate can reach 600 Mbit/s (theoretical value). However, only the routers supporting 802.11ac are true 5G, and now many routers supporting 2.4G and 5G dual-band only support the fourth generation wireless standard, that is, dual-band of 802.11n, while the routers supporting ac 5G are four-five hundred yuan or even thousands yuan the least expensive.

5. Internet protocol version four (4, IPv 4)

The fourth revision in the development of the internet protocol is also the first widely deployed version of this protocol. IPv4 is the core of the internet, and is also the most widely used version of the internet protocol. IPv4 is a connectionless protocol that operates at the link layer (e.g., ethernet) using packet switching. This protocol will deliver the packets with the best effort, i.e., it does not guarantee that any packets will arrive at the destination, nor that all packets will arrive in the correct order without duplication.

6. Internet protocol version six (6, IPv 6)

Is the next generation IP protocol designed by the Internet Engineering Task Force (IETF) to replace IPv4, and the number of addresses can be named as one address for each sand all over the world.

7. Artificial Intelligence (AI)

Is a branch of computer science that attempts to understand the essence of intelligence and produces a new intelligent machine that can react in a manner similar to human intelligence. The method is a new technical science for researching and developing theories, methods, technologies and application systems for simulating, extending and expanding human intelligence.

Research in this area includes robotics, language recognition, image recognition, natural language processing, and expert systems, among others. Since the birth of artificial intelligence, theories and technologies become mature day by day, and application fields are expanded continuously, so that science and technology products brought by the artificial intelligence in the future can be assumed to be 'containers' of human intelligence. The artificial intelligence can simulate the information process of human consciousness and thinking. Artificial intelligence is not human intelligence, but can think like a human, and can also exceed human intelligence.

Artificial intelligence is a gate-challenging science that people who work must understand computer knowledge, psychology and philosophy. Artificial intelligence is a very broad science composed of different fields such as machine learning, computer vision, etc. In general, one of the main goals of artificial intelligence research is to enable machines to perform complex tasks that typically require human intelligence to complete. But the understanding of this "complex work" is different for different times and for different people.

An AI processor, also known as an AI accelerator or computing card, i.e., a deep learning processor, refers to a module dedicated to handling a large number of computing tasks in artificial intelligence applications (other non-computing tasks are still handled by the CPU). Many data processing by AI involve matrix multiplication and addition. A large number of GPUs working in parallel provides an inexpensive approach, but the disadvantage is higher power. Field Programmable Gate Arrays (FPGAs) with built-in Digital Signal Processing (DSP) modules and local memory are more energy efficient, but they are generally more expensive. The AI processor, in popular terms, refers to learning, judging and deciding by simulating the mechanism of the human brain through a deep neural network.

8. Machine learning

Machine learning is a multi-field cross discipline, and relates to a plurality of disciplines such as probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and the like. The special research on how a computer simulates or realizes the learning behavior of human beings so as to acquire new knowledge or skills and reorganize the existing knowledge structure to continuously improve the performance of the computer.

It is the core of artificial intelligence and the fundamental way to make computer have intelligence.

Machine learning has several definitions:

(1) machine learning is the science of artificial intelligence, and the main research object in the field is artificial intelligence, particularly how to improve the performance of a specific algorithm in empirical learning.

(2) Machine learning is a study of computer algorithms that can be automatically improved through experience.

(3) Machine learning is the use of data or past experience to optimize the performance criteria of a computer program.

9. Deep learning

Deep learning refers to a multi-layered artificial neural network and a method of training it.

Deep Learning (DL) is a new research direction in the field of Machine Learning (ML), and is introduced into machine learning to make it closer to the original target, artificial intelligence.

Deep learning is the intrinsic law and expression level of the learning sample data, and the information obtained in the learning process is very helpful for the interpretation of data such as characters, images and sounds. The final aim of the method is to enable the machine to have the analysis and learning capability like a human, and to recognize data such as characters, images and sounds. Deep learning is a complex machine learning algorithm, and achieves the effect in speech and image recognition far exceeding the prior related art.

Deep learning has achieved many achievements in search technology, data mining, machine learning, machine translation, natural language processing, multimedia learning, speech, recommendation and personalization technologies, and other related fields. The deep learning enables the machine to imitate human activities such as audio-visual and thinking, solves a plurality of complex pattern recognition problems, and makes great progress on the artificial intelligence related technology.

Deep learning is a general term of a type of pattern analysis method, and mainly relates to three types of methods in terms of specific research contents:

(1) a neural network system based on convolution operation, namely, a Convolutional Neural Network (CNN).

(2) Self-coding neural networks based on multi-layer neurons include two classes (auto encoder) and sparse coding, which have received much attention in recent years.

(3) Pre-training is performed in a multi-layer self-coding neural network mode, and then Deep Belief Networks (DBNs) of neural network weights are further optimized by combining the discrimination information.

Through multi-layer processing, after the initial low-layer feature representation is gradually converted into the high-layer feature representation, the complex learning tasks such as classification can be completed by using a simple model. Thus, deep learning can be understood as "feature learning" or "representation learning".

In the past, when machines were learned for realistic tasks, the features describing the samples typically had to be designed by human experts, which became "feature engineering". As is well known, the quality of the features has a crucial influence on the generalization performance, and it is not easy for a human expert to design good features; feature learning (token learning) produces good features through the machine learning technique itself, which advances machine learning one step further toward "fully automatic data analysis".

In recent years, researchers have gradually combined these methods, such as unsupervised pre-training of a convolutional neural network originally based on supervised learning in combination with a self-coding neural network, and further fine-tuning a convolutional deep belief network formed by network parameters by using identification information. Compared with the traditional learning method, the deep learning method presets more model parameters, so that the model training difficulty is higher, and the more the model parameters are, the larger the data volume needing to participate in training is.

Due to limited computer computing power and limitations of related art, the amount of data available for analysis is too small, and deep learning does not exhibit excellent recognition performance in pattern analysis. Since the CD-K algorithm proposed by Hinton et al to quickly calculate the weights and deviations of the Restricted Boltzmann Machine (RBM) network in 2006, RBM became a powerful tool to increase the depth of neural networks, resulting in the emergence of deep networks such as the extensive DBN (developed by Hinton et al and used in speech recognition by microsoft et al). Meanwhile, sparse coding and the like are also applied to deep learning because features can be automatically extracted from data. Convolutional neural network methods based on local data regions have also been studied in large quantities in the recent years.

10. Central Processing Unit (CPU)

The core of the computer system is the final execution unit for information processing and program operation.

Von neumann architectures are the basis of modern computers. Under the system structure, programs and data are stored in a unified mode, instructions and data need to be accessed from the same storage space and transmitted through the same bus, and the instructions and the data cannot be executed in an overlapped mode. According to the von neumann system, the operation of the CPU is divided into the following 5 stages: instruction fetching stage, instruction decoding stage, instruction executing stage, access and access number and result write-back.

The central processing unit is one of the main devices of the electronic computer, and is a core accessory in the computer. Its functions are mainly to interpret computer instructions and to process data in computer software. The CPU is the core component of the computer responsible for reading, decoding and executing instructions. The central processor mainly comprises two parts, namely a controller and an arithmetic unit, and also comprises a cache memory and a bus for realizing data and control of the connection between the cache memory and the arithmetic unit. The three major core components of the computer are the CPU, internal memory, and input/output devices. The central processing unit mainly has the functions of processing instructions, executing operations, controlling time and processing data. In a computer architecture, a CPU is a core hardware unit that performs control and allocation of all hardware resources (such as memory and input/output units) of a computer and performs general operations. The CPU is the computational and control core of the computer. The operation of all software layers in the computer system will eventually be mapped to the operation of the CPU by the instruction set.

11. Graphics Processor (GPU)

The system is also called a display core, a visual processor and a display chip, and is a microprocessor which is specially used for image and graph related operation work on personal computers, workstations, game machines and some mobile devices (such as tablet computers, smart phones and the like).

The GPU reduces the dependence of the graphics card on the CPU, and performs part of the original CPU, and particularly, the core technologies adopted by the GPU in 3D graphics processing include hardware geometry conversion and lighting (T & L), cubic environment texture mapping and vertex mixing, texture compression and bump mapping, a dual-texture four-pixel 256-bit rendering engine, and the like, and the hardware T & L technology can be said to be a mark of the GPU.

12. Neural network processor (neural-network processing unit, NPU)

The microprocessor is specially used for performing relevant operation work of an artificial neural network on equipment.

13. System integration (system integration)

Generally, software, hardware and communication technologies are combined to solve information processing problems for users, each separated integrated part is originally an independent system, and all parts of the integrated whole can organically and coordinately work with each other to exert the whole benefits and achieve the purpose of whole optimization.

System integration is an emerging service mode, and is an industry with the most vigorous development in the international information service industry in recent years. The essence of system integration is the optimized comprehensive overall design, and a large-scale comprehensive computer network system comprises the integration of computer software, hardware, operating system technology, database technology, network communication technology and the like, and the integration of product selection and matching of different manufacturers, the system integration aims to achieve the aim of optimal overall performance, namely all components and components are combined together to work, the whole system is a low-cost, high-efficiency, uniform-performance, extensible and maintainable system, and the advantages and disadvantages of system integrators are crucial in order to achieve the aim.

Each system integration manufacturer has self understanding of the concept of system integration, although the emphasis points are different, the system integration manufacturers are the same in nature, and reasonably select various optimally configured software and hardware products and resources according to the requirements of users for numerous technologies and products to form a complete integration scheme capable of solving the specific application requirements of customers, so that the overall performance of the system is optimal, the system is advanced in technology, feasible in implementation, flexible in use, extensible in development and beneficial in investment. System integration has become a synonym for providing an overall solution, providing a full suite of devices, and providing full-range services.

The system integration is a solution scheme which is provided for customers on the product level, has the advantages of technical standard matching, complete technical interface, reasonable technical equipment and economic engineering cost on the basis of longitudinal continuous deepening and transverse continuous integration, and the formed system is advanced, open and resource-sharing.

Broadly, system integration includes various tasks such as personnel integration, organization integration, device integration, system software integration, application software integration, and management method integration. In a narrow sense, system integration is the integration of a system platform. System integration and application function integration, network integration, software interface integration and other integration technologies. The key to the system integration implementation is to solve the interconnection and interoperability problem between systems, which is a multi-vendor, multi-protocol and application-oriented architecture. All integration-oriented problems related to the construction coordination, organization management and personnel allocation of subsystems and building environments, such as interfaces, protocols, system platforms, application software and the like among various devices and subsystems need to be solved.

The embodiment of the invention provides a communication system, which comprises at least one central node and at least one branch node. The central node and the branch nodes are connected through a wired network and/or a wireless network. The system can also comprise a data center, and the data center is connected with the central node through a wired network and/or a wireless network.

Illustratively, the connection mode between the central node and the branch nodes may be a networking mode of a custom specification, or may be a standardized network, for example, IPv4, IPv6, a cellular network (5G, 4G, 3G, 2G, etc.), a wireless local area network (WiFi, etc.).

For example, the system shown in FIG. 1 includes a data center, a hub node, and a branch node. Wherein, 3 branch nodes are arranged under the central node 2, it can be understood that a plurality of branch nodes are also arranged under other central nodes, which are not shown in fig. 1. It should be noted that fig. 1 is only an example and is not intended to limit the present application, and the present application does not limit the number of the central nodes and the branch nodes, generally, one or more data centers may be set for each preset area, and the specific area range is not limited by the present application.

In one possible application scenario, the data center may include a large computer device, for example, a plurality of servers, the central node may be disposed in the household electric meter, for example, the central node may be built in the household electric meter in the form of one chip, or may be a stand-alone device capable of communicating with the household electric meter, and the branch node may be disposed in each household electric device, for example, a computer, a television, a washing machine, or the like, for example, the branch node may be built in the household electric device in the form of one chip.

In one possible application scenario, a data center may include a large computer device, e.g., including multiple servers, a central node may be deployed within a facility for recording carbon consumption of an enterprise, and branch nodes may be deployed at various production tools of the enterprise.

In addition, the branch node may also be provided with multiple levels of sub-branch nodes, as shown in fig. 2, where the branch node may be used to implement the function of the central node.

After the system is powered on, networking among all devices in the system is completed, and the data center, the central node and the branch nodes enter an operating state.

In order to solve the problem of how to know the carbon consumption requirement of the user when an emergency occurs, the embodiment of the present application provides a communication method, as shown in fig. 3. It is to be understood that the embodiments shown below do not particularly limit the specific structure of the execution subject of the method provided by the embodiments of the present application, as long as the communication can be performed by the method provided by the embodiments of the present application by running the program recorded with the code of the method provided by the embodiments of the present application, for example, the execution subject may be a functional module in a branch node or a branch node that can call a program and execute the program, or the execution subject may be a functional module in a central node or a central node that can call a program and execute the program. In the following, only the branch node or the central node is taken as an example for explanation.

As shown in fig. 3, the method includes:

step 300: the branch node determines that the first incident occurs.

Illustratively, the branch node may be added with an emergency monitoring module, which is used for detecting the emergency experienced by the branch node; or, the branch node may also receive the emergency notification information from other devices, and the branch node determines that the first emergency occurs according to the received emergency notification information.

Wherein, the first emergency event includes but is not limited to any one of the following events: fire, earthquake, explosion, carbon energy leakage (such as electric leakage and air leakage), terrorist attack, interruption of carbon energy supply (such as large-scale power failure), theft of carbon energy and major system failure.

It will be appreciated that the above events are merely examples and that other events may be included.

Step 310: the branch node determines carbon consumption prediction information corresponding to the first burst event.

In a possible implementation manner, the branch node determines, according to a carbon consumption prediction database corresponding to the first emergency, carbon consumption prediction information corresponding to the first emergency, where the carbon consumption prediction information corresponding to the first emergency may specifically include, but is not limited to, part or all of the following: the carbon consumption power of a certain time in the future of the first emergency, and the carbon consumption of the first emergency in a period of time in the future, wherein the branch node stores a carbon consumption prediction database corresponding to at least one emergency respectively, and the at least one emergency comprises the first emergency.

Wherein the carbon consumption prediction database corresponding to each of the at least one emergency is determined from historical data associated with the emergency. The carbon consumption prediction database corresponding to each emergency may be determined by a method such as deep learning (e.g., CNN, Deep Neural Networks (DNN)), and the specific determination method of the carbon consumption prediction database corresponding to each emergency is not limited in the present application. For example, the first emergency event is a fire, carbon consumption power or carbon consumption amount in a preset time period corresponding to a plurality of branch nodes collected when a fire occurs in the past time period (for example, 3 years) is used as historical data associated with the fire, and then a carbon consumption prediction database corresponding to the fire is determined by using the CNN model.

Illustratively, the branch node determines the carbon consumption prediction information corresponding to the first emergency according to the carbon consumption prediction database corresponding to the first emergency, the device type of the branch node, and a first time, where the first time is an occurrence time of the first emergency determined by the branch node.

It will be appreciated that the carbon consumption prediction database will typically be different for different incidents. For example, the first emergency event is a fire, the second emergency event is an earthquake, and the carbon consumption prediction database corresponding to the fire is different from the carbon consumption prediction database corresponding to the earthquake. And the emergency prediction database is different from the conventional prediction database, and each database is respectively maintained and executes different entering mode judgment.

The carbon consumption prediction information for branch nodes of different device types is typically different for the same incident. For example, the first branch node is a computer, the second branch node is a refrigerator, and the carbon consumption prediction information of the computer is generally different from the carbon consumption prediction information of the refrigerator.

For the same emergency, the carbon consumption prediction information may be different for the same branch node at different time periods. For example, the branch node is a computer, and the carbon consumption prediction information for computers at 5:00 to 6:00 in the morning is generally different from the carbon consumption prediction information for computers at 10:00 to 11:00 in the morning. Wherein, the computer may be in the power-off state in the morning from 5:00 to 6:00, and the computer may be in the power-on state in the morning from 10:00 to 11: 00.

The branch node also transmits information indicating the first time and/or a device type of the branch node.

Further, after the branch node determines the carbon consumption prediction information corresponding to the first emergency, the branch node switches from the non-burst operation state to the burst operation state corresponding to the first emergency.

Illustratively, the branch node is in a non-burst operation state when it is not determined that the first emergency event occurs and no other emergency event occurs, or can be described as a normal operation state or a normal operation state again. At this time, the branch node may record its own history data in a conventional database. And when the branch node determines that the first incident occurs, the branch node may store the collected historical data after the first incident in a database corresponding to the first incident, e.g., a carbon consumption prediction database corresponding to the first incident.

The carbon consumption prediction database corresponding to the first emergency is a set of statistical prediction system independent of the conventional database, can be read and written without any requirement in a non-emergency operation state, and can be stored in the system as a standby file.

Step 320: the branch node transmits carbon consumption prediction information corresponding to the first burst event.

The branch node may send the carbon consumption prediction information corresponding to the first burst event to the central node or other branch nodes.

In addition, if the branch node determines that the first emergency has been resolved, the branch node sends notification information indicating that the first emergency has been resolved. For example, the branch node may send notification information to the central node.

For example, the branch node may determine that the first emergency is resolved by the newly added emergency monitoring module; or, the branch node may also receive emergency release information from other devices, and the branch node determines that the first emergency has been released according to the received emergency release information. Further, the branch node is switched from the burst operation state corresponding to the first emergency to the non-burst operation state.

By adopting the mode, the central node can take the carbon consumption prediction information reported by each branch node as the reference data of the intelligent scheduling time-sharing segment.

Fig. 4 shows a possible exemplary block diagram of an apparatus involved in the embodiments of the present application, the apparatus 400 comprising: a transceiving unit 410 and a processing unit 420, the transceiving unit 410 may include a receiving unit and a transmitting unit. The processing unit 420 is used for controlling and managing the operation of the apparatus 400. The transceiving unit 410 is used to support communication of the apparatus 400 with other network entities. Optionally, the apparatus 400 may further comprise a storage unit for storing program codes and data of the apparatus 400.

Alternatively, each unit in the apparatus 400 may be implemented by software.

Alternatively, the processing unit 420 may be a processor or a controller, such as a general purpose Central Processing Unit (CPU), a general purpose processor, a Digital Signal Processing (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, units, and circuits described in connection with the disclosure of the embodiments of the application. The processor may also be a combination of computing functions, e.g., comprising one or more microprocessors, DSPs, and microprocessors, among others. The transceiver unit 410 may be a communication interface, a transceiver circuit, or the like, wherein the communication interface is generally referred to, and in a specific implementation, the communication interface may include a plurality of interfaces, and the storage unit may be a memory.

When the apparatus 400 is a branch node or a chip in a branch node, the processing unit 420 in the apparatus 400 may support the apparatus 400 to perform the actions of the branch node in the above methods examples, for example, the processing unit 420 may support the apparatus 400 to perform step 300 and step 310 in fig. 3.

The transceiving unit 410 may support communication between the apparatus 400 and a central node or other branch nodes, e.g., the transceiving unit 410 may support the apparatus 400 to perform step 320 in fig. 3.

In one implementation, the processing unit 420 is configured to determine that a first emergency event occurs; determining carbon consumption prediction information corresponding to the first emergency; the transceiver 410 is configured to send the carbon consumption prediction information corresponding to the first emergency.

It should be understood that the apparatus 400 according to the embodiment of the present application may correspond to a branch node in the foregoing method embodiment, and the operations and/or functions of the units in the apparatus 400 are respectively for implementing the corresponding steps of the method of the branch node in the foregoing method embodiment, so that the beneficial effects in the foregoing method embodiment may also be implemented, and for brevity, no detailed description is provided here.

Fig. 5 shows a schematic block diagram of a communication apparatus 500 according to an embodiment of the present application. As shown in fig. 5, the apparatus 500 includes: a processor 501.

When the apparatus 500 is a branch node or a chip in a branch node, in a possible implementation, when the processor 501 is configured to invoke an interface to perform the following actions:

determining that a first emergency event occurs; determining carbon consumption prediction information corresponding to the first emergency; and sending the carbon consumption prediction information corresponding to the first emergency.

It should be understood that the apparatus 500 may also be used to perform other steps and/or operations on the branch node side in the foregoing embodiments, and therefore, for brevity, the detailed description is omitted here.

It should be understood that the processor 501 may invoke an interface to perform the transceiving actions, wherein the invoked interface may be a logical interface or a physical interface, which is not limited thereto. Alternatively, the physical interface may be implemented by a transceiver. Optionally, the apparatus 500 further comprises a transceiver 503.

Optionally, the apparatus 500 further includes a memory 502, and the memory 502 may store the program codes in the above method embodiments for the processor 501 to call.

Specifically, if the apparatus 500 includes a processor 501, a memory 502 and a transceiver 503, the processor 501, the memory 502 and the transceiver 503 communicate with each other via an internal connection path to transmit control and/or data signals. In one possible design, the processor 501, the memory 502, and the transceiver 503 may be implemented by chips, and the processor 501, the memory 502, and the transceiver 503 may be implemented in the same chip, or may be implemented in different chips, or any two functions may be implemented in one chip. The memory 502 may store program code that the processor 501 calls upon stored by the memory 502 to implement the corresponding functionality of the apparatus 500.

The method disclosed in the embodiments of the present application may be applied to a processor, or may be implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method embodiments may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The processor may be a general-purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, a system on chip (SoC), a Central Processing Unit (CPU), a Network Processor (NP), a Digital Signal Processor (DSP), a Microcontroller (MCU), a programmable logic controller (PLD), or other integrated chip. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.

It will be appreciated that the memory in the embodiments of the subject application can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable EPROM (EEPROM), or a flash memory. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), double data rate SDRAM, enhanced SDRAM, SLDRAM, Synchronous Link DRAM (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.

It should be understood that, in the embodiment of the present application, the numbers "first" and "second" … are only used for distinguishing different objects, such as for distinguishing different parameter information or messages, and do not limit the scope of the embodiment of the present application, and the embodiment of the present application is not limited thereto.

It should also be understood that, in the various embodiments of the present application, the size of the serial number of each process described above does not mean the execution sequence, and the execution sequence of each process should be determined by the function and the inherent logic of each process. The various numbers or serial numbers involved in the above processes are merely used for convenience of description and should not be construed as limiting the implementation processes of the embodiments of the present application in any way.

It should also be understood that the term "and/or" herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

Items appearing in this application as similar to "include one or more of the following: the meaning of the expressions A, B, and C "generally means that the item may be any of the following, unless otherwise specified: a; b; c; a and B; a and C; b and C; a, B and C; a and A; a, A and A; a, A and B; a, A and C, A, B and B; a, C and C; b and B, B, B and C, C and C; c, C and C, and other combinations of A, B and C. The above description is made by taking 3 elements of a, B and C as examples of optional items of the item, and when the expression "item" includes at least one of the following: a, B, … …, and X ", i.e., more elements in the expression, then the items to which the item may apply may also be obtained according to the aforementioned rules.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a read-only memory ROM, a random access memory RAM, a magnetic disk, or an optical disk.

Claims (11)

1. A method of communication, comprising:

the branch node determines that a first emergency occurs;

the branch node determines carbon consumption prediction information corresponding to the first emergency;

and the branch node sends the carbon consumption prediction information corresponding to the first emergency.

2. The method of claim 1, wherein the branch node determining carbon consumption prediction information corresponding to the first incident comprises:

and the branch node determines carbon consumption prediction information corresponding to the first emergency according to a carbon consumption prediction database corresponding to the first emergency, wherein the branch node stores the carbon consumption prediction database corresponding to at least one emergency respectively, and the at least one emergency comprises the first emergency.

3. The method of claim 2, wherein the determining, by the branch node, the carbon consumption prediction information corresponding to the first incident based on the carbon consumption prediction database corresponding to the first incident comprises:

and the branch node determines carbon consumption prediction information corresponding to the first emergency according to a carbon consumption prediction database corresponding to the first emergency, the equipment type of the branch node and first time, wherein the first time is the occurrence time of the first emergency determined by the branch node.

4. The method of claim 3, further comprising:

the branch node sends information indicating the first time and/or a device type of the branch node.

5. The method of any of claims 2-4, wherein the database of carbon consumption predictions for each of the at least one incident is determined based on historical data associated with the incident.

6. The method of claim 1, further comprising:

after the branch node determines the carbon consumption prediction information corresponding to the first emergency, the branch node switches from a non-burst operation state to a burst operation state corresponding to the first emergency.

7. The method of claim 1, further comprising:

the first emergency event includes but is not limited to any one of the following events: fires, earthquakes, explosions, carbon energy leaks, terrorist attacks, interruptions in the supply of carbon energy, theft of carbon energy, major system failures.

8. The method of claim 1, further comprising:

the branch node determining that the first incident has been resolved;

the branch node sends notification information indicating that the first emergency has been resolved.

9. A communications apparatus, comprising: at least one processor for executing a computer program or instructions in a memory, which when executed, implements the method of any of claims 1-8.

10. A communication system, comprising: the system comprises at least one branch node, at least one central node and a data center; the central node and the branch nodes are connected through a wired network and/or a wireless network; wherein the branch node is configured to perform the method of any of claims 1-8.

11. A computer-readable storage medium having stored thereon computer instructions which, when executed on a computer, cause the computer to perform the method of any one of claims 1 to 8.

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