CN111773662A - Cloud game acceleration method, system, device and medium based on fog calculation - Google Patents
Cloud game acceleration method, system, device and medium based on fog calculation Download PDFInfo
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/30—Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers
- A63F13/35—Details of game servers
- A63F13/352—Details of game servers involving special game server arrangements, e.g. regional servers connected to a national server or a plurality of servers managing partitions of the game world
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/30—Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers
- A63F13/33—Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers using wide area network [WAN] connections
- A63F13/335—Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers using wide area network [WAN] connections using Internet
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- G—PHYSICS
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- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
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Abstract
The application discloses cloud game acceleration method, system, device and medium based on fog calculation, wherein the method comprises the step of obtaining the corresponding relation between relevant data related to historical cloud games and a data processing scheme in advance, so that a target data processing scheme can be determined according to the corresponding relation when the current fog calculation resources and target client running data are obtained, the target data processing scheme comprises fog calculation nodes, and the fog calculation nodes are closer to the edge side where the cloud game client is located, and a large amount of bandwidth is not needed in data transmission, so that the data downlink speed is increased, the transmission rate of the cloud games is greatly increased, and the game experience of players is improved.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a cloud game acceleration method, system, device, and medium based on fog computing.
Background
With the maturity of cloud computing technology, the traditional computing service mode is changed greatly, a large amount of physical hardware resources are aggregated by the cloud center, unified allocation, scheduling and management of heterogeneous network computing resources are realized by adopting a virtualization technology, and the cost of computing and storing is greatly reduced by intensively building a data center.
The cloud game is an online game technology based on a cloud computing technology, and enables light-end equipment with relatively limited graphic processing and data operation capacity to run a high-quality game. In a cloud game scene, a game is not in a player game terminal but runs in a cloud server, and the player game terminal does not need to have strong graphic operation and data processing capacity and only needs to have basic streaming media playing capacity and capacity of acquiring input instructions of a player and sending the input instructions to the cloud server.
The appearance of the cloud game brings a new direction for game development, however, due to the fact that the region distribution of game players is wide, the data volume generated by the players is huge, and meanwhile, video transmission after cloud game video rendering has higher requirements on a game player network, the transmission rate can be reduced, the problem of control delay can be caused, and bad game experience can be brought to the players.
In view of the foregoing prior art, finding a method for effectively improving the running effect and user experience of a cloud game is an urgent problem to be solved by those skilled in the art.
Disclosure of Invention
The application aims to provide a cloud game acceleration method, a cloud game acceleration system, a cloud game acceleration device and a cloud game acceleration medium based on fog calculation.
In order to solve the above technical problem, the present application provides a cloud game acceleration method based on fog calculation, including:
acquiring a corresponding relation between related data related to historical cloud games and a data processing scheme, wherein the related data comprises fog computing resources and client operation data, the data processing scheme comprises objects participating in processing the cloud game data and a data processing method, and the objects participating in processing the cloud game data at least comprise fog computing nodes;
acquiring current fog computing resources and target client operating data;
and determining a target data processing scheme according to the corresponding relation so that the fog computing node can perform corresponding data processing.
Preferably, the fog computing resource specifically includes a geographical location distribution, an operating state, and log data of the fog computing node;
the client operation data specifically comprises log data of a cloud game client, and position data and network conditions of terminal equipment where the cloud game client is located.
Preferably, the objects participating in processing cloud game data specifically include a cloud server and a fog computing node;
the data processing method specifically comprises the following steps:
the cloud server acquires cloud game data and an operation instruction generated by user operation;
the cloud server carries out image rendering on the cloud game data according to the operation instruction to obtain a game video;
the cloud server encodes the game video;
the cloud server sends the coded game video to a fog computing node;
and the fog computing node sends the coded game video to target terminal equipment.
Preferably, the objects participating in processing cloud game data specifically include a fog computing node;
the data processing method specifically comprises the following steps:
the cloud computing node acquires cloud game data and an operation instruction generated by user operation;
the cloud computing node performs image rendering on the cloud game data according to the operation instruction to obtain a game video;
the fog computing node encodes the game video;
and the fog computing node sends the coded game video to the target terminal equipment.
Preferably, the objects participating in processing cloud game data specifically include a fog computing node;
the data processing method specifically comprises the following steps:
the cloud computing node acquires cloud game data and an operation instruction generated by user operation;
the cloud computing node performs image rendering on the cloud game data according to the operation instruction to obtain a game video;
and the fog computing node sends the game video to target terminal equipment.
Preferably, the objects participating in processing cloud game data specifically include a fog computing node;
the data processing method specifically comprises the following steps:
the method comprises the steps that a first fog computing node obtains cloud game data and an operation instruction generated by user operation;
the first fog computing node performs image rendering on the cloud game data according to the operation instruction to obtain a game video;
the first fog computing node sends the game video to a second fog computing node;
the second fog computing node sends the game video to target terminal equipment;
the first fog computer node is a node with the most residual computing resources, and the second fog computer node is a node with the most residual transmission resources.
In order to solve the above technical problem, the present application further provides a cloud game acceleration system based on fog calculation, including: a cloud server and a fog computing node;
the cloud server is used for acquiring the corresponding relation between related data related to historical cloud games and a data processing scheme and acquiring current cloud computing resources and target client operating data; determining a target data processing scheme according to the corresponding relation so that the fog computing node can perform corresponding data processing; the relevant data comprises fog computing resources and client operation data, the data processing scheme comprises objects participating in processing cloud game data and a data processing method, and the objects participating in processing the cloud game data at least comprise fog computing nodes;
and the fog computing node is in communication connection with the cloud server through a network and is used for carrying out corresponding data processing according to the data processing scheme.
In order to solve the above technical problem, the present application further provides a cloud game accelerating device based on fog calculation, including:
the cloud game processing system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring the corresponding relation between related data related to historical cloud games and a data processing scheme, the related data comprises fog computing resources and client operation data, the data processing scheme comprises objects participating in processing the cloud game data and a data processing method, and the objects participating in processing the cloud game data at least comprise fog computing nodes;
the second acquisition module is used for acquiring the current fog computing resource and the target client operating data;
and the determining module is used for determining a target data processing scheme according to the corresponding relation so as to facilitate the fog computing node to perform corresponding data processing.
In order to solve the above technical problem, the present application further provides a cloud game acceleration apparatus based on fog calculation, including a memory for storing a computer program;
a processor for implementing the steps of the fog-computing based cloud game acceleration method as described when executing the computer program.
In order to solve the above technical problem, the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores thereon a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the cloud game acceleration method based on fog calculation.
According to the cloud game acceleration method based on the fog computing, the corresponding relation between the related data related to the historical cloud game and the data processing scheme is obtained in advance, the target data processing scheme can be determined according to the corresponding relation when the current fog computing resource and the target client running data are obtained, the target data processing scheme comprises the fog computing node, the fog computing node is closer to the edge side where the cloud game client is located, a large amount of bandwidth is not needed in data transmission, the data downlink speed is improved, the transmission rate of the cloud game is greatly improved, and the game experience of a player is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application, the drawings needed for the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained by those skilled in the art without inventive effort.
Fig. 1 is a flowchart of a cloud game acceleration method based on fog calculation according to an embodiment of the present disclosure;
fig. 2 is a flowchart of another cloud game acceleration method based on fog calculation according to an embodiment of the present disclosure;
fig. 3 is a flowchart of another cloud game acceleration method based on fog calculation according to an embodiment of the present disclosure;
fig. 4 is a flowchart of another cloud game acceleration method based on fog calculation according to an embodiment of the present disclosure;
fig. 5 is a flowchart of another cloud game acceleration method based on fog calculation according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of a cloud game acceleration system based on fog calculation according to an embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of a cloud game acceleration apparatus based on fog calculation according to an embodiment of the present disclosure;
fig. 8 is a schematic structural diagram of another cloud game acceleration apparatus based on fog calculation according to an embodiment of the present disclosure;
wherein, 1 is a cloud server, and 2 is a fog computing node.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without any creative effort belong to the protection scope of the present application.
The cloud game acceleration method based on the fog computing can improve the transmission rate of the cloud game and further improve the game experience of a player.
In order that those skilled in the art will better understand the disclosure, the following detailed description will be given with reference to the accompanying drawings.
Fig. 1 is a flowchart of a cloud game acceleration method based on fog calculation according to an embodiment of the present application, and as shown in fig. 1, the method includes:
s10: and acquiring the corresponding relation between the related data related to the historical cloud games and the data processing scheme.
The related data comprises fog computing resources and client operation data, the data processing scheme comprises objects and data processing methods which participate in processing cloud game data, and the objects which participate in processing the cloud game data at least comprise fog computing nodes.
In specific implementation, the cloud server collects a large amount of relevant data related to historical cloud games, including fog computing resources, client operation data and the like, the data are gathered to form a large amount of independently operating data units through technologies such as virtualization and container, then a neural network model is designed for the data units, and training is performed in the cloud server to obtain a data processing scheme corresponding to the neural network model.
It should be noted that the fog computing node mentioned in the present application is a bridge between the cloud server and the terminal device, provides resources such as computation and storage, can implement large-scale computation such as image rendering of the cloud game on the fog computing node, and interacts with the cloud server and the terminal player. The cloud computing node is low in position in the network topology, is closer to the edge side where the cloud game client is located, and has smaller network delay. In addition, the method for acquiring the fog computing resources is not limited, the fog computing nodes can be registered in the cloud server, so that the cloud server is provided with relevant data of the fog computing resources in real time, and the cloud computing nodes can manage the cloud platform to be connected to the cloud server through other fog computing nodes to finish acquisition and transmission of the fog computing resources.
S11: and acquiring the current fog computing resource and the target client operating data.
S12: and determining a target data processing scheme according to the corresponding relation so that the fog computing node can perform corresponding data processing.
In specific implementation, when the current fog computing resource and the target client operating data are acquired, a target data processing scheme is determined according to the corresponding relation so that the fog computing node can perform corresponding data processing conveniently.
It should be noted that, the specific action of the mist computing node for performing the corresponding data processing may be, according to the actual situation, storing the mist computing node itself or data from the cloud game client, or sending related data sent by the cloud service to the terminal device, or analyzing and calculating related data transmitted by the cloud server, which is not limited in this application.
Therefore, according to the cloud game acceleration method based on the fog computing, the corresponding relation between the related data related to the historical cloud game and the data processing scheme is obtained in advance, the target data processing scheme can be determined according to the corresponding relation when the current fog computing resource and the target client running data are obtained, the target data processing scheme comprises the fog computing node, and the fog computing node is closer to the edge side where the cloud game client is located, so that a large amount of bandwidth is not needed for data transmission, the data downlink speed is increased, the transmission rate of the cloud game is greatly increased, and the game experience of a player is improved.
On the basis of the above embodiment, the fog computing resources specifically include the geographical location distribution, the operating state, and the log data of the fog computing nodes; the client operation data specifically comprises log data of the cloud game client, position data of the terminal equipment where the cloud game client is located and network conditions.
It should be noted that the terminal device is a mobile or fixed networked computing device, including a smart phone, a tablet computer, or a personal computer.
In the specific implementation, the geographic positions of the fog computing nodes are not uniform, if a player at a cloud game client is in Beijing and the fog computing nodes are arranged in Guangdong, the game running speed is very slow due to the cross-region reason when the player plays the game, the game experience of the player is influenced, and the player is easy to lose. Therefore, the cloud server needs to acquire the geographical position distribution condition of a large number of fog computing nodes, so that the fog computing nodes closer to players are distributed on the demand side of the cloud game client, and the transmission rate is further improved.
It should be noted that, the operation state of the fog computing node mentioned in this embodiment refers to a use condition of the fog computing node, because a bandwidth provided by each fog computing node is limited, if a service is provided for multiple cloud game clients at the same time, the speed of cloud game data transmission is slow, and sometimes even the cloud game clients cannot be opened, so that the cloud server needs to obtain the operation state of the fog computing node to perform better distribution.
It can be understood that, based on the same considerations as those described above, the cloud server needs to obtain the location data and the network condition of the terminal device where the cloud game client is located. In addition, the log data of the fog computing node and the log data of the cloud game client comprise data such as background process tracking kernel logs and user tracking, and after the cloud server collects the information, a personalized data processing scheme can be formed for specific players through big data analysis, so that the game experience of the players is further improved.
On the basis of the above embodiments, in order to make the technical solutions proposed in the present application more clear to those skilled in the art, data processing schemes under different situations are specifically described below.
Fig. 2 is a flowchart of another cloud game acceleration method based on fog calculation according to an embodiment of the present disclosure. As shown in fig. 2, as a preferred embodiment, the objects participating in processing cloud game data specifically include a cloud server and a fog computing node.
The data processing method specifically comprises the following steps:
s20: the cloud server acquires cloud game data and an operation instruction generated by user operation.
S21: and the cloud server carries out image rendering on the cloud game data according to the operation instruction to obtain a game video.
S22: the cloud server encodes the game video.
S23: and the cloud server sends the coded game video to the fog computing node.
S24: and the fog computing node sends the coded game video to the target terminal equipment.
In specific implementation, the cloud game data includes internal data and cache generated by the cloud game, such as pictures and videos, and also includes computing services related to the cloud game, such as image rendering and deep learning, and the cloud server needs to select different cloud computing nodes for different service scenes. For example, a chess game picture is simple, and too many image renderings are not needed, while a hero competitive game like a royal requires a large number of image renderings, so in S23, if the game data is displayed as a chess game, a common fog computing node is selected; and if the cloud game data shows that the prince glows, selecting the node with the most residual computing resources, namely the fog computing node with strong graph computing capability.
The operation command generated by the user operation is the actions of walking, jumping, etc. and the operation command is transmitted by the fog computing node, but the type of the fog computing node is not limited in the embodiment of the present application, and the cloud game client may select an appropriate fog computing node according to the amount of data uploaded by the cloud game client and transmit the command to the cloud server.
In S21, the cloud server performs image rendering on the cloud game data according to the operation instruction. Taking an urban scene in a racing game as an example, the cloud server needs to render the urban scene, the racing car, the track and a non-player controlled character (NPC) to obtain a game video.
Further, the rendered game video is large, and the requirement on the network condition of the user is high when the game video is directly transmitted, so that the cloud server encodes the game video, sends the encoded game video to the fog computing node with the most residual transmission resources, namely the node with strong network capacity, takes the fog computing node as an intermediate node, sends the encoded game video to the target terminal device, and then the cloud game client in the target terminal device decodes and displays the game video.
Therefore, according to the cloud game acceleration method based on the fog computing, the cloud game data and the operation instruction generated by the user operation are obtained, the image rendering and encoding are carried out on the cloud game data, and then the encoded video is sent to the fog computing node with the most residual transmission resources, namely the node with strong network capacity for transmission; in addition, the cloud game client can select a proper fog computing node according to the uploaded data volume to send an instruction to the cloud server, so that the data uploading speed is increased, the transmission rate of the cloud game is greatly increased, and the game experience of a player is improved.
In a specific implementation, since the cloud server is far away from the cloud computing node, and data transmission also requires a lot of time, fig. 3 is a flowchart of another cloud game acceleration method based on fog computing according to an embodiment of the present application, and as shown in fig. 3, as a preferred embodiment, an object participating in processing cloud game data specifically includes the fog computing node.
The data processing method specifically comprises the following steps:
s30: the cloud computing node obtains cloud game data and an operation instruction generated by user operation.
S31: and the fog computing node performs image rendering on the cloud game data according to the operation instruction to obtain a game video.
S32: the fog computing node encodes the game video.
S33: and the fog computing node sends the coded game video to the target terminal equipment.
In a specific implementation, in order to further increase the speed of cloud game transmission, a node with the most remaining computing resources, that is, a fog computing node with strong graph computing capability, may be selected to perform image rendering and encoding on cloud game data, and then send the encoded game video to a target terminal device.
According to the cloud game acceleration method based on the fog computing, after the cloud game data and the operation instruction generated by the user operation are obtained, a large number of computing services such as image rendering and coding are carried out on the cloud game data and are pushed to the fog computing node, the fog computing node is closer to the edge side where the cloud game client side is located, and data transmission does not need a large amount of bandwidth, so that the data downlink speed is increased, the transmission rate of the cloud game is greatly increased, and the game experience of a player is improved.
Fig. 4 is a flowchart of another cloud game acceleration method based on fog calculation according to an embodiment of the present disclosure. As shown in fig. 4, the objects participating in processing cloud game data specifically include fog computing nodes.
The data processing method specifically comprises the following steps:
s40: the cloud computing node obtains cloud game data and an operation instruction generated by user operation.
S41: and the fog computing node performs image rendering on the cloud game data according to the operation instruction to obtain a game video.
S42: and the fog computing node sends the game video to the target terminal equipment.
In specific implementation, if the transmission rate between the target terminal device and the fog computing node is fast, for example, the fog computing node of the directly connected 5G base station AP, the fog computing node may directly send the cloud game data to the target terminal device without encoding the video after performing image rendering on the cloud game data according to the operation instruction to obtain the game video.
According to the cloud game acceleration method based on the fog computing, the cloud game data are subjected to image rendering by the fog computing nodes after the cloud game data and the operation instructions generated by user operation are obtained, and then the video is directly sent to the target terminal device.
In a specific implementation, if there is no fog computing node with strong graph computing capability and strong network uplink and downlink capability near the target terminal device, please refer to fig. 5, where fig. 5 is a flowchart of another cloud game acceleration method based on fog computing according to an embodiment of the present application, and an object participating in processing cloud game data specifically includes the fog computing node.
The data processing method specifically comprises the following steps:
s50: the method comprises the steps that a first fog computing node obtains cloud game data and an operation instruction generated by user operation;
s51: the first fog computing node performs image rendering on the cloud game data according to the operation instruction to obtain a game video;
s52: the first fog computing node sends the game video to the second fog computing node;
s53: the second fog computing node sends the game video to the target terminal equipment;
the first fog computer node is the node with the most residual computing resources, and the second fog computer node is the node with the most residual transmission resources.
According to the cloud game acceleration method based on the fog computing, after the cloud game data and the operation instruction generated by the user operation are obtained, the cloud game data are subjected to image rendering by the node with the most residual computing resources, and the video is sent to the target terminal device by the node with the most residual transmission resources, so that the time for encoding and decoding the video is saved, the transmission rate of the cloud game is improved, and the game experience of a player is improved.
In the above embodiments, the cloud game acceleration method based on fog calculation is described in detail, and on this basis, the present application also provides a cloud game acceleration system based on fog calculation, which is explained from the structure and connection relationship of hardware devices.
Fig. 6 is a schematic structural diagram of a cloud game acceleration system based on fog calculation according to an embodiment of the present application, where the system includes: cloud server 1 and fog computing node 2.
The cloud server 1 is used for acquiring the corresponding relation between related data related to historical cloud games and a data processing scheme and acquiring current cloud computing resources and target client operating data; determining a target data processing scheme according to the corresponding relation so that the fog computing node 2 can perform corresponding data processing; the related data comprises fog computing resources and client operation data, the data processing scheme comprises objects and data processing methods which participate in processing cloud game data, and the objects which participate in processing the cloud game data at least comprise the fog computing nodes 2.
The fog computing node 2 is in communication connection with the cloud server 1 through a network and is used for performing corresponding data processing according to a data processing scheme.
Since the embodiments of the system part and the method part correspond to each other, for the embodiments of the apparatus part, reference is made to the description of the embodiments of the method part, and details are not repeated here.
The cloud game acceleration system based on the fog computing, provided by the application, because the corresponding relation between the related data related to the historical cloud game and the data processing scheme is obtained in advance, the target data processing scheme can be determined according to the corresponding relation when the current fog computing resource and the target client running data are obtained, and the target data processing scheme comprises the fog computing node.
In the foregoing embodiments, the cloud game acceleration method and system based on fog calculation are described in detail, and the present application also provides embodiments corresponding to the cloud game acceleration apparatus based on fog calculation. It should be noted that the present application describes the embodiments of the apparatus portion from two perspectives, one from the perspective of the function module and the other from the perspective of the hardware.
Fig. 7 is a schematic structural diagram of a cloud game acceleration apparatus based on fog calculation according to an embodiment of the present application. As shown in fig. 7, the apparatus includes, based on the angle of the function module:
the first obtaining module 10 is configured to obtain a corresponding relationship between related data related to a historical cloud game and a data processing scheme, where the related data includes a fog computing resource and client operation data, the data processing scheme includes an object participating in processing the cloud game data and a data processing method, and the object participating in processing the cloud game data at least includes a fog computing node.
And the second obtaining module 11 is configured to obtain the current fog computing resource and the target client operating data.
And the determining module 12 is configured to determine a target data processing scheme according to the corresponding relationship so that the fog computing node performs corresponding data processing.
As a preferred embodiment, the method further comprises the following steps:
and the third acquisition module is used for acquiring cloud game data and an operation instruction generated by user operation.
And the rendering module is used for performing image rendering on the cloud game data according to the operation instruction to obtain a game video.
And the coding module is used for coding the game video.
And the first sending module is used for sending the encoded game video to the fog computing node by the cloud server.
And the second sending module is used for sending the encoded game video to the target terminal equipment by the fog computing node.
Since the embodiments of the apparatus portion and the method portion correspond to each other, please refer to the description of the embodiments of the method portion for the embodiments of the apparatus portion, which is not repeated here.
The cloud game accelerating device based on the fog computing, provided by the application, because the corresponding relation between the related data related to the historical cloud game and the data processing scheme is obtained in advance, the target data processing scheme can be determined according to the corresponding relation when the current fog computing resource and the target client running data are obtained, and the target data processing scheme comprises the fog computing node, because the fog computing node is closer to the edge side where the cloud game client is located, a large amount of bandwidth is not needed in data transmission, the data downlink speed is improved, the transmission rate of the cloud game is greatly improved, and the game experience of a player is improved.
Fig. 8 is a schematic structural diagram of another cloud game acceleration apparatus based on fog calculation according to an embodiment of the present application. As shown in fig. 8, the apparatus includes, from the perspective of the hardware configuration: a memory 20 for storing a computer program;
a processor 21 for implementing the steps of the cloud game acceleration method based on fog calculation as described in the above embodiments when executing the computer program.
The memory 20 includes at least one type of readable storage medium, which includes a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, and the like. The memory 20 may in some embodiments be an internal storage unit of the control device on which the program runs.
The processor 21 may be a Central Processing Unit (CPU), a controller, a microcontroller, a microprocessor or other data Processing chip in some embodiments, and is used to execute program codes stored in the memory 20 or process data, such as a program corresponding to a control method for executing program operations.
In some embodiments, the bus 22 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 8, but this is not intended to represent only one bus or type of bus.
Those skilled in the art will appreciate that the configuration shown in fig. 8 does not constitute a limitation of a cloud game acceleration apparatus based on fog calculations, and may include more or fewer components than those shown.
The cloud game accelerating device based on fog calculation comprises a memory and a processor, wherein when the processor executes a program stored in the memory, the following method can be realized: the method comprises the steps of obtaining the corresponding relation between relevant data related to historical cloud games and a data processing scheme in advance, determining the target data processing scheme according to the corresponding relation when obtaining current fog computing resources and target client operation data, wherein the target data processing scheme comprises fog computing nodes, and because the fog computing nodes are closer to the edge side where the cloud game client is located, a large amount of bandwidth is not needed in data transmission, the data downlink speed is increased, the transmission rate of the cloud games is greatly increased, and the game experience of players is improved.
Finally, the application also provides a corresponding embodiment of the computer readable storage medium. The computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps as set forth in the above-mentioned method embodiments.
It is to be understood that if the method in the above embodiments is implemented in the form of software functional units and sold or used as a stand-alone product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium and executes all or part of the steps of the methods described in the embodiments of the present application, or all or part of the technical solutions. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The cloud game acceleration method, system, device and medium based on fog calculation provided by the present application are described in detail above. The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (10)
1. A cloud game acceleration method based on fog calculation is characterized by comprising the following steps:
acquiring a corresponding relation between related data related to historical cloud games and a data processing scheme, wherein the related data comprises fog computing resources and client operation data, the data processing scheme comprises objects participating in processing the cloud game data and a data processing method, and the objects participating in processing the cloud game data at least comprise fog computing nodes;
acquiring current fog computing resources and target client operating data;
and determining a target data processing scheme according to the corresponding relation so that the fog computing node can perform corresponding data processing.
2. The fog-computing-based cloud game acceleration method of claim 1, wherein the fog computing resources specifically include geographic location distribution, operational status, and log data of the fog computing nodes;
the client operation data specifically comprises log data of a cloud game client, and position data and network conditions of terminal equipment where the cloud game client is located.
3. The fog-computing-based cloud game acceleration method of claim 1, wherein the objects involved in processing cloud game data specifically comprise cloud servers and fog computing nodes;
the data processing method specifically comprises the following steps:
the cloud server acquires cloud game data and an operation instruction generated by user operation;
the cloud server carries out image rendering on the cloud game data according to the operation instruction to obtain a game video;
the cloud server encodes the game video;
the cloud server sends the coded game video to a fog computing node;
and the fog computing node sends the coded game video to target terminal equipment.
4. The cloud game acceleration method based on fog calculations of claim 1, wherein the objects involved in processing cloud game data specifically comprise fog calculation nodes;
the data processing method specifically comprises the following steps:
the cloud computing node acquires cloud game data and an operation instruction generated by user operation;
the cloud computing node performs image rendering on the cloud game data according to the operation instruction to obtain a game video;
the fog computing node encodes the game video;
and the fog computing node sends the coded game video to the target terminal equipment.
5. The cloud game acceleration method based on fog calculations of claim 1, wherein the objects involved in processing cloud game data specifically comprise fog calculation nodes;
the data processing method specifically comprises the following steps:
the cloud computing node acquires cloud game data and an operation instruction generated by user operation;
the cloud computing node performs image rendering on the cloud game data according to the operation instruction to obtain a game video;
and the fog computing node sends the game video to target terminal equipment.
6. The cloud game acceleration method based on fog calculations of claim 1, wherein the objects involved in processing cloud game data specifically comprise fog calculation nodes;
the data processing method specifically comprises the following steps:
the method comprises the steps that a first fog computing node obtains cloud game data and an operation instruction generated by user operation;
the first fog computing node performs image rendering on the cloud game data according to the operation instruction to obtain a game video;
the first fog computing node sends the game video to a second fog computing node;
the second fog computing node sends the game video to target terminal equipment;
the first fog computer node is a node with the most residual computing resources, and the second fog computer node is a node with the most residual transmission resources.
7. A cloud game acceleration system based on fog computing, comprising: a cloud server and a fog computing node;
the cloud server is used for acquiring the corresponding relation between related data related to historical cloud games and a data processing scheme and acquiring current cloud computing resources and target client operating data; determining a target data processing scheme according to the corresponding relation so that the fog computing node can perform corresponding data processing; the relevant data comprises fog computing resources and client operation data, the data processing scheme comprises objects participating in processing cloud game data and a data processing method, and the objects participating in processing the cloud game data at least comprise fog computing nodes;
and the fog computing node is in communication connection with the cloud server through a network and is used for carrying out corresponding data processing according to the data processing scheme.
8. A cloud game acceleration apparatus based on fog computing, comprising:
the cloud game processing system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring the corresponding relation between related data related to historical cloud games and a data processing scheme, the related data comprises fog computing resources and client operation data, the data processing scheme comprises objects participating in processing the cloud game data and a data processing method, and the objects participating in processing the cloud game data at least comprise fog computing nodes;
the second acquisition module is used for acquiring the current fog computing resource and the target client operating data;
and the determining module is used for determining a target data processing scheme according to the corresponding relation so as to facilitate the fog computing node to perform corresponding data processing.
9. A cloud gaming acceleration apparatus based on fog calculations, comprising a memory for storing a computer program;
a processor for implementing the steps of the fog-computing based cloud game acceleration method of any of claims 1 to 6 when executing said computer program.
10. A computer-readable storage medium, having stored thereon a computer program which, when executed by a processor, carries out the steps of the fog-computing-based cloud game acceleration method according to any one of claims 1 to 6.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114401427A (en) * | 2021-12-28 | 2022-04-26 | 深圳志趣互娱科技有限公司 | Streaming media data transmission system and method for cloud game |
| WO2022247514A1 (en) * | 2021-05-27 | 2022-12-01 | 腾讯科技（深圳）有限公司 | Game data processing method, apparatus, and system, electronic device, and storage medium |
| CN116347608A (en) * | 2023-04-19 | 2023-06-27 | 湖南科技学院 | Time division resource self-adaptive adjustment method |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060143675A1 (en) * | 2004-12-17 | 2006-06-29 | Daniel Willis | Proxy advertisement server and method |
| US20080039205A1 (en) * | 2006-08-11 | 2008-02-14 | Jonathan Ackley | Method and/or system for mobile interactive gaming |
| CN102571900A (en) * | 2010-12-08 | 2012-07-11 | 中国电信股份有限公司 | System and method for implementing far-end real-time control |
| CN104093046A (en) * | 2013-04-01 | 2014-10-08 | 云联（北京）信息技术有限公司 | Video inserting system and method based on cloud game |
| CN106621326A (en) * | 2015-08-19 | 2017-05-10 | 索尼互动娱乐美国有限责任公司 | Local application quick start with cloud transitioning |
| WO2017100640A1 (en) * | 2015-12-11 | 2017-06-15 | Interdigital Patent Holdings, Inc. | Method and apparatus for enabling third party edge clouds at the mobile edge |
| CN107243156A (en) * | 2017-06-30 | 2017-10-13 | 珠海金山网络游戏科技有限公司 | A kind of large-scale distributed network game server system |
| CN107995171A (en) * | 2017-11-22 | 2018-05-04 | 贵州力创科技发展有限公司 | A kind of online game accelerated method and system |
| CN108355350A (en) * | 2018-02-11 | 2018-08-03 | 清华大学 | A kind of application service cut-in method and device based on mobile edge calculations |
| CN108499100A (en) * | 2018-03-30 | 2018-09-07 | 南京工业大学 | Cloud game error recovery method and system based on edge calculation |
| CN108815842A (en) * | 2018-06-01 | 2018-11-16 | 网宿科技股份有限公司 | A kind of method, apparatus and system running cloud game |
| CN108837505A (en) * | 2018-06-14 | 2018-11-20 | 北京金山安全软件有限公司 | Network game data transmission method and system |
| CN109460297A (en) * | 2018-11-01 | 2019-03-12 | 中山大学 | A kind of edge cloud game caching and resource regulating method |
| CN110392079A (en) * | 2018-04-20 | 2019-10-29 | 上海无线通信研究中心 | The node calculating task dispatching method and its equipment calculated towards mist |
-
2020
- 2020-06-29 CN CN202010605993.0A patent/CN111773662B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060143675A1 (en) * | 2004-12-17 | 2006-06-29 | Daniel Willis | Proxy advertisement server and method |
| US20080039205A1 (en) * | 2006-08-11 | 2008-02-14 | Jonathan Ackley | Method and/or system for mobile interactive gaming |
| CN102571900A (en) * | 2010-12-08 | 2012-07-11 | 中国电信股份有限公司 | System and method for implementing far-end real-time control |
| CN104093046A (en) * | 2013-04-01 | 2014-10-08 | 云联（北京）信息技术有限公司 | Video inserting system and method based on cloud game |
| CN106621326A (en) * | 2015-08-19 | 2017-05-10 | 索尼互动娱乐美国有限责任公司 | Local application quick start with cloud transitioning |
| WO2017100640A1 (en) * | 2015-12-11 | 2017-06-15 | Interdigital Patent Holdings, Inc. | Method and apparatus for enabling third party edge clouds at the mobile edge |
| CN107243156A (en) * | 2017-06-30 | 2017-10-13 | 珠海金山网络游戏科技有限公司 | A kind of large-scale distributed network game server system |
| CN107995171A (en) * | 2017-11-22 | 2018-05-04 | 贵州力创科技发展有限公司 | A kind of online game accelerated method and system |
| CN108355350A (en) * | 2018-02-11 | 2018-08-03 | 清华大学 | A kind of application service cut-in method and device based on mobile edge calculations |
| CN108499100A (en) * | 2018-03-30 | 2018-09-07 | 南京工业大学 | Cloud game error recovery method and system based on edge calculation |
| CN110392079A (en) * | 2018-04-20 | 2019-10-29 | 上海无线通信研究中心 | The node calculating task dispatching method and its equipment calculated towards mist |
| CN108815842A (en) * | 2018-06-01 | 2018-11-16 | 网宿科技股份有限公司 | A kind of method, apparatus and system running cloud game |
| CN108837505A (en) * | 2018-06-14 | 2018-11-20 | 北京金山安全软件有限公司 | Network game data transmission method and system |
| CN109460297A (en) * | 2018-11-01 | 2019-03-12 | 中山大学 | A kind of edge cloud game caching and resource regulating method |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022247514A1 (en) * | 2021-05-27 | 2022-12-01 | 腾讯科技（深圳）有限公司 | Game data processing method, apparatus, and system, electronic device, and storage medium |
| CN114401427A (en) * | 2021-12-28 | 2022-04-26 | 深圳志趣互娱科技有限公司 | Streaming media data transmission system and method for cloud game |
| CN114401427B (en) * | 2021-12-28 | 2024-10-01 | 深圳志趣互娱科技有限公司 | Streaming media data transmission system and method for cloud game |
| CN116347608A (en) * | 2023-04-19 | 2023-06-27 | 湖南科技学院 | Time division resource self-adaptive adjustment method |
| CN116347608B (en) * | 2023-04-19 | 2024-03-15 | 湖南科技学院 | Time division resource self-adaptive adjustment method |
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|---|---|
| CN111773662B (en) | 2024-08-06 |
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