CN115604266B - Edge service terminal based on cloud edge collaborative intelligent allocation computing power - Google Patents
Edge service terminal based on cloud edge collaborative intelligent allocation computing power Download PDFInfo
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Abstract
The invention provides an edge service terminal for intelligently distributing computing power based on cloud edge cooperation. The terminal acquires the equipment data volume and the terminal data volume through an acquisition module; the calculation module calculates a demand calculation force value according to the equipment data volume and calculates an edge idle calculation force value according to the terminal data volume; the judging module judges the force calculating state of the edge service terminal according to the demand force calculating value and the edge idle force calculating value; the first processing module judges the computing power state of the edge service terminal according to the demand computing power value and the edge idle computing power value, judges the computing power state of the cloud server according to the cloud idle computing power value and the cloud total computing power value, and judges whether to split the edge computing task according to the computing power state of the cloud server; the second processing module obtains an edge residual computing force value of the edge service terminal, judges a residual computing force state of the edge service terminal according to the edge residual computing force value, judges whether to obtain a cloud computing task or not according to the residual computing force state of the edge service terminal, and improves the operation efficiency of the edge computing platform.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an edge service terminal for intelligently distributing computing power based on cloud edge cooperation.
Background
Edge computing means that an open platform integrating network, computing, storage and application core capabilities is adopted on one side close to an object or a data source to provide nearest-end services nearby. The application program is initiated at the edge side to generate faster network service response, so that the basic requirements of the industry on real-time business, application intelligence, safety, privacy protection and the like are met, and edge computing is positioned between a physical entity and industrial connection or at the top end of the physical entity.
Patent document CN111507650B discloses a method and a system for computing power allocation scheduling of an edge computing platform, which includes: sampling a service calculation power consumption peak value; evaluating the service computing power demand level according to the sampled computing power consumption peak value; and performing calculation power distribution scheduling according to the calculation power demand level.
In the prior art, a business computing power consumption peak value is sampled, a business computing power demand level is evaluated according to the sampled computing power consumption peak value, and finally computing power distribution scheduling is performed according to the computing power demand level, but the computing power distribution scheduling only occurs on an edge computing platform, the computing power of the edge computing platform is limited, and the distribution of computing tasks with different computing power demands is difficult, so that the operation efficiency of the edge computing platform is low.
Disclosure of Invention
Therefore, the invention provides an edge service terminal for intelligently distributing computing power based on cloud edge cooperation, which can solve the problem of low operation efficiency of an edge computing platform.
In order to achieve the above object, the present invention provides an edge service terminal for intelligently allocating computing power based on cloud edge collaboration, the service terminal comprising:
the system comprises an acquisition module, a data processing module and a data processing module, wherein the acquisition module is connected with at least one physical device and used for acquiring the device data volume of the physical device and generating an edge operation task, and the acquisition module is also used for acquiring the terminal data volume of an edge service terminal;
the calculation module is connected with the acquisition module and used for calculating a required calculation force value of the edge calculation task according to the equipment data volume and calculating an edge idle calculation force value of the edge service terminal according to the terminal data volume;
the judging module is connected with the calculating module and used for judging the force calculating state of the edge service terminal according to the relation between the demand force calculating value and the edge idle force calculating value, and the force calculating state of the edge service terminal comprises a first edge force calculating state and a second edge force calculating state;
the first processing module is connected with the judging module and at least one cloud server and used for acquiring a cloud idle calculation force value of the cloud server when the calculation force state of the edge service terminal is a first edge calculation force state, judging the calculation force state of the cloud server according to the relation between the cloud idle calculation force value and a cloud total calculation force value, judging whether the edge calculation task is split or not according to the calculation force state of the cloud server by the first processing module and obtaining a sub-edge calculation task, and sending the sub-edge calculation task to the cloud server for calculation and receiving a calculation result by the first processing module;
the second processing module is connected with the judging module and the at least one cloud server and used for acquiring the edge residual force value of the edge service terminal when the force calculation state of the edge service terminal is a second edge force calculation state and judging the residual force calculation state of the edge service terminal according to the edge residual force value, and the second processing module is used for judging whether to acquire a cloud computing task and send a computing result according to the residual force calculation state of the edge service terminal.
Further, the judging module judges the force calculation state of the edge service terminal according to the relation between the demand force calculation value H0 and the edge idle force calculation value H1,
if H0 is larger than or equal to H1, the judging module judges that the force calculation state of the edge service terminal is a first edge force calculation state;
and if the H0 is less than the H1, the judging module judges that the computing power state of the edge service terminal is a second edge computing power state.
Further, the first processing module comprises a first determination unit, the first determination unit is configured to determine the computing power state of the cloud server according to a relationship between the cloud idle computing power value Y0 and a cloud total computing power value Y1 when the computing power state of the edge service terminal is a first edge computing power state, Y0 is the number of idle computing power nodes of the cloud server, and Y1 is the number of total computing power nodes of the cloud server;
if Y0 is less than 0.6 multiplied by Y1, the first judging unit judges that the computing power state of the cloud server is a first cloud computing power state;
and if the Y0 is more than or equal to 0.6 multiplied by Y1, the first judging unit judges that the computing power state of the cloud server is the second cloud computing power state.
Further, the first processing module further comprises a second determination unit, connected to the first determination unit, for determining whether to split the edge calculation task according to the computing power status of the cloud server,
if the computing power state of the cloud server is the first cloud computing power state, the second determination unit determines not to split the edge computing task;
and if the computing power state of the cloud server is a second cloud computing power state, the second judgment unit judges that the edge computing task is split.
Further, the first processing module further includes a splitting unit, connected to the second determining unit, for splitting the edge calculation task according to the edge idle calculation value H1, splitting the edge calculation task into a first sub-edge task and a second sub-edge task,
the demand calculation force value H1= H1 of the first sub-edge task;
the demand calculation force value H2= H0-H1 of the second sub-edge task.
Further, the second processing module includes a third determining unit, which is connected to the second obtaining unit and configured to determine the remaining power calculation state of the edge service terminal according to a relationship between the edge remaining power calculation value Hs and the edge total power calculation value Hz when the power calculation state of the edge service terminal is the second edge power calculation state,
if Hs is less than 0.3 multiplied by Hz, the third judging unit judges that the residual computing power state of the edge service terminal is a first residual computing power state;
if Hs is more than or equal to 0.3 multiplied by Hz and less than Hz, the third judging unit judges that the residual computing power state of the edge service terminal is a second residual computing power state.
Further, the second processing module further comprises a fourth determination unit, which is connected to the third determination unit and is configured to determine whether to acquire a cloud computing task according to the remaining computing power state of the edge service terminal,
if the residual computing power state of the edge service terminal is the first residual computing power state, the fourth judging unit judges that the cloud computing task is not acquired;
and if the residual computing power state of the edge service terminal is a second residual computing power state, the fourth judging unit judges to acquire the cloud computing task.
Further, the calculation module is provided with a first formula H0= D0/D1, where D0 is the device data volume of the physical device, and D1 is the data volume of the maximum processing data of each computation power node of the edge service terminal;
the calculation module is further provided with a second formula H1= C0/C1, wherein C0 is an idle calculation power node of the edge service terminal, and C1 is a total calculation power node of the edge service terminal.
Further, the first processing module is further provided with a first obtaining unit, the obtaining unit is connected with the cloud server and used for obtaining the cloud idle computation force value of the cloud server, the first obtaining unit is provided with a third formula Y0= E0/E1, E0 is an idle computation force node of the cloud server, and E1 is a total computation force node of the cloud server.
Further, the second processing module is further provided with a second obtaining unit for obtaining the edge remaining computation force value of the edge service terminal, the second obtaining unit is provided with a fourth formula Hs = H1-H0, H0 is a demand computation force value, and H1 is an edge idle computation force value.
Compared with the prior art, the method has the advantages that the device data volume of the physical device is collected through the collection module to generate the edge operation task, and the collection module also collects the terminal data volume of the edge service terminal; the calculation module calculates a required calculation force value of the edge calculation task and calculates an edge idle calculation force value of the edge service terminal according to the terminal data amount of the edge service terminal; the first processing module judges the computing power state of the edge service terminal according to the relation between the required computing power value and the edge idle computing power value, acquires a cloud idle computing power value of a cloud server, judges the computing power state of the cloud server according to the relation between the cloud idle computing power value and a cloud total computing power value, judges whether the edge computing task is split or not according to the computing power state of the cloud server, obtains a sub-edge computing task, sends the sub-edge computing task to the cloud server for computing and receives a computing result; or the second processing module acquires an edge residual force value of the edge service terminal and judges the residual force state of the edge service terminal according to the edge residual force value, and the second processing module judges whether to acquire a cloud computing task and sends a computing result according to the residual force state of the edge service terminal. The method has the advantages that the collection of the edge computing tasks and the computation of the required computing power are realized, the computing power distribution of the cloud server is adopted to improve the computing efficiency of the edge computing tasks, the cloud computing tasks in the cloud server are acquired, the computing power of the edge service terminal is fully utilized, and the operating efficiency of the edge computing platform is improved.
Particularly, the calculation force state of the edge service terminal is judged according to the relation between the demand calculation force value and the edge idle calculation force value through a judging module; the method comprises the steps that a first obtaining unit obtains a cloud idle calculation force value of a cloud server; the first judging unit judges the computing power state of the cloud server according to the relation between the cloud idle computing power value and the cloud total computing power value, judges the computing power state of the edge service terminal, judges the occupation of the edge computing task on the edge service terminal, acquires the cloud idle computing power value of the cloud server, judges the computing power state of the cloud server, and prepares for sending the edge computing task to the cloud server subsequently.
Particularly, the calculation force state of the edge service terminal is judged according to the relation between the required calculation force value and the edge idle calculation force value through the judging module, and the idle calculation force value of the edge service terminal is compared with the required calculation force value of the edge calculation task, so that the calculation force state of the edge service terminal is judged more accurately to the maximum extent, and the calculation force judgment accuracy of the calculation force state of the edge service terminal is improved.
Particularly, the computing power state of the cloud server is judged through the first judging unit according to the relation between the cloud idle computing power value and the cloud total computing power value, so that the cloud idle state of the cloud server is judged, and preparation is made for computing power distribution of subsequent edge computing tasks.
Particularly, the invention judges whether the edge operation task is split or not according to the computing power state of the cloud server by a second judging unit; the splitting unit splits the edge operation task according to the edge idle calculation force value to obtain a first sub-edge operation task and a second sub-edge operation task, splits the edge operation task, calculates the split operation task by using the calculation force of the cloud server under the condition that the edge service terminal is ensured to normally operate, and improves the processing efficiency of the edge operation task.
Particularly, the invention judges whether the edge operation task is split or not according to the computing power state of the cloud server through the second judging unit, determines the maximum continuous operation edge operation task according to the state of the edge operation task after judging the computing power state of the cloud server, and sends an operation result, thereby realizing the efficient utilization of the cloud server and improving the operation efficiency of the edge service terminal.
Particularly, the edge operation task is split by the splitting unit according to the edge idle calculation force value, the edge operation task is split into a first sub-edge task and a second sub-edge task, when the edge operation task demand calculation force value is larger than the edge idle calculation force of the edge service terminal, the edge operation task can be split in the mode, the split sub-edge operation task is operated through the cloud server for follow-up, the operation pressure of the edge service terminal is relieved, and the operation efficiency of the edge service terminal is improved.
Particularly, the invention obtains the edge residual force value of the edge service terminal through a second obtaining unit; a third judging unit judges the residual force calculation state of the edge service terminal according to the edge residual force calculation value; a fourth judging unit judges whether to acquire a cloud computing task according to the residual computing power state of the edge service terminal; the third acquisition unit acquires the cloud computing task, so that the cloud computing task is processed when idle computing power exists in the edge service terminal, and the operation efficiency of the edge service terminal is improved.
Particularly, the invention obtains the edge residual force value of the edge service terminal through a second obtaining unit; a third judging unit judges the residual force calculation state of the edge service terminal according to the edge residual force calculation value; a fourth judging unit judges whether to acquire a cloud computing task according to the residual computing power state of the edge service terminal; the third acquisition unit acquires the cloud computing task, so that the cloud computing task is processed when the edge service terminal has idle computing power, and the operation efficiency of the edge service terminal is improved.
Particularly, the invention judges the residual computing power state of the edge service terminal according to the relationship between the edge residual computing power value and the edge total computing power value through the third judging unit, realizes the operation of the edge service terminal on the cloud operation task in the cloud server by using the self computing power to the maximum extent through the judgment of the residual computing power state of the edge service terminal, operates the cloud operation task in the cloud server under the condition of ensuring the normal operation of the self operation of the edge service terminal, and improves the synergistic action between the edge service terminal and the cloud server.
Drawings
Fig. 1 is a schematic structural diagram of an edge service terminal for intelligently allocating computing power based on cloud edge collaboration according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a first processing module of an edge service terminal for intelligently allocating computing power based on cloud edge collaboration according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a second processing module of the edge service terminal based on cloud-edge cooperative intelligent allocation of computing power according to the embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described below with reference to examples; it should be understood that the specific embodiments described herein are merely illustrative of the invention and do not delimit the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principle of the present invention, and are not within the scope of the present invention.
It should be noted that in the description of the present invention, the terms of direction or positional relationship indicated by the terms "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, which are only for convenience of description, and do not indicate or imply that the device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, cannot be understood as an idle of the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Referring to fig. 1, the present invention provides an edge service terminal for intelligently allocating computing power based on cloud edge collaboration, including:
the system comprises an acquisition module 100, a service module and a service module, wherein the acquisition module 100 is connected with at least one physical device and is used for acquiring the device data volume of the physical device and generating an edge operation task, and the acquisition module also acquires the terminal data volume of an edge service terminal;
the calculation module 200 is connected to the acquisition module 100, and is configured to calculate a required computation force value of the edge computation task according to the device data amount and calculate an edge idle computation force value of the edge service terminal according to the terminal data amount;
the judging module 300 is respectively connected with the collecting module 100, the computing module 200 and the at least one cloud server, and is configured to judge the force calculation state of the edge service terminal according to the relationship between the required force calculation value and the edge idle force calculation value, where the force calculation state of the edge service terminal includes a first edge force calculation state and a second edge force calculation state;
the first processing module 400 is connected to the determining module 300, and is configured to obtain a cloud idle computation force value of a cloud server when the computation force state of the edge service terminal is a first edge computation force state, determine the computation force state of the cloud server according to a relationship between the cloud idle computation force value and a cloud total computation force value, determine whether to split the edge computation task and obtain a sub-edge computation task according to the computation force state of the cloud server, and send the sub-edge computation task to the cloud server for computation and receive a computation result;
the second processing module 500 is connected to the determining module 300, and is configured to obtain an edge remaining computation force value of the edge service terminal when the computation force state of the edge service terminal is a second edge computation force state, and determine the remaining computation force state of the edge service terminal according to the edge remaining computation force value, and the second processing module is configured to determine whether to obtain a cloud computation task and send a computation result according to the remaining computation force state of the edge service terminal.
Specifically, in the embodiment of the present invention, an acquisition module acquires the device data volume of the physical device to generate an edge calculation task, and the acquisition module further acquires the terminal data volume of an edge service terminal; the calculation module calculates a required calculation force value of the edge calculation task according to the equipment data volume and calculates an edge idle calculation force value of the edge service terminal according to the terminal data volume; the judging module judges the force calculation state of the edge service terminal according to the relation between the demand force calculation value and the edge idle force calculation value, wherein the force calculation state of the edge service terminal comprises a first edge force calculation state and a second edge force calculation state; the method comprises the steps that a first processing module obtains a cloud idle calculation force value of a cloud server when the calculation force state of an edge service terminal is a first edge calculation force state, the calculation force state of the cloud server is judged according to the relation between the cloud idle calculation force value and a cloud total calculation force value, the first processing module judges whether an edge calculation task is split or not according to the calculation force state of the cloud server, a sub-edge calculation task is obtained, the first processing module sends the sub-edge calculation task to the cloud server for calculation, and receives a calculation result; the second processing module is used for obtaining the edge residual force value of the edge service terminal when the force calculation state of the edge service terminal is the second edge force calculation state, judging the residual force calculation state of the edge service terminal according to the edge residual force value, and judging whether to obtain a cloud computing task and send a computing result according to the residual force calculation state of the edge service terminal. The method has the advantages that the acquisition of the edge computing tasks and the computation of the required computing power are realized, the computing power distribution of the cloud server is adopted to improve the computing efficiency of the edge computing tasks, the computing power of the edge service terminal is fully utilized by acquiring the cloud computing tasks in the cloud server, and the operating efficiency of the edge computing platform is improved.
Specifically, when the determining module determines the force calculation state of the edge service terminal according to the relationship between the demand force calculation value H0 and the edge idle force calculation value H1,
if H0 is larger than or equal to H1, the judging module judges that the force calculation state of the edge service terminal is a first edge force calculation state;
and if H0 is less than H1, the judging module judges that the force calculation state of the edge service terminal is a second edge force calculation state.
Specifically, the calculation force state of the edge service terminal is judged according to the relation between the required calculation force value and the edge idle calculation force value through the judging module, the idle calculation force value of the edge service terminal is compared with the required calculation force value of the edge calculation task, the calculation force state of the edge service terminal is judged more accurately to the maximum extent, and the calculation force judging accuracy of the calculation force state of the edge service terminal is improved.
Specifically, referring to fig. 2, the first processing module 400 includes a first obtaining unit 410 and a first determining unit 420;
the first acquisition unit is used for acquiring a cloud idle calculation force value of the cloud server;
the first judging unit is connected with the first acquiring unit and used for judging the computing power state of the cloud server according to the relation between the cloud idle computing power value and the cloud total computing power value.
Specifically, the cloud idle calculation force value of the cloud server is obtained through a first obtaining unit; the first judging unit judges the computing power state of the cloud server according to the relation between the cloud idle computing power value and the cloud total computing power value, judges the computing power state of the edge service terminal, judges the occupation of the edge computing task on the edge service terminal, acquires the cloud idle computing power value of the cloud server, judges the computing power state of the cloud server, and prepares for sending the edge computing task to the cloud server subsequently.
Specifically, when the computing power state of the edge service terminal is a first edge computing power state, the first judging unit judges the computing power state of the cloud server according to the relation between the cloud idle computing power value Y0 and the cloud total computing power value Y1, wherein Y0 is the number of idle computing power nodes of the cloud server, and Y1 is the number of total computing power nodes of the cloud server;
if Y0 is less than 0.6 multiplied by Y1, the first judging unit judges that the computing power state of the cloud server is a first cloud computing power state;
and if the Y0 is more than or equal to 0.6 multiplied by Y1, the first judging unit judges that the computing power state of the cloud server is the second cloud computing power state.
Specifically, the computing power state of the cloud server is judged through the first judging unit according to the relation between the cloud idle computing power value and the cloud total computing power value, so that the cloud idle state of the cloud server is judged, and preparation is made for computing power distribution of subsequent edge computing tasks.
Specifically, the first processing module 400 further includes a second determining unit 430 and a splitting unit 440;
the second judging unit is connected with the first judging unit and used for judging whether the edge computing task is split or not according to the computing power state of the cloud server;
the splitting unit is connected with the second judging unit and is used for splitting the edge operation task according to the edge idle operation value to obtain a first sub-edge operation task and a second sub-edge operation task.
Specifically, according to the embodiment of the invention, a second determination unit determines whether to split the edge calculation task according to the calculation power state of the cloud server; the splitting unit splits the edge operation task according to the edge idle calculation force value to obtain a first sub-edge operation task and a second sub-edge operation task, splits the edge operation task, calculates the split operation task by using the calculation force of the cloud server under the condition that the edge service terminal is ensured to normally operate, and improves the processing efficiency of the edge operation task.
Specifically, when the second determination unit is used to determine whether to split the edge calculation task according to the computing power state of the cloud server,
if the computing power state of the cloud server is the first cloud computing power state, the second determination unit determines not to split the edge computing task;
and if the computing power state of the cloud server is a second cloud computing power state, the second judgment unit judges that the edge computing task is split.
Specifically, according to the embodiment of the invention, the second determination unit determines whether the edge operation task is split according to the computing power state of the cloud server, determines the maximum edge operation task to be continuously operated according to the state of the edge operation task after the computing power state of the cloud server is determined, and sends the operation result, so that the efficient utilization of the cloud server is realized, and the operation efficiency of the edge service terminal is improved.
Specifically, the splitting unit splits the edge calculation task into a first sub-edge task and a second sub-edge task when the edge calculation task is split according to the edge idle calculation value H1,
the demand calculation force value H1= H1 of the first sub-edge task;
the demand calculation force value H2= H0-H1 of the second sub-edge task.
Specifically, according to the embodiment of the invention, the edge operation task is split by the splitting unit according to the edge idle calculation force value, the edge operation task is split into the first sub-edge task and the second sub-edge task, when the edge operation task demand calculation force value is greater than the edge idle calculation force of the edge service terminal, the edge operation task is split in this way, the split sub-edge operation task is subsequently operated by the cloud server, the operation pressure of the edge service terminal is relieved, and the operation efficiency of the edge service terminal is improved.
Specifically, referring to fig. 3, the second processing module 500 includes a second obtaining unit 510, a third determining unit 520, a fourth determining unit 530 and a third obtaining unit 540;
the second obtaining unit is used for obtaining an edge residual force value of the edge service terminal;
the third judging unit is connected with the second acquiring unit and used for judging the residual force calculation state of the edge service terminal according to the edge residual force calculation value;
the fourth judging unit is used for judging whether to acquire a cloud computing task according to the residual computing power state of the edge service terminal;
the third obtaining unit is used for obtaining the cloud computing task.
Specifically, in the embodiment of the present invention, a second obtaining unit obtains an edge remaining force value of the edge service terminal; a third judging unit judges the residual computing power state of the edge service terminal according to the edge residual computing power value; a fourth judging unit judges whether to acquire a cloud computing task according to the residual computing power state of the edge service terminal; the third acquisition unit acquires the cloud computing task, so that the cloud computing task is processed when idle computing power exists in the edge service terminal, and the operation efficiency of the edge service terminal is improved.
Specifically, when the computation power state of the edge service terminal is a second edge computation power state, the third determination unit determines the remaining computation power state of the edge service terminal according to the relationship between the edge remaining computation power Hs and the edge total computation power Hz,
if Hs is less than 0.3 multiplied by Hz, the third judging unit judges that the residual computing power state of the edge service terminal is a first residual computing power state;
if Hs is more than or equal to 0.3 multiplied by Hz and less than Hz, the third judging unit judges that the residual computing power state of the edge service terminal is a second residual computing power state.
Specifically, the residual computing force state of the edge service terminal is judged according to the relationship between the edge residual computing force value and the edge total computing force value through the third judging unit, the cloud computing task in the cloud server is operated by using the self computing force of the edge service terminal to the maximum extent through the judgment of the residual computing force state of the edge service terminal, the cloud computing task in the cloud server is operated under the condition that the normal operation of the edge service terminal is ensured, and the synergistic effect between the edge service terminal and the cloud server is improved.
Specifically, when the fourth determination unit determines whether to acquire the cloud computing task according to the remaining computing power state of the edge service terminal,
if the residual computing power state of the edge service terminal is the first residual computing power state, the fourth judging unit judges that the cloud computing task is not acquired;
and if the residual computing power state of the edge service terminal is a second residual computing power state, the fourth judging unit judges to acquire the cloud computing task.
Specifically, the fourth determination unit determines whether to acquire the cloud computing task according to the residual computing power state of the edge service terminal, so that the determination on the residual computing power state of the edge service terminal is realized, whether to acquire the cloud computing task is determined on the premise that the operation of the edge service terminal is guaranteed preferentially, meanwhile, the pressure is shared by the cloud computing task, and the synergy of cloud edge collaboration is improved.
Specifically, the calculation module is provided with a first formula H0= D0/D1, where D0 is the device data size of the physical device, and D1 is the data size of the maximum processing data of each computation power node of the edge service terminal;
the calculation module is further provided with a second formula H1= C0/C1, wherein C0 is an idle calculation power node of the edge service terminal, and C1 is a total calculation power node of the edge service terminal.
Specifically, the first obtaining unit is provided with a third formula Y0= E0/E1, where E0 is an idle computing power node of the cloud server, and E1 is a total computing power node of the cloud server.
Specifically, the second obtaining unit is provided with a fourth formula Hs = H1-H0, H0 is a demand force calculation value, and H1 is an edge idle force calculation value.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention; various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The utility model provides an edge service terminal based on calculation power is joined in marriage to cloud limit intelligence, its characterized in that includes:
the system comprises an acquisition module, a data processing module and a data processing module, wherein the acquisition module is connected with at least one physical device and used for acquiring the device data volume of the physical device and generating an edge operation task, and the acquisition module is also used for acquiring the terminal data volume of an edge service terminal;
the calculation module is connected with the acquisition module and used for calculating a required calculation force value of the edge calculation task according to the equipment data volume and calculating an edge idle calculation force value of the edge service terminal according to the terminal data volume;
the judging module is connected with the calculating module and used for judging the force calculation state of the edge service terminal according to the relation between the demand force calculation value and the edge idle force calculation value, and the force calculation state of the edge service terminal comprises a first edge force calculation state and a second edge force calculation state;
the first processing module is connected with the judging module and at least one cloud server and used for acquiring a cloud idle calculation force value of the cloud server when the calculation force state of the edge service terminal is a first edge calculation force state, judging the calculation force state of the cloud server according to the relation between the cloud idle calculation force value and a cloud total calculation force value, judging whether the edge calculation task is split or not according to the calculation force state of the cloud server by the first processing module and obtaining a sub-edge calculation task, and sending the sub-edge calculation task to the cloud server for calculation and receiving a calculation result by the first processing module;
the second processing module is connected with the judging module and the at least one cloud server and used for acquiring the edge residual force value of the edge service terminal when the force calculation state of the edge service terminal is a second edge force calculation state and judging the residual force calculation state of the edge service terminal according to the edge residual force value, and the second processing module is used for judging whether to acquire a cloud computing task and send a computing result according to the residual force calculation state of the edge service terminal.
2. The edge service terminal for distributing computing power based on cloud edge collaboration intelligence as claimed in claim 1, wherein the determining module determines the computing power state of the edge service terminal according to the relation between the demand computing power value H0 and the edge idle computing power value H1,
if H0 is larger than or equal to H1, the judging module judges that the force calculation state of the edge service terminal is a first edge force calculation state;
and if H0 is less than H1, the judging module judges that the force calculation state of the edge service terminal is a second edge force calculation state.
3. The edge service terminal for intelligently distributing computing power based on cloud edge collaboration according to claim 2, wherein the first processing module comprises a first determination unit, the first determination unit is configured to determine the computing power state of the cloud server according to a relationship between the cloud idle computing power value Y0 and a cloud total computing power value Y1 when the computing power state of the edge service terminal is a first edge computing power state, Y0 is the number of idle computing power nodes of the cloud server, and Y1 is the number of total computing power nodes of the cloud server;
if Y0 is less than 0.6 multiplied by Y1, the first judging unit judges that the computing power state of the cloud server is a first cloud computing power state;
and if the Y0 is more than or equal to 0.6 multiplied by Y1, the first judging unit judges that the computing power state of the cloud server is the second cloud computing power state.
4. The edge service terminal for intelligent allocation of computing power based on cloud edge collaboration according to claim 3, wherein the first processing module further comprises a second determination unit, the second determination unit is connected to the first determination unit and is used for determining whether to split the edge computing task according to the computing power state of the cloud server,
if the computing power state of the cloud server is the first cloud computing power state, the second determination unit determines not to split the edge computing task;
and if the computing power state of the cloud server is a second cloud computing power state, the second judgment unit judges that the edge computing task is split.
5. The edge service terminal for intelligent distribution of computing power based on cloud edge collaboration according to claim 4, wherein the first processing module further includes a splitting unit, connected to the second determining unit, for splitting the edge computing task according to the edge idle computing power value H1, splitting the edge computing task into a first sub-edge task and a second sub-edge task,
the demand calculation force value H1= H1 of the first sub-edge task;
and the demand calculation force value H2= H0-H1 of the second sub-edge task.
6. The edge service terminal for intelligent allocation of computing power based on cloud edge collaboration according to claim 5, wherein the second processing module includes a third determination unit configured to determine the remaining computing power state of the edge service terminal according to a relationship between the edge remaining computing power value Hs and the edge total computing power value Hz when the computing power state of the edge service terminal is the second edge computing power state,
if Hs is less than 0.3 multiplied by Hz, the third judging unit judges that the residual computing power state of the edge service terminal is a first residual computing power state;
if Hs is more than or equal to 0.3 multiplied by Hz and less than Hz, the third judging unit judges that the residual computing power state of the edge service terminal is a second residual computing power state.
7. The edge service terminal for intelligent power distribution based on cloud edge collaboration according to claim 6, wherein the second processing module further comprises a fourth determination unit, the fourth determination unit is connected to the third determination unit, and is configured to determine whether to acquire the cloud computing task according to a remaining power state of the edge service terminal,
if the residual computing power state of the edge service terminal is the first residual computing power state, the fourth judging unit judges that the cloud computing task is not acquired;
and if the residual computing power state of the edge service terminal is a second residual computing power state, the fourth judging unit judges to acquire the cloud computing task.
8. The edge service terminal for intelligently allocating computing power based on cloud edge collaboration according to claim 7, wherein the computing module is provided with a first formula H0= D0/D1, D0 is a device data volume of the physical device, and D1 is a data volume of maximum processing data of each computing power node of the edge service terminal;
the calculation module is further provided with a second formula H1= C0/C1, wherein C0 is an idle calculation power node of the edge service terminal, and C1 is a total calculation power node of the edge service terminal.
9. The edge service terminal for intelligently allocating computing power based on cloud edge collaboration according to claim 8, wherein the first processing module is further provided with a first obtaining unit, the first obtaining unit is connected to the cloud server and used for obtaining a cloud idle computing power value of the cloud server, the first obtaining unit is provided with a third formula Y0= E0/E1, E0 is an idle computing power node of the cloud server, and E1 is a total computing power node of the cloud server.
10. The edge service terminal for intelligently distributing computing power based on cloud edge collaboration as claimed in claim 9, wherein the second processing module is further provided with a second obtaining unit for obtaining an edge remaining computing power value of the edge service terminal, the second obtaining unit is provided with a fourth formula Hs = H1-H0, H0 is a demand computing power value, and H1 is an edge idle computing power value.
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| CN115190033A (en) * | 2022-05-22 | 2022-10-14 | 重庆科技学院 | Cloud edge fusion network task unloading method based on reinforcement learning |
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| CN111475276A (en) * | 2020-05-29 | 2020-07-31 | 深圳市元征科技股份有限公司 | Task management method and device based on edge calculation |
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