CN109936619B - Spatial information network architecture, method and readable storage medium based on fog calculation - Google Patents
Spatial information network architecture, method and readable storage medium based on fog calculation Download PDFInfo
- Publication number
- CN109936619B CN109936619B CN201910046373.5A CN201910046373A CN109936619B CN 109936619 B CN109936619 B CN 109936619B CN 201910046373 A CN201910046373 A CN 201910046373A CN 109936619 B CN109936619 B CN 109936619B
- Authority
- CN
- China
- Prior art keywords
- calculation
- information
- fog
- application service
- layer
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Mobile Radio Communication Systems (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
Abstract
The invention discloses a space information network architecture, a method and a readable storage medium based on fog computing, wherein the architecture comprises the following components: the sensing layer is used for collecting basic information of one or more applications in remote sensing, weather and positioning and sending the collected information to the cooperative processing layer; the cooperative processing layer is used for cooperatively processing the information acquired by the sensing layer; and the application service layer receives the information processed by the sensing layer and the cooperative processing layer and is used for providing comprehensive application service for space-based, sea-based and land-based users. The invention can provide distributed storage and distributed computation, can save network bandwidth, optimizes the CDN, saves the network bandwidth and improves the interaction rate. And the invention can also select the calculation mode according to the application service content, can process the application service more rapidly, utilize the computational resource to the maximum extent.
Description
Technical Field
The invention belongs to the field of communication information processing, and particularly relates to a space information network architecture, a space information network method and a readable storage medium based on fog computing.
Background
The spatial information network can support high-dynamic and broadband real-time transmission of earth observation downwards and ultra-long-distance and large-delay reliable transmission of deep space exploration upwards while serving major applications such as ocean navigation, emergency rescue, navigation positioning, air transportation, aerospace measurement and control and the like, thereby expanding human science, culture and production activities to space, ocean and even deep space and being a research hotspot in the global range.
Fig. 1 shows a prior art satellite information architecture of the present invention. Satellite electronics systems typically employ specialized aerospace chips, embedded operating systems and software, and specialized networking technologies. The satellite bus usually adopts MIL-STD-1553B, RS422, CAN, FC, etc., and generally uses a redundant topology structure to provide highly reliable communication connection for the satellite internal network, and most scenarios require real-time and certainty to be guaranteed. Satellite operating systems and software development are greatly different from traditional consumer electronics and industrial electronics, and due to the limitation of high volume, heavy power consumption, real-time performance and the like, embedded real-time operating systems such as VxWorks and the like are generally adopted, sometimes application programs need to run on a bare computer, and the fact that no operating system exists at all is meant.
In the current spatial information network, the on-board on-orbit computing processing capacity is very limited, and application data is mainly processed by high-speed satellite-ground links and relays which are transmitted back to ground nodes. However, with the development of space payload technology and satellite internet of things, the amount of data to be returned is larger and larger, which causes serious satellite-to-ground link bandwidth pressure on one hand, and on the other hand, cannot cope with tasks with higher requirements on timeliness, such as timely distribution of messages in hot spot areas, emergency early warning, and the like.
In order to solve the contradiction that the satellite communication transmission distance is long, the bandwidth is limited, but the application delay requirement is low, the satellite high-performance computing processing capacity is a necessary condition for realizing space-based networking and reducing ground dependence. From the development trend of the world-wide integrated information network, high timeliness and multi-dimensional fusion are inevitable trends in development, the data collection amount of space equipment is gradually increased, and a more efficient new implementation mode needs to be adopted in each stage of storage, calculation, decision, distribution and transmission. Therefore, it is necessary to research a new spatial information network architecture.
Disclosure of Invention
In order to solve at least one technical problem, the present invention provides a spatial information network architecture based on fog computing, including:
the sensing layer is used for collecting basic information of one or more applications in remote sensing, weather and positioning and sending the collected information to the cooperative processing layer;
the cooperative processing layer is connected with the sensing layer and the application service layer and is used for cooperatively processing the information acquired by the sensing layer;
and the application service layer receives the information processed by the sensing layer and the cooperative processing layer and is used for providing comprehensive application service for space-based, sea-based and land-based users.
In this scheme, the perception layer includes:
one or more of sensor node, intelligent terminal and satellite node.
In this scheme, the satellite node includes:
the system comprises a plurality of investigation satellites, a plurality of monitoring satellites and a plurality of user requests, wherein the investigation satellites are interconnected with adjacent satellites through wireless communication and used for collecting information of ground targets, ocean targets and aerial targets, carrying out investigation, monitoring and tracking on the targets, acquiring information and simultaneously carrying out distributed calculation processing on the user requests;
the system comprises a plurality of communication satellites, a plurality of satellite communication stations and a plurality of spacecrafts, wherein the communication satellites are interconnected with adjacent satellites through wireless communication and used for forwarding radio signals, realizing the radio communication between two satellite communication earth stations or between the satellite communication earth stations and the spacecrafts, and simultaneously performing distributed computing to process user requests;
the remote sensing satellites are interconnected with adjacent satellites through wireless communication and are used for collecting and recording electromagnetic wave information radiated or reflected by the earth or atmospheric targets, the electromagnetic wave information is sent to the ground by the sending equipment and the transmission equipment for processing and processing, the information of the earth environment, resources and scenery is interpreted, and meanwhile, the user request is processed through distributed calculation.
In the scheme, the cooperative processing layer comprises a space edge node, a space edge cloud and a far-end cloud.
In the scheme, the space edge nodes comprise satellite nodes; the space edge cloud comprises a space-based information harbor infrastructure and is used for bearing the functions of a space-based edge data center; the remote cloud includes a ground based information port infrastructure for assuming large scale cloud computing center functions.
The second aspect of the present invention further provides a spatial information processing method based on fog computing, which is applied to the spatial information network architecture based on fog computing, and includes:
receiving an application service request sent by an application service layer;
judging the type, the operation complexity and the operation time of the application service request;
determining a calculation processing mode according to the calculation complexity and the calculation time;
and sending the application service request data to the corresponding processing node according to the calculation processing method.
In this scheme, the determining a calculation processing manner according to the calculation complexity and the calculation time includes:
acquiring operation complexity and operation time information, and generating a quantized data value;
acquiring a calculation processing mode meeting the requirement of a quantized data value;
and selecting a calculation processing mode as a processing mode for processing the application service request according to the preset priority.
In this scheme, the generating quantized data values includes:
respectively confirming the scores of the operation complexity and the operation time information according to a preset grade;
calculating the scores of the operation complexity and the operation time information according to a preset calculation rule to obtain a calculation result;
the calculation result is a quantized data value.
In this scheme, the calculation processing mode is a single-node calculation processing mode or a multi-node cooperative calculation processing mode.
The third aspect of the present invention also provides a computer-readable storage medium, which includes a fog-calculation-based spatial information processing method program, and when the fog-calculation-based spatial information processing method program is executed by a processor, the method realizes the steps of the fog-calculation-based spatial information processing method as described in any one of the above.
By the aid of the space information Network architecture, the space information Network method and the readable storage medium based on the fog computing, distributed storage and distributed computing can be provided, Network bandwidth can be saved, a Content Distribution Network (CDN) is optimized, the Network bandwidth is saved, and interaction rate is improved. And the invention can also select the calculation mode according to the application service content, can process the application service more rapidly, utilize the computational resource to the maximum extent.
Drawings
FIG. 1 illustrates a prior art satellite information architecture of the present invention;
FIG. 2 shows a block diagram of a spatial information fog network hierarchy architecture;
FIG. 3 is a block diagram illustrating the spatial information fog network architecture of the present invention;
FIG. 4 is a flow chart of a spatial information processing method based on fog calculation according to the invention;
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Fog computing is a new computing paradigm appearing in recent years, and is more suitable for delay-sensitive applications compared with cloud computing, the fog computing expands a network computing center to the edge of a network, fog node data is processed at the edge, data transmission quantity to a cloud end is reduced, and the cloud computing has the advantages of being small in response delay, saving return bandwidth, protecting privacy and the like. Based on the advantages, the fog computing technology is introduced into a space-based information system, the space-based information system is used for innovating a space-based network architecture, novel satellite application is promoted, and the innovation of the space-based network architecture is significant. Fog computing is a highly virtualized platform, typically providing computing, storage, and network services between end devices and traditional cloud computing data centers.
With the development of technologies such as space artificial intelligence application, satellite internet of things and 5G satellite communication, users have higher requirements on a space information network, and the development of key technologies such as high-precision geometric positioning, multi-source sensor fusion, target detection tracking and information sharing needs to be supported by a more efficient space-based computing platform. The invention provides a novel paradigm (SFC) over Space information system) of a spatial information network architecture, which is an effective solution.
The space fog network architecture can realize on-track processing, greatly save the downlink bandwidth of the sky and the ground, reduce the transmission delay and meet the requirements of time-sensitive services; the effective utilization of computing storage resources of the satellite cluster is promoted; one satellite has multiple purposes, so that the system cost is reduced; promote the various development of space business, whether in military use or civilian field all bring the revolutionary development for the satellite.
Fig. 2 shows a block diagram of a spatial information fog network hierarchy architecture.
As shown in fig. 2, the present invention provides a spatial information network architecture based on fog calculation, which includes:
the sensing layer is used for collecting basic information of one or more applications in remote sensing, weather and positioning and sending the collected information to the cooperative processing layer;
the cooperative processing layer is connected with the sensing layer and the application service layer and is used for cooperatively processing the information acquired by the sensing layer;
and the application service layer receives the information processed by the sensing layer and the cooperative processing layer and is used for providing comprehensive application service for space-based, sea-based and land-based users.
It should be noted that the space information network entity based on fog computing includes 3 parts, which are a space edge node (such as a remote sensing satellite, etc.), a space edge cloud (such as a space-based information port infrastructure, which undertakes a space-based edge data center function), and a remote cloud (such as a foundation-based information port infrastructure, which undertakes a large-scale cloud computing center function).
According to an embodiment of the invention, the sensing layer comprises:
one or more of sensor node, intelligent terminal and satellite node.
According to an embodiment of the invention, the satellite node comprises:
the system comprises a plurality of investigation satellites, a plurality of monitoring satellites and a plurality of user requests, wherein the investigation satellites are interconnected with adjacent satellites through wireless communication and used for collecting information of ground targets, ocean targets and aerial targets, carrying out investigation, monitoring and tracking on the targets, acquiring information and simultaneously carrying out distributed calculation processing on the user requests;
the system comprises a plurality of communication satellites, a plurality of satellite communication stations and a plurality of spacecrafts, wherein the communication satellites are interconnected with adjacent satellites through wireless communication and used for forwarding radio signals, realizing the radio communication between two satellite communication earth stations or between the satellite communication earth stations and the spacecrafts, and simultaneously performing distributed computing to process user requests;
the remote sensing satellites are interconnected with adjacent satellites through wireless communication and are used for collecting and recording electromagnetic wave information radiated or reflected by the earth or atmospheric targets, the electromagnetic wave information is sent to the ground by the sending equipment and the transmission equipment for processing and processing, the information of the earth environment, resources and scenery is interpreted, and meanwhile, the user request is processed through distributed calculation.
According to the embodiment of the invention, the cooperative processing layer comprises a space edge node, a space edge cloud and a far-end cloud.
According to an embodiment of the present invention, the spatial edge nodes include satellite nodes; the space edge cloud comprises a space-based information harbor infrastructure and is used for bearing the functions of a space-based edge data center; the remote cloud includes a ground based information port infrastructure for assuming large scale cloud computing center functions.
Fig. 3 shows a block diagram of the spatial information fog network architecture of the present invention. As shown in fig. 3, the edge node of the invention may be an individual local area network, an unmanned aerial vehicle local area network, etc., and the cloud processing end may be one or more of a space-based management and control center, a space station data center, a space-ground integrated management and control center, a foundation management and control center, and a data center. The space-based convergence layer, the space-based access layer, the space-based network and the foundation network can be used as transition parts from the edge nodes to the cloud computing nodes and can cooperatively compute.
With the development of commercial aerospace, more and more small satellites are launched, the small satellites are limited by platforms and are difficult to be equipped with complete on-orbit computing storage resources, and with the development of intelligent technologies, the computing required by the satellite platforms with limited resources is more and more intensive, so that it is necessary to migrate the computing-intensive tasks on the satellite platforms to edge cloud facilities.
In space-based mobile edge computing platforms, space edge nodes are connected to space edge clouds by inter-satellite links to build and deploy services. When the space edge node executes the calculation intensive work flow, the satellite comprehensively analyzes the inter-satellite link channel quality and the self calculation capacity, and selects to unload the service of the calculation work to the space edge cloud or local processing.
In the space edge cloud, a space-based edge data center receives a request from a satellite user, statistically analyzes data such as current computing load, storage occupation, a communication link and a task queue, and selects to process a task request or unload a computing task to a remote cloud for processing at a proper time. And finally returning to the satellite user through the inter-satellite link.
The computation offload technology can greatly simplify the design of the small satellite and improve the service capability of the small satellite.
The cooperative computing technology enables a plurality of distributed satellite application systems to cooperate with each other, such as joint earth observation, multi-satellite data fusion and the like. In such applications, the position and the time delay are also important in the communication process, so that the space-based cooperative computing technology can be effectively supported by the space fog computing technology.
In a space-based mobile edge computing platform, a space edge cloud autonomously plans task-oriented satellite application, divides an algorithm related to a task, and sends the algorithm to a space edge node with computing resources in a scheduling sequence through an inter-satellite link. And the task nodes perform calculation processing on the distributed tasks according to the received parameters and algorithms, realize on-orbit distributed cooperative task parallel processing, and finally return calculation results to the space edge cloud. And the space edge clouds are combined to complete corresponding satellite application, so that space-based computing efficiency is improved.
Based on space fog calculation, the space-based mobile edge calculation platform can perform intra-network autonomous decision making and control space edge nodes to efficiently complete cooperative tasks.
Fig. 4 shows a flow chart of a spatial information processing method based on fog calculation according to the invention.
As shown in fig. 4, the second aspect of the present invention further provides a spatial information processing method based on fog calculation, which is applied to the spatial information network architecture based on fog calculation as described above, and includes:
s102, receiving an application service request sent by an application service layer;
s104, judging the type, the operation complexity and the operation time of the application service request;
s106, determining a calculation processing mode according to the calculation complexity and the calculation time;
and S108, sending the application service request data to the corresponding processing node according to the calculation processing method.
It should be noted that, when information is specifically processed, the application service layer makes a service request to the cooperative processing layer. And the cooperative processing layer analyzes the service types, the operation complexity and the operation time, plans the tasks and distributes the tasks to the perception layer. The sensing layer collects information and transmits the information back to the cooperative processing layer. And the cooperative processing layer processes data and sends the data to the application service layer.
It should be noted that services such as missile early warning, battlefield situation awareness, accurate positioning, 5G communication, dangerous case monitoring and the like can be provided in the application service layer. When a user selects a service, an application service request is sent to a background server, and the background server receives the application service request sent by an application service layer and judges the type, the operation complexity and the operation time of the application service request. The corresponding category and the operation complexity are preset for each application service. For example, the type of missile early warning is monitoring type, the type of 5G communication is communication type, and the like; the operation complexity of missile early warning is 5 levels, and the operation complexity of 5G communication is 1 level. Each different application service corresponds to different operation time, and the operation time can be preset by a background or can be obtained according to the current application service budget. Those skilled in the art can set the corresponding category, operation complexity and operation time of the application service according to actual needs.
According to an embodiment of the present invention, the determining a calculation processing manner according to the operation complexity and the operation time includes:
acquiring operation complexity and operation time information, and generating a quantized data value;
acquiring a calculation processing mode meeting the requirement of a quantized data value;
and selecting a calculation processing mode as a processing mode for processing the application service request according to the preset priority.
It should be noted that, in the background, corresponding quantized data value ranges are preset for each of the different processing modes. For example, the single node has a processing score of 0-10, and the fog network has a processing score of 10-20; the processing score of the remote cloud is 30-50. The skilled in the art can set a corresponding processing score rule according to actual needs, and the invention does not specifically limit the score range of the processing mode.
If all of the plurality of processing methods satisfy the current application service, an appropriate processing method is selected according to internally defined priorities. The definition of the priority needs to consider the reasonable allocation of resources and the requirement of operation time. For example, when processing 5G communication service, the quantized data value is 8, and any processing method satisfies the processing requirement, then the final processing method is determined according to the priority information, and in the priority: and if the single node is greater than the fog network and the remote cloud is greater than the remote cloud, the single node mode is preferentially selected to process the current service.
Specifically, the generating the quantized data value includes:
respectively confirming the scores of the operation complexity and the operation time information according to a preset grade;
calculating the scores of the operation complexity and the operation time information according to a preset calculation rule to obtain a calculation result;
the calculation result is a quantized data value.
It should be noted that, corresponding quantization levels are preset in the system, for example, the level of the operation complexity is 1 to 5, and the scores are respectively: 10. 20, 30, 40, 50; the grade of the operation time information is 1-7 grades; the fractions are respectively: 10. 20, 30, 40, 50, 60, 70. According to the preset grade, the operation complexity and the score of the operation time information are respectively confirmed, and a table look-up method can be adopted when the scores are determined, for example, when the application service is an accurate positioning service, the operation complexity defined in the application service is 2, the operation time information is 3, the table look-up is carried out, the score of the operation complexity is 20, and the score of the operation time information is 30. The skilled person can set the corresponding grade and score according to the actual need, and the invention does not limit the specific grade and score division, but any method using grade and score confirmation will fall into the protection scope of the invention.
It should be noted that after the score is determined, the calculation is performed according to a preset weighting algorithm. The calculation result is the coefficient 1+ the calculation complexity fraction + the coefficient 2 + the calculation time information fraction. Wherein the coefficient 1+ the coefficient 2 is 1. For example, a factor of 0.4 for 1 and 0.6 for 2; or the coefficient 1 is 0.3 and the coefficient 2 is 0.7. The specific values of the coefficient 1 and the coefficient 2 are determined by a background server, or determined by data mining according to historical data, or determined by cloud computing. After the calculation result is calculated by adopting a preset rule, the calculation result is used as a quantized data value, and a corresponding processing mode is selected according to the quantized data value.
According to the embodiment of the invention, the calculation processing mode is a single-node calculation processing mode or a multi-node cooperative calculation processing mode.
The third aspect of the present invention also provides a computer-readable storage medium, which includes a fog-calculation-based spatial information processing method program, and when the fog-calculation-based spatial information processing method program is executed by a processor, the method realizes the steps of the fog-calculation-based spatial information processing method as described in any one of the above.
By the space information network architecture, the space information network method and the readable storage medium based on the fog computing, the distributed storage and the distributed computing can be provided, the network bandwidth can be saved, the CDN is optimized, the network bandwidth is saved, and the interaction rate is improved. And the invention can also select the calculation mode according to the application service content, can process the application service more rapidly, utilize the computational resource to the maximum extent. The invention has the following specific advantages:
(1) distributed storage: the fog computing platform can perform lightweight configuration and planning on spatial edge nodes. Satellites on the spatial edge nodes have the characteristic of wide distribution, and meanwhile, the satellites are provided with large-capacity storage. Under the spatial information network architecture, a large number of fog satellite nodes can be cooperated to perform distributed storage, and storage spaces of spatial edge clouds and remote clouds are saved.
(2) Distributed computing: similarly, under the spatial information fog network architecture, heterogeneous large-scale computing resources are configured on the fog satellite nodes, and heterogeneous resource distributed computing is achieved through heterogeneous resource scheduling, so that the computing resource utilization rate of the spatial edge nodes can be improved, and the computing pressure of the spatial edge clouds and the far-end clouds is relieved.
(3) And (3) network bandwidth allocation: applications and services of the application service layer may use real-time network data (e.g., communication link conditions, network statistics, etc.) of the spatial information fog network to provide allocable network bandwidth. While new applications and services can be developed that benefit from real-time network data.
(4) And (3) backhaul bandwidth is saved: the fog satellite nodes predict the requirements of mobile users on information in an active mode, and information sources sensitive to the users can be processed and stored on the specific low-orbit fog satellite nodes. In terms of network topology, a user can directly acquire required information from the fog satellite node, unnecessary or unneeded data are reduced from being transmitted back to the space edge cloud and the far-end cloud, and network transmission back bandwidth is effectively saved.
(5) To help the effective implementation of CDN: a Content Distribution Network (CDN) is a Network that deploys a cache service at the edge of the Internet, reducing download delay of remote site Content. But the user interest oriented to the method is wide, the service requirement is fuzzy, and the accurate service is difficult to predict. The real-time network data in the spatial information fog network can realize optimization of the CDN, the fog satellite nodes have clearer target user and service requirements, the fog satellite nodes fully utilize storage and computing resources of the fog satellite nodes to provide optimal services for mobile users, and high performance and availability of content distribution can be ensured more easily.
(6) Cross-layer optimization: the fog node may autonomously manage the communication network and application services provided within the coverage area. The spatial information fog network can manage the whole communication layer through real-time network data, meanwhile, the fog satellite node senses information context, and the application service layer has the best user service quality through cross-layer optimization.
(7) Real-time nature of the interaction: the delay of mobile services is mainly affected by three factors, namely propagation distance, computing power and data rate. When the fog satellite node is operating in low orbit, the effect of the inherent delay between the satellite and the user is reduced. And the fog satellite nodes have strong distributed computing resources and can process computing-intensive programs in real time. Meanwhile, real-time network bandwidth allocation can provide a high-quality transmission link, minimize congestion in other parts of the network, and improve user experience, thereby achieving the effect of near real-time interaction.
The space edge nodes can be linked to a network, the space edge cloud is a small-scale data center deployed to a space base and is responsible for network flow control and control of various mobile edge satellite services and applications, when the processing capacity of the fog satellite nodes cannot meet the requirements of the space edge cloud nodes, computing-intensive tasks and mass data can be migrated to the space base edge cloud through the satellite network for processing, particularly time-sensitive and military services, and when the edge cloud cannot meet the requirements of edge equipment, part of tasks and data can be migrated to a remote cloud for processing.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
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; can be located in one place or 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, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several 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 methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (9)
1. A spatial information processing method based on fog calculation is applied to a spatial information network architecture based on fog calculation, and is characterized in that the architecture comprises the following steps: the sensing layer is used for collecting basic information of one or more applications in remote sensing, weather and positioning and sending the collected information to the cooperative processing layer; the cooperative processing layer is connected with the sensing layer and the application service layer and is used for cooperatively processing the information acquired by the sensing layer; the application service layer is used for receiving the information processed by the sensing layer and the cooperative processing layer and providing comprehensive application service for space-based, sea-based and land-based users;
the method comprises the following steps:
receiving an application service request sent by an application service layer;
judging the type, the operation complexity and the operation time of the application service request;
determining a calculation processing mode according to the calculation complexity and the calculation time;
and sending the application service request data to a corresponding processing node according to the calculation processing mode.
2. The spatial information processing method based on fog calculation as set forth in claim 1, wherein the determining a calculation processing manner according to the calculation complexity and the calculation time comprises:
acquiring operation complexity and operation time information, and generating a quantized data value;
acquiring a calculation processing mode meeting the requirement of a quantized data value;
and selecting a calculation processing mode as a processing mode for processing the application service request according to the preset priority.
3. The spatial information processing method based on fog calculation as set forth in claim 2, wherein the generating quantized data values comprises:
respectively confirming the scores of the operation complexity and the operation time information according to a preset grade;
calculating the scores of the operation complexity and the operation time information according to a preset calculation rule to obtain a calculation result;
the calculation result is a quantized data value.
4. The spatial information processing method based on fog computing as claimed in claim 1, wherein the computing processing mode is a single-node computing processing mode or a multi-node collaborative computing processing mode.
5. The spatial information processing method based on fog calculation as set forth in claim 1, wherein the perception layer comprises:
one or more of sensor node, intelligent terminal and satellite node.
6. The spatial information processing method based on fog calculation as set forth in claim 5, wherein the satellite node comprises:
the system comprises a plurality of investigation satellites, a plurality of monitoring satellites and a plurality of user requests, wherein the investigation satellites are interconnected with adjacent satellites through wireless communication and used for collecting information of ground targets, ocean targets and aerial targets, carrying out investigation, monitoring and tracking on the targets, acquiring information and simultaneously carrying out distributed calculation processing on the user requests;
the system comprises a plurality of communication satellites, a plurality of satellite communication stations and a plurality of spacecrafts, wherein the communication satellites are interconnected with adjacent satellites through wireless communication and used for forwarding radio signals, realizing the radio communication between two satellite communication earth stations or between the satellite communication earth stations and the spacecrafts, and simultaneously performing distributed computing to process user requests;
the remote sensing satellites are interconnected with adjacent satellites through wireless communication and are used for collecting and recording electromagnetic wave information radiated or reflected by the earth or atmospheric targets, the electromagnetic wave information is sent to the ground by the sending equipment and the transmission equipment for processing and processing, the information of the earth environment, resources and scenery is interpreted, and meanwhile, the user request is processed through distributed calculation.
7. The spatial information processing method based on fog computing as claimed in claim 1, wherein the cooperative processing layer comprises spatial edge nodes, spatial edge clouds and remote clouds.
8. The fog-computation-based spatial information processing method according to claim 7, wherein the spatial edge nodes include satellite nodes; the space edge cloud comprises a space-based information harbor infrastructure and is used for bearing the functions of a space-based edge data center; the remote cloud includes a ground based information port infrastructure for assuming large scale cloud computing center functions.
9. A computer-readable storage medium, characterized in that a fog-computation-based spatial information processing method program is included in the computer-readable storage medium, and when being executed by a processor, the fog-computation-based spatial information processing method program realizes the steps of a fog-computation-based spatial information processing method according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910046373.5A CN109936619B (en) | 2019-01-18 | 2019-01-18 | Spatial information network architecture, method and readable storage medium based on fog calculation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910046373.5A CN109936619B (en) | 2019-01-18 | 2019-01-18 | Spatial information network architecture, method and readable storage medium based on fog calculation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109936619A CN109936619A (en) | 2019-06-25 |
| CN109936619B true CN109936619B (en) | 2021-07-20 |
Family
ID=66984962
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910046373.5A Active CN109936619B (en) | 2019-01-18 | 2019-01-18 | Spatial information network architecture, method and readable storage medium based on fog calculation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109936619B (en) |
Families Citing this family (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110473015A (en) * | 2019-08-09 | 2019-11-19 | 南京智骋致想电子科技有限公司 | A kind of smart ads system and advertisement placement method |
| CN110633144A (en) * | 2019-08-23 | 2019-12-31 | 成都华为技术有限公司 | Method and device for fusion management of edge cloud |
| CN110753107B (en) * | 2019-10-21 | 2022-12-20 | 中国科学院空间应用工程与技术中心 | Resource scheduling system, method and storage medium under space-based cloud computing architecture |
| CN110740183A (en) * | 2019-10-21 | 2020-01-31 | 中国科学院空间应用工程与技术中心 | Resource allocation method, system and storage medium under space-based cloud computing architecture |
| CN110730138A (en) * | 2019-10-21 | 2020-01-24 | 中国科学院空间应用工程与技术中心 | Dynamic resource allocation method, system and storage medium for space-based cloud computing architecture |
| CN110719335B (en) * | 2019-10-21 | 2022-10-04 | 中国科学院空间应用工程与技术中心 | Resource scheduling method, system and storage medium under space-based cloud computing architecture |
| CN111027397B (en) * | 2019-11-14 | 2023-05-12 | 上海交通大学 | Comprehensive feature target detection method, system, medium and equipment suitable for intelligent monitoring network |
| CN111124640A (en) * | 2019-12-11 | 2020-05-08 | 浙江大华技术股份有限公司 | Task allocation method and system, storage medium and electronic device |
| CN111132063A (en) * | 2019-12-27 | 2020-05-08 | 山东超越数控电子股份有限公司 | Wearable equipment system for special combat |
| CN111614395B (en) * | 2020-04-21 | 2021-08-13 | 中国人民解放军军事科学院国防科技创新研究院 | Data processing method for satellite-to-ground direct connection terminal in satellite-to-ground direct connection system |
| CN111421554B (en) * | 2020-05-22 | 2021-05-04 | 中国科学院自动化研究所 | Mechanical arm intelligent control system, method and device based on edge calculation |
| CN111711991B (en) * | 2020-06-08 | 2023-08-08 | 中国科学院上海微***与信息技术研究所 | Calculation task scheduling method in star-ground fusion network |
| CN114253697A (en) * | 2020-09-22 | 2022-03-29 | 中国科学院沈阳自动化研究所 | Equipment state monitoring edge calculation framework for lithium ion battery cell manufacturing |
| CN112929074B (en) * | 2021-01-27 | 2022-02-08 | 东南大学 | Satellite and high-altitude platform assisted satellite-ground edge computing task unloading method |
| CN113329050B (en) * | 2021-04-20 | 2022-06-21 | 清华大学 | Content distribution method and system |
| CN113938176A (en) * | 2021-08-26 | 2022-01-14 | 西安空间无线电技术研究所 | Low-delay service space-based computing method |
| CN114337783B (en) * | 2021-12-30 | 2023-11-17 | 中国电子科技集团公司电子科学研究院 | Space distributed edge computing device and business processing method |
| CN114362809B (en) * | 2022-01-10 | 2023-11-24 | 中国人民解放军国防科技大学 | Space-based intelligent network connection edge computing system |
| CN114584199A (en) * | 2022-03-01 | 2022-06-03 | 中国电子科技集团公司第五十四研究所 | Earth observation operation system architecture based on space cloud service |
| CN115459828B (en) * | 2022-07-25 | 2023-11-28 | 中国人民解放军军事科学院国防科技创新研究院 | Autonomous migration method of service for low-orbit constellation edge micro cloud |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103530168A (en) * | 2013-10-14 | 2014-01-22 | 中国科学院对地观测与数字地球科学中心 | Multi-satellite remote sensing data processing system and method based on virtualization technology |
| CN106230497A (en) * | 2016-09-27 | 2016-12-14 | 中国科学院空间应用工程与技术中心 | A kind of Information Network resource bilayer dispatching method and system |
| CN206226436U (en) * | 2016-09-27 | 2017-06-06 | 中国科学院空间应用工程与技术中心 | A kind of Information Network resource bilayer scheduling system |
| CN107343025A (en) * | 2017-06-07 | 2017-11-10 | 西安电子科技大学 | Time delay optimization method under the distributed satellites cloud and mist network architecture and power consumption constraint |
| CN107404526A (en) * | 2017-07-25 | 2017-11-28 | 桂林电子科技大学 | P2P remotely-sensed data network self-adapting dissemination systems and method based on SDN |
| CN108989099A (en) * | 2018-07-02 | 2018-12-11 | 北京邮电大学 | Federated resource distribution method and system based on software definition Incorporate network |
| CN109121141A (en) * | 2018-07-24 | 2019-01-01 | 北京邮电大学 | A kind of star based on MEC server ground two-stage edge network and its collaboration method |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140278108A1 (en) * | 2013-03-13 | 2014-09-18 | Locus Energy, Llc | Methods and Systems for Optical Flow Modeling Applications for Wind and Solar Irradiance Forecasting |
| CN106507366B (en) * | 2016-11-25 | 2019-11-05 | 中国航空无线电电子研究所 | The repeater satellite sky time-frequency domain resources dynamic dispatching method of facing multiple users |
| CN113064185B (en) * | 2017-01-11 | 2022-07-19 | 荣耀终端有限公司 | Positioning method, terminal and server |
-
2019
- 2019-01-18 CN CN201910046373.5A patent/CN109936619B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103530168A (en) * | 2013-10-14 | 2014-01-22 | 中国科学院对地观测与数字地球科学中心 | Multi-satellite remote sensing data processing system and method based on virtualization technology |
| CN106230497A (en) * | 2016-09-27 | 2016-12-14 | 中国科学院空间应用工程与技术中心 | A kind of Information Network resource bilayer dispatching method and system |
| CN206226436U (en) * | 2016-09-27 | 2017-06-06 | 中国科学院空间应用工程与技术中心 | A kind of Information Network resource bilayer scheduling system |
| CN107343025A (en) * | 2017-06-07 | 2017-11-10 | 西安电子科技大学 | Time delay optimization method under the distributed satellites cloud and mist network architecture and power consumption constraint |
| CN107404526A (en) * | 2017-07-25 | 2017-11-28 | 桂林电子科技大学 | P2P remotely-sensed data network self-adapting dissemination systems and method based on SDN |
| CN108989099A (en) * | 2018-07-02 | 2018-12-11 | 北京邮电大学 | Federated resource distribution method and system based on software definition Incorporate network |
| CN109121141A (en) * | 2018-07-24 | 2019-01-01 | 北京邮电大学 | A kind of star based on MEC server ground two-stage edge network and its collaboration method |
Non-Patent Citations (1)
| Title |
|---|
| "雾计算的概念相关研究与应用";贾维嘉;《通信学报》;20180531;第39卷(第5期);153-165 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109936619A (en) | 2019-06-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109936619B (en) | Spatial information network architecture, method and readable storage medium based on fog calculation | |
| CN109818669B (en) | Virtualization-based satellite service processing method, system and storage medium | |
| Liu et al. | Deep reinforcement learning based latency minimization for mobile edge computing with virtualization in maritime UAV communication network | |
| Yu et al. | EC-SAGINs: Edge-computing-enhanced space–air–ground-integrated networks for internet of vehicles | |
| Shang et al. | Computing over space-air-ground integrated networks: Challenges and opportunities | |
| Huda et al. | Survey on computation offloading in UAV-Enabled mobile edge computing | |
| Zhang et al. | Air-ground integrated mobile edge networks: A survey | |
| Wei et al. | Application of edge intelligent computing in satellite Internet of Things | |
| Lakew et al. | Intelligent offloading and resource allocation in heterogeneous aerial access IoT networks | |
| Al-Hilo et al. | RIS-assisted UAV for timely data collection in IoT networks | |
| CN114268357B (en) | Method, system, equipment and application for unloading computing tasks based on low-orbit satellite edges | |
| Mohammed et al. | Deep reinforcement learning for computation offloading and resource allocation in blockchain-based multi-UAV-enabled mobile edge computing | |
| Chen et al. | Learning-based computation offloading for IoRT through Ka/Q-band satellite–terrestrial integrated networks | |
| Cao et al. | Space-based cloud-fog computing architecture and its applications | |
| Nguyen et al. | Towards flying mobile edge computing | |
| CN116366134A (en) | Space-based Internet of things multi-star collaborative strategy construction method based on element space-time expansion diagram | |
| CN112469047A (en) | Method for deploying space-ground integrated intelligent network satellite nodes | |
| CN113098583A (en) | Air-space-ground integrated networking method for tracking air moving target | |
| Tang et al. | Machine learning for space–air–ground integrated network assisted vehicular network: A novel network architecture for vehicles | |
| Wang et al. | Double-edge computation offloading for secure integrated space-air-aqua networks | |
| Zhang et al. | Mobile edge computing for UAVs | |
| Wang et al. | Resource scheduling in mobile edge computing using improved ant colony algorithm for space information network | |
| Jia et al. | Collaborative satellite-terrestrial edge computing network for everyone-centric Customized services | |
| Wang et al. | Load-balancing method for leo satellite edge-computing networks based on the maximum flow of virtual links | |
| CN115827185B (en) | Method, storage medium and equipment for combining 6G air base station with Beidou air obstacle avoidance |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |