CN113157446A - Cloud edge cooperative resource allocation method, device, equipment and medium - Google Patents
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Abstract
The invention discloses a resource allocation method, a device, equipment and a medium for cloud edge coordination, wherein the method comprises the following steps: the cloud side collaboration platform performs task analysis on a task of a resource to be allocated, and determines a task parameter and a minimum split subset of the resource to be allocated; determining a cloud edge coordination scheme according to the task parameters of the resources to be distributed and a task resource coordination algorithm; according to the block chain and the cloud edge coordination scheme, resource allocation is carried out on the task of the resource to be allocated; according to the invention, the resources are limited and controlled through a block chain and cloud edge cooperative scheme, all subtasks are started according to a coupling rule set logic, and finally, the total task is completed according to the aggregation of the execution results of all subtasks, so that the stability, the safety and the performance excellence of resource allocation are improved, and the method can be widely applied to the technical field of cloud edge resource computing.
Description
Technical Field
The invention relates to the technical field of cloud-edge resource computing, in particular to a cloud-edge cooperative resource allocation method, device, equipment and medium.
Background
With the continuous development of technologies such as the internet of things and the like and the continuous increase of data, the cloud-based internet of things solution can not meet the increasing demands of people gradually, more and more enterprises begin to turn the eyes to the edge cloud and use the edge cloud as the extended extension of the cloud, so that the data analysis speed is increased, and the enterprises can make decisions faster and better.
With the emergence of more and more high-bandwidth low-delay services, the scale of the edge cloud is continuously expanded. The appearance of the edge cloud enables business data of the enterprise to be processed nearby, so that the enterprise can provide faster service for customers more conveniently. However, due to the limitation of scale and resources, enterprise business cannot be completed by relying on the edge cloud alone, and usually needs to be completed by matching with the core cloud. How to realize resource cooperation, data cooperation, intelligent cooperation, application management cooperation, business management cooperation and service cooperation of the core cloud and the edge cloud becomes a problem to be solved.
Most of the current collaborative schemes for realizing the core cloud and the edge cloud are closely related to the types of tasks, the tasks are split into subtasks before deployment, and the subtasks are fixedly deployed in the core cloud or the edge cloud. Meanwhile, when the cloud-edge collaborative scheme executes the cloud-edge collaborative task, the used resources cannot be well controlled and limited, and the problems of stability, safety, excellent performance and cost of the resources used by the task are difficult to be simultaneously considered.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method, an apparatus, a device, and a medium for resource allocation in cloud-edge coordination, so as to improve stability, security, and performance superiority of resources used for tasks.
In one aspect, an embodiment of the present invention provides a resource allocation method for cloud-edge collaboration, including:
the method comprises the steps of obtaining a task of a resource to be allocated, sending the task of the resource to be allocated to a cloud-side cooperative platform, carrying out task analysis on the task of the resource to be allocated, and determining a task parameter of the resource to be allocated;
determining a cloud edge coordination scheme according to the task parameters of the resources to be distributed and a task resource coordination algorithm;
pre-allocating resources according to the cloud edge coordination scheme, and determining pre-allocated resources;
adding the pre-allocated resources into a resource locking list, and informing a cooperative platform cloud agent to lock the resources of the pre-allocated resources;
when the pre-allocated resources are successfully locked, deleting the successfully locked pre-allocated resources from the resource locking list, constructing block blocks, adding the block blocks into a block chain, and determining the block chain;
when the locking of the pre-allocated resources fails, analyzing the task execution time of the resources to be allocated, and determining that the next step of the resource allocation method of cloud-edge cooperation is finished or restarted;
and performing resource allocation on the task of the resources to be allocated according to the block chain and the cloud edge coordination scheme.
Preferably, the resource allocation for the task to be allocated with the resource according to the block chain and the cloud edge coordination scheme includes:
task auditing is carried out on the task of the resource to be distributed, and the service type, the time sensitivity index and the target client information of the task are determined;
splitting the task by combining a task splitting algorithm according to the time sensitivity index and the target client information to determine task splitting diversity;
inquiring the block chain, determining an idle resource list, and performing resource allocation on the subtasks in the task split set;
according to the logic sequence of the cloud edge cooperation scheme, starting the subtasks and determining the execution result of the subtasks;
according to the execution result of the subtasks, performing aggregation processing on the subtasks, and determining that the task of the resources to be allocated completes resource allocation;
and releasing the allocated resources according to the cloud edge coordination scheme, constructing blocks according to the states of the allocated resources, and adding the blocks into the block chain.
Preferably, the method further comprises a cloud-edge resource changing method, including the following steps:
determining the type of the change of the cloud edge resources;
if the type of the change of the cloud side resource is that a new resource is added, recording the information of the new resource into first resource record data;
if the type of the change of the cloud side resource is deleting an old resource, recording the information of the old resource into second resource recording data;
creating a block according to the first resource record data or the second resource record data, and broadcasting to the members of the block chain;
after the member of the block chain receives the broadcast, the block body is added to the block chain;
and when the type of the change of the cloud edge resource is that an old resource is deleted, deleting the old resource from the resource locking list.
Preferably, if the type of the change of the cloud-edge resource is to delete an old resource, recording information of the old resource in second resource record data includes:
adding the old resource to the resource lock list and determining a task list on the old resource from the blockchain;
determining a task set to be redistributed according to the task list and a redistribution task set algorithm;
according to the task re-allocation method, re-allocating resources for the task set to be re-allocated, adjusting the cooperative relationship among tasks, and determining that the task re-allocation is completed;
and according to the completion of the task reallocation, the task list on the old resource is empty, and the second resource record data is determined.
Preferably, the method for reallocating the tasks according to the reallocation task method, reallocating the resources for the task set to be reallocated and adjusting the cooperative relationship among the tasks to determine that the task reallocation is completed, includes:
acquiring the task set to be redistributed and the block chain;
acquiring an idle resource list from the block chain;
acquiring a task set to be redistributed according to the task set to be redistributed, and determining a first task coupling relation set of the task set to be redistributed;
according to the task coupling relation set, deploying the tasks in the task set to be redistributed to the resources in the free resource list, and determining a second task coupling relation set;
and updating the record of the related resources on the block chain according to the second task coupling relation set, and determining that the task reallocation is completed.
Preferably, the determining a cloud-edge coordination scheme according to the task parameter of the resource to be allocated and by combining a task resource coordination algorithm includes:
acquiring an idle resource list, a resource locking list and a resource locking failure list, and determining an available resource list;
according to the task parameters of the resources to be distributed, deleting unsuitable resources from the available resource table, and determining a task available resource set;
setting the parallelism and the repulsion information of the minimum subtask in the minimum task set according to the task parameters of the resources to be distributed, and determining the minimum task set;
analyzing resources in the task available resource set according to the task parameters of the resources to be allocated, allocating resources for the minimum subtask in the minimum task set, and determining an allocated resource set;
determining a configuration scheme set and a task starting set rule set according to the allocation resource set and the task coupling relation set;
and merging the allocation resource set, the configuration scheme set and the task starting set rule set to determine the cloud edge coordination scheme.
Preferably, when the locking of the pre-allocated resource fails, analyzing the task execution time of the resource to be allocated, and determining that the next step of the resource allocation method of cloud-edge coordination is to be ended or restarted includes:
recording the pre-allocated resources with locking failure into a resource locking failure list;
when the current execution time of the task of the resources to be distributed is less than the maximum time of task cooperation, re-determining the cloud-edge cooperation scheme and carrying out the next step;
or the like, or, alternatively,
and when the current execution time of the task of the resource to be allocated is greater than the maximum time of the task cooperation, performing fault analysis processing, deleting the pre-allocated resource from the resource locking list and finishing.
On the other hand, an embodiment of the present invention further provides a cloud-edge cooperative resource allocation apparatus, including:
the system comprises a first module, a second module and a third module, wherein the first module is used for acquiring a task of a resource to be allocated, sending the task of the resource to be allocated to a cloud-side cooperative platform, performing task analysis on the task of the resource to be allocated and determining a task parameter of the resource to be allocated;
the second module is used for determining a cloud edge coordination scheme according to the task parameters of the resources to be distributed and a task resource coordination algorithm;
the third module is used for pre-allocating resources according to the cloud edge coordination scheme and determining pre-allocated resources;
the fourth module is used for adding the pre-allocated resources into a resource locking list and informing a cooperative platform cloud agent of locking the resources of the pre-allocated resources;
a fifth module, configured to delete the pre-allocated resource that is successfully locked from the resource locking list, construct a block, add the block to a block chain, and determine the block chain;
a sixth module, configured to analyze the task execution time of the resource to be allocated, and determine that a next step of the resource allocation method for cloud-edge coordination is to end or restart;
a seventh module, configured to perform resource allocation on the task of the resource to be allocated according to the block chain and the cloud-edge coordination scheme.
On the other hand, the embodiment of the invention also provides an electronic device, which comprises a processor and a memory;
the memory is used for storing programs;
the processor executes the program to implement the method as described above.
In another aspect, an embodiment of the present invention further provides a computer-readable storage medium, where the storage medium stores a program, and the program is executed by a processor to implement the method described above.
The embodiment of the invention also discloses a computer program product or a computer program, which comprises computer instructions, and the computer instructions are stored in a computer readable storage medium. The computer instructions may be read by a processor of a computer device from a computer-readable storage medium, and the computer instructions executed by the processor cause the computer device to perform the foregoing method.
By adopting the technical scheme, compared with the related technology, the invention has the following technical effects: the method comprises the steps of obtaining a task of a resource to be allocated, sending the task of the resource to be allocated to a cloud-side cooperative platform, carrying out task analysis on the task of the resource to be allocated, and determining a task parameter of the resource to be allocated; the information of the tasks can be better known, so that the resources of the tasks can be better distributed; determining a cloud edge coordination scheme according to the task parameters of the resources to be distributed and a task resource coordination algorithm; stability, safety and performance excellence of the task can be considered at the same time; pre-allocating resources according to the cloud edge coordination scheme, and determining pre-allocated resources; the resource allocation can be controlled in a limited way; adding the pre-allocated resources into a resource locking list, and informing a cooperative platform cloud agent to lock the resources of the pre-allocated resources; when the pre-allocated resources are successfully locked, deleting the successfully locked pre-allocated resources from the resource locking list, constructing block blocks, adding the block blocks into a block chain, and determining the block chain; when the locking of the pre-allocated resources fails, analyzing the task execution time of the resources to be allocated, and determining that the next step of the resource allocation method of cloud-edge cooperation is finished or restarted; according to the block chain and the cloud edge coordination scheme, resource allocation is carried out on the task of the resource to be allocated; the stability, the safety and the performance excellence of the task use resources can be improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flow chart of resource allocation for cloud-edge collaboration according to an embodiment of the present invention;
FIG. 2 is a flowchart of top-level task collaborative work according to an embodiment of the present invention;
fig. 3 is a flow chart of cloud-edge resource change according to an embodiment of the present invention;
FIG. 4 is a flowchart of a re-allocation task according to an embodiment of the present invention;
FIG. 5 is a task hierarchy illustration of an embodiment of the present invention;
fig. 6 is a network topology diagram of a resource allocation method for cloud-edge coordination according to an embodiment of the present invention;
fig. 7 is a framework diagram of a resource allocation method for cloud-edge coordination according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The embodiment of the invention discloses a resource allocation method for cloud edge collaboration, which comprises the following steps:
the method comprises the steps of obtaining a task of a resource to be allocated, sending the task of the resource to be allocated to a cloud-side cooperative platform, carrying out task analysis on the task of the resource to be allocated, and determining a task parameter of the resource to be allocated;
determining a cloud edge coordination scheme according to the task parameters of the resources to be distributed and a task resource coordination algorithm;
pre-allocating resources according to the cloud edge coordination scheme, and determining pre-allocated resources;
adding the pre-allocated resources into a resource locking list, and informing a cooperative platform cloud agent to lock the resources of the pre-allocated resources;
when the pre-allocated resources are successfully locked, deleting the successfully locked pre-allocated resources from the resource locking list, constructing block blocks, adding the block blocks into a block chain, and determining the block chain;
when the locking of the pre-allocated resources fails, analyzing the task execution time of the resources to be allocated, and determining that the next step of the resource allocation method of cloud-edge cooperation is finished or restarted;
and performing resource allocation on the task of the resources to be allocated according to the block chain and the cloud edge coordination scheme.
Further as a preferred embodiment, the resource allocation for the task to be allocated with the resource according to the block chain and the cloud edge coordination scheme includes:
task auditing is carried out on the task of the resource to be distributed, and the service type, the time sensitivity index and the target client information of the task are determined;
splitting the task by combining a task splitting algorithm according to the time sensitivity index and the target client information to determine task splitting diversity;
inquiring the block chain, determining an idle resource list, and performing resource allocation on the subtasks in the task split set;
according to the logic sequence of the cloud edge cooperation scheme, starting the subtasks and determining the execution result of the subtasks;
according to the execution result of the subtasks, performing aggregation processing on the subtasks, and determining that the task of the resources to be allocated completes resource allocation;
and releasing the allocated resources according to the cloud edge coordination scheme, constructing blocks according to the states of the allocated resources, and adding the blocks into the block chain.
Referring to fig. 2 and fig. 7, the cloud-edge collaboration platform obtains a top-level task, that is, a task of the resource to be allocated, according to a northbound interface; the cloud-side collaboration platform audits the top-level task through the task analysis module, judges the service type of the top-level task, and simultaneously obtains the time sensitivity index and the target client information of the top-level task; the cloud edge collaboration platform calls a task splitting module to split the top-level task into task splitting sets; a cloud edge collaboration platform calls a block chain query module to acquire a core cloud and an idle resource list on an edge cloud from a block chain, and resource allocation is carried out on subtasks in a task split set; a task aggregation module of the cloud-edge collaboration platform starts all subtasks according to an aggregation rule set in the cloud-edge collaboration scheme, waits for the subtasks to return execution results through a collaboration platform cloud-edge agent, and aggregates all the execution results to complete a total task successfully; and a task clear module of the cloud-edge cooperation platform releases resources according to the cloud-edge cooperation scheme, and constructs a block according to the final condition of the resources and adds the block into the block chain.
Referring to fig. 5, fig. 5 is a task hierarchy explanatory diagram, and an embodiment of the present invention splits a top-level task into minimum subtasks to better utilize cloud-side resources, where a specific method is as follows; the cloud side collaboration platform calls a task splitting module to put a top-level task into a set to be split, and sets a minimum subtask set and a coupling relation set as an empty set; splitting the tasks in the set to be split into two subtasks according to the task parameters, analyzing the resource demand of the two tasks, and splitting the subtasks respectively until the set to be split is empty; forming a splitting scheme set for the two successfully split subtasks; when the resource demand of two subtasks in the splitting scheme is less than the minimum value of the resource demand limited by splitting, stopping splitting the task failed to split, and putting the subtask ID, the task information, the required computing resource, the network resource, the storage resource, the configuration requirement and the like into the minimum subtask set; the minimum value of the resource demand is a fixed value of a minimum resource set by the cloud-side collaboration platform, and comprises a minimum value of the computing resource demand, a minimum value of the network resource demand and a minimum value of the storage resource demand; selecting an optimal splitting scheme from the splitting scheme set according to the task parameters, and recording the splitting task and the split two subtasks into a coupling relation set; and calculating the estimated maximum time from the receiving of the top-level task to the completion of the starting of all the subtasks according to the minimum subtask set and the coupling relation set, and combining the maximum time, the top-level task ID, the minimum subtask set and the coupling relation set into a task splitting set.
Further, as a preferred embodiment, the method further includes a cloud-edge resource changing method, including the steps of:
determining the type of the change of the cloud edge resources;
if the type of the change of the cloud side resource is that a new resource is added, recording the information of the new resource into first resource record data;
if the type of the change of the cloud side resource is deleting an old resource, recording the information of the old resource into second resource recording data;
creating a block according to the first resource record data or the second resource record data, and broadcasting to the members of the block chain;
after the member of the block chain receives the broadcast, the block body is added to the block chain;
and when the type of the change of the cloud edge resource is that an old resource is deleted, deleting the old resource from the resource locking list.
Referring to fig. 3 and 7, when the resource of the cloud-side collaboration platform changes, the resource change status is determined; when the cloud edge resources change to be added with new resources, the cloud edge collaboration platform fills information into the first resource record data through the cloud edge resource evaluation module, the information comprises the steps of adding the cloud to which the new added resources belong and the resource type to obtain corresponding resource numbers, setting the task list as an empty set, writing the new added resources into a total resource list and an idle resource list in a classified mode according to computing resources, network resources and storage data, and calculating to obtain resource attribute factor values; the resource attribute factors comprise stability factors, safety factors, performance factors and cost factors; the cloud edge collaboration platform calls a block chain building module to create a block according to first resource record data and broadcasts the block to the members of the block chain, wherein the first resource record data are stored on the block in an encrypted mode; receiving the broadcast by the member of the block chain, and calling a block chain building module to add the block to the block chain; and when the cloud edge resources change to delete old resources, deleting the resources to be deleted from the resource locking list.
In a further preferred embodiment, if the type of the change in the cloud-side resource is deletion of an old resource, recording information of the old resource in second resource record data includes:
adding the old resource to the resource lock list and determining a task list on the old resource from the blockchain;
determining a task set to be redistributed according to the task list and a redistribution task set algorithm;
according to the task re-allocation method, re-allocating resources for the task set to be re-allocated, adjusting the cooperative relationship among tasks, and determining that the task re-allocation is completed;
and according to the completion of the task reallocation, the task list on the old resource is empty, and the second resource record data is determined.
Referring to fig. 3 and 7, the cloud-edge collaboration platform calls a cloud-edge resource locking submodule to add a resource to be deleted into a resource locking list by using a cloud-edge resource allocation module, and obtains a task list on the resource to be deleted from a blockchain through a blockchain query module; the cloud edge collaboration platform obtains a task set to be redistributed by using a redistribution task set algorithm according to the task list through the task redistribution module, redistributes resources for the task set to be redistributed and adjusts the collaboration relationship among tasks; after receiving a completion notification returned by the task re-allocation submodule, the cloud side collaboration platform calls a cloud side resource monitoring module to confirm that a task list on the resource is empty; the cloud-edge collaboration platform fills in second resource record data information through the cloud-edge resource evaluation module, and the method comprises the following steps: setting the task list as an empty set, setting the total resource list as an empty set, setting the free resource list as an empty set, setting the resource attribute factor value as 0, and determining second resource record data.
Further, as a preferred embodiment, the reallocating resources for the task set to be reallocated and adjusting a coordination relationship between tasks according to the method for reallocating tasks, and determining completion of task reallocation includes:
acquiring the task set to be redistributed and the block chain;
acquiring an idle resource list from the block chain;
acquiring a task set to be redistributed according to the task set to be redistributed, and determining a first task coupling relation set of the task set to be redistributed;
according to the task coupling relation set, deploying the tasks in the task set to be redistributed to the resources in the free resource list, and determining a second task coupling relation set;
and updating the record of the related resources on the block chain according to the second task coupling relation set, and determining that the task reallocation is completed.
Referring to fig. 4, the cloud-edge collaboration platform acquires a task set to be reallocated through the task reallocation sub-module, and calls the block chain query module to acquire free resource lists on the core cloud and the edge cloud from the block chain; the cloud side collaboration platform extracts the task dismantling sets and the coupling relation sets in the task sets to be redistributed through the task redistributing module; the task reallocation module optimizes and deploys the tasks in the task set to be reallocated to the cloud-edge resources in the idle resource list according to the coupling relation set, and updates the coupling relation set information in the task split set by using the task reallocation module; the cooperative platform cloud agent calls a block chain construction module to update records of related resources on a block chain, a block is constructed and broadcast to block chain members, the block chain members complete accounting and consensus confirmation work, a random number and a timestamp are recorded into a block header, the block is added into the block chain, the block chain construction is completed, task reallocation is determined to be completed, and the cloud edge cooperative platform reenters a cloud edge cooperative resource allocation method flow after all reallocation tasks complete task periods to perform cloud edge cooperative resource allocation.
Further as a preferred embodiment, the determining a cloud-edge coordination scheme according to the task parameter of the resource to be allocated and by combining a task resource coordination algorithm includes:
acquiring an idle resource list, a resource locking list and a resource locking failure list, and determining an available resource list;
according to the task parameters of the resources to be distributed, deleting unsuitable resources from the available resource table, and determining a task available resource set;
setting the parallelism and the repulsion information of the minimum subtask in the minimum task set according to the task parameters of the resources to be distributed, and determining the minimum task set;
analyzing resources in the task available resource set according to the task parameters of the resources to be allocated, allocating resources for the minimum subtask in the minimum task set, and determining an allocated resource set;
determining a configuration scheme set and a task starting set rule set according to the allocation resource set and the task coupling relation set;
and merging the allocation resource set, the configuration scheme set and the task starting set rule set to determine the cloud edge coordination scheme.
Subtracting the locking resource list from the free resource list, and subtracting the locking resource failure list from the free resource list to obtain an available resource list; deleting unsuitable resource units from an available resource table according to task stability requirements, performance requirements and safety requirements of resources to be allocated to obtain a task available resource set of the resources to be allocated; adjusting the proportion of using the edge cloud resources, namely the quotient of the total resource amount of the edge cloud and the total resource amount used by the task, according to the service types of the resources to be distributed, including IAAS, PAAS and SAAS types; setting the parallelism and the repulsion information of the minimum subtask in the minimum task set according to the stability requirement, the performance requirement and the safety requirement of the tasks to obtain task limitation and expansion requirements; analyzing a resource number and a resource attribute factor of each resource in the task available resource set according to the time sensitivity index of the task, the task collaborative maximum time and the target customer information, allocating task available resources for the minimum subtask in the minimum subtask set according to a performance priority principle, and recording the used resource number and the resource information planned to obtain an allocated resource set; and calculating a configuration scheme set and a task starting and aggregating rule set according to all subtask configuration requirements recorded by the minimum subtask set and the coupling relation set, and combining the sets to obtain the cloud edge coordination scheme.
Further as a preferred embodiment, when the pre-allocated resource locking fails, analyzing the task execution time of the resource to be allocated, and determining that the next step of the resource allocation method for cloud-edge coordination is to end or restart, includes:
recording the pre-allocated resources with locking failure into a resource locking failure list;
when the current execution time of the task of the resources to be distributed is less than the maximum time of task cooperation, re-determining the cloud-edge cooperation scheme and carrying out the next step;
or the like, or, alternatively,
and when the current execution time of the task of the resource to be allocated is greater than the maximum time of the task cooperation, performing fault analysis processing, deleting the pre-allocated resource from the resource locking list and finishing.
Referring to fig. 1, a cloud-edge resource locking module records resource locking failure information into a resource locking failure list; judging whether the task execution time is less than the maximum task collaborative time, if the current task execution time of the resources to be allocated is less than the maximum task collaborative time, re-determining a cloud-edge collaborative scheme according to the task parameters of the resources to be allocated and a task resource collaborative algorithm, and performing the next step; otherwise, the execution of the total task fails, fault analysis processing is carried out, and the pre-allocated resources are deleted from the resource locking list and are finished; and removing the resource locking failure information from the resource locking failure list after the failure analysis processing is completed.
The embodiment of the invention also discloses a resource allocation device for cloud edge coordination, which comprises:
the system comprises a first module, a second module and a third module, wherein the first module is used for acquiring a task of a resource to be allocated, sending the task of the resource to be allocated to a cloud-side cooperative platform, performing task analysis on the task of the resource to be allocated and determining a task parameter of the resource to be allocated;
the second module is used for determining a cloud edge coordination scheme according to the task parameters of the resources to be distributed and a task resource coordination algorithm;
the third module is used for pre-allocating resources according to the cloud edge coordination scheme and determining pre-allocated resources;
the fourth module is used for adding the pre-allocated resources into a resource locking list and informing a cooperative platform cloud agent of locking the resources of the pre-allocated resources;
a fifth module, configured to delete the pre-allocated resource that is successfully locked from the resource locking list, construct a block, add the block to a block chain, and determine the block chain;
a sixth module, configured to analyze the task execution time of the resource to be allocated, and determine that a next step of the resource allocation method for cloud-edge coordination is to end or restart;
a seventh module, configured to perform resource allocation on the task of the resource to be allocated according to the block chain and the cloud-edge coordination scheme.
Referring to fig. 1 and 6, fig. 6 is a network topology diagram of a resource allocation method for cloud-edge collaboration according to an embodiment of the present invention, where an environment is composed of a cloud-edge collaboration platform, a core cloud, an edge cloud, a terminal environment, and a task-related environment, where the cloud-edge collaboration platform deploys a collaboration platform cloud agent on each of the core cloud and the edge cloud to perform cloud-edge collaboration task work; the cloud-edge collaborative platform performs cloud-edge resource allocation for the task of the resource to be allocated, and obtains task parameters through the task analysis module, wherein the cloud-edge collaborative platform comprises: task splitting diversity, service types of tasks, time sensitivity indexes of the tasks, target client information and an idle resource list; the cloud-edge coordination platform calls the task resource coordination computing module to obtain a cloud-edge coordination scheme by using a task resource coordination algorithm, and informs the cloud-edge resource allocation module to allocate resources according to the cloud-edge coordination scheme and carry out corresponding allocation; the cloud side resource allocation module calls a cloud side resource locking module to add pre-allocated resources into a resource locking list, and calls a cloud side resource arrangement module to inform resource allocation modules of all cooperative platform cloud side agents on the cloud platform to be deployed of resources required by task locking; when the resource is locked, the resource number and the resource attribute factor of the resource unit where the resource to be locked is located are inquired through the block chain inquiry module; calculating whether the resource attribute factor of the resource number is the same as the resource attribute factor value recorded on the block or not by a cloud edge resource monitoring module of the collaborative platform cloud agent, if so, indicating that the state of the resource when being brought into the platform is changed, and the resource locking fails; when the locking of the pre-allocated resources fails, analyzing the task execution time of the resources to be allocated, and determining that the next step of the resource allocation method of cloud-edge cooperation is finished or restarted; when the pre-allocated resources are successfully locked, the cloud-edge resource locking module deletes resource locking failure information corresponding to the locked resources from the resource locking failure list, and the collaboration platform cloud agent calls the block chain construction module to update records of related resources on the block chain: adding the task list to a task list newly allocated on the resource, wherein the free resource list is obtained by subtracting a resource list to be allocated on the resource from the element free resource list; after the block chain is constructed, the cloud side cooperation platform informs a cloud side resource locking module to delete the locked resource from the resource locking list, and the cloud side cooperation platform calls a cloud side resource allocation module to inform all cooperation platform cloud side agents to be allocated with the cloud sides of the cloud sides to allocate the needed resource for each subtask and carry out corresponding configuration so as to carry out work; and the cooperative platform cloud agent calls the resource allocation module to allocate resources to the subtasks allocated to the cloud and carry out corresponding configuration, and after the allocation is finished, the cooperative platform returns a notification that the cloud resource allocation of the tasks is successful to the cloud side cooperative platform.
The embodiment of the invention also discloses an electronic device, which comprises a processor and a memory;
the memory is used for storing programs;
the processor executes the program to implement the method as described in fig. 1.
The embodiment of the invention also discloses a computer readable storage medium, wherein the storage medium stores a program, and the program is executed by a processor to realize the method shown in the figure 1.
The embodiment of the invention also discloses a computer program product or a computer program, which comprises computer instructions, and the computer instructions are stored in a computer readable storage medium. The computer instructions may be read by a processor of a computer device from a computer-readable storage medium, and executed by the processor to cause the computer device to perform the method illustrated in fig. 1.
In the related technology, most of the cooperation schemes for realizing the core cloud and the edge cloud are closely related to the types of tasks, the tasks are split into subtasks before deployment, and the subtasks are fixedly deployed in the core cloud or the edge cloud. Meanwhile, when the cloud-edge collaborative scheme executes the cloud-edge collaborative task, the used resources cannot be well controlled and limited, and the problems of stability, safety, excellent performance and cost of the resources used by the task are difficult to be simultaneously considered.
In summary, the cloud-edge cooperative resource allocation method, apparatus, device and medium of the present invention have the following advantages:
1) according to the invention, the block chain is used for recording the sub-resource current status information of the core cloud and the edge cloud, so that the credibility of the task allocation resource and the resource allocation record is ensured, the integrity and the usability of the resource information are improved, and the resource allocation is controlled through the resource information, so that the safety of the resource allocation is improved;
2) according to the cloud-side collaborative scheme, time sensitivity indexes and target customer information factors, namely position range of a task service target, network communication state, client equipment performance, customer environment safety factor information and other comprehensive information are considered, and the stability of resource allocation is improved;
3) according to the invention, the cloud edge cooperative platform is used for distributing proper resources to the tasks after performing unified analysis on the tasks, a coupling rule set is added when a cloud edge cooperative scheme is designed, the coupling relation of the subtasks is listed, most tasks in the subtask set can be executed on a plurality of resources in parallel during actual execution, and meanwhile, the distribution of the cloud edge resources is based on the overall realization requirement of the tasks, and available resources are distributed under the condition of considering stability, safety, performance superiority and cost.
In alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flow charts of the present invention are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of larger operations are performed independently.
Furthermore, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the described functions and/or features may be integrated in a single physical device and/or software module, or one or more functions and/or features may be implemented in a separate physical device or software module. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary for an understanding of the present invention. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be understood within the ordinary skill of an engineer, given the nature, function, and internal relationship of the modules. Accordingly, those skilled in the art can, using ordinary skill, practice the invention as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative of and not intended to limit the scope of the invention, which is defined by the appended claims and their full scope of equivalents.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A resource allocation method for cloud edge collaboration is characterized by comprising the following steps:
the method comprises the steps of obtaining a task of a resource to be allocated, sending the task of the resource to be allocated to a cloud-side cooperative platform, carrying out task analysis on the task of the resource to be allocated, and determining a task parameter of the resource to be allocated;
determining a cloud edge coordination scheme according to the task parameters of the resources to be distributed and a task resource coordination algorithm;
pre-allocating resources according to the cloud edge coordination scheme, and determining pre-allocated resources;
adding the pre-allocated resources into a resource locking list, and informing a cooperative platform cloud agent to lock the resources of the pre-allocated resources;
when the pre-allocated resources are successfully locked, deleting the successfully locked pre-allocated resources from the resource locking list, constructing block blocks, adding the block blocks into a block chain, and determining the block chain;
when the locking of the pre-allocated resources fails, analyzing the task execution time of the resources to be allocated, and determining that the next step of the resource allocation method of cloud-edge cooperation is finished or restarted;
and performing resource allocation on the task of the resources to be allocated according to the block chain and the cloud edge coordination scheme.
2. The method according to claim 1, wherein the resource allocation for the task to which the resource is to be allocated according to the block chain and the cloud-edge coordination scheme includes:
task auditing is carried out on the task of the resource to be distributed, and the service type, the time sensitivity index and the target client information of the task are determined;
splitting the task by combining a task splitting algorithm according to the time sensitivity index and the target client information to determine task splitting diversity;
inquiring the block chain, determining an idle resource list, and performing resource allocation on the subtasks in the task split set;
according to the logic sequence of the cloud edge cooperation scheme, starting the subtasks and determining the execution result of the subtasks;
according to the execution result of the subtasks, performing aggregation processing on the subtasks, and determining that the task of the resources to be allocated completes resource allocation;
and releasing the allocated resources according to the cloud edge coordination scheme, constructing blocks according to the states of the allocated resources, and adding the blocks into the block chain.
3. The method for allocating resources in cloud-edge collaboration according to claim 1, further comprising a cloud-edge resource changing method, including the following steps:
determining the type of the change of the cloud edge resources;
if the type of the change of the cloud side resource is that a new resource is added, recording the information of the new resource into first resource record data;
if the type of the change of the cloud side resource is deleting an old resource, recording the information of the old resource into second resource recording data;
creating a block according to the first resource record data or the second resource record data, and broadcasting to the members of the block chain;
after the member of the block chain receives the broadcast, the block body is added to the block chain;
and when the type of the change of the cloud edge resource is that an old resource is deleted, deleting the old resource from the resource locking list.
4. The method according to claim 3, wherein if the type of the change of the cloud-edge resource is deletion of an old resource, recording information of the old resource in second resource record data includes:
adding the old resource to the resource lock list and determining a task list on the old resource from the blockchain;
determining a task set to be redistributed according to the task list and a redistribution task set algorithm;
according to the task re-allocation method, re-allocating resources for the task set to be re-allocated, adjusting the cooperative relationship among tasks, and determining that the task re-allocation is completed;
and according to the completion of the task reallocation, the task list on the old resource is empty, and the second resource record data is determined.
5. The method for resource allocation of cloud-edge collaboration as claimed in claim 4, wherein the step of reallocating resources for the task set to be reallocated and adjusting collaboration among tasks according to the task reallocation method to determine completion of task reallocation comprises:
acquiring the task set to be redistributed and the block chain;
acquiring an idle resource list from the block chain;
acquiring a task set to be redistributed according to the task set to be redistributed, and determining a first task coupling relation set of the task set to be redistributed;
according to the task coupling relation set, deploying the tasks in the task set to be redistributed to the resources in the free resource list, and determining a second task coupling relation set;
and updating the record of the related resources on the block chain according to the second task coupling relation set, and determining that the task reallocation is completed.
6. The method according to claim 1, wherein the determining a cloud-edge coordination scheme according to the task parameter of the resource to be distributed in combination with a task resource coordination algorithm includes:
acquiring an idle resource list, a resource locking list and a resource locking failure list, and determining an available resource list;
according to the task parameters of the resources to be distributed, deleting unsuitable resources from the available resource table, and determining a task available resource set;
setting the parallelism and the repulsion information of the minimum subtask in the minimum task set according to the task parameters of the resources to be distributed, and determining the minimum task set;
analyzing resources in the task available resource set according to the task parameters of the resources to be allocated, allocating resources for the minimum subtask in the minimum task set, and determining an allocated resource set;
determining a configuration scheme set and a task starting set rule set according to the allocation resource set and the task coupling relation set;
and merging the allocation resource set, the configuration scheme set and the task starting set rule set to determine the cloud edge coordination scheme.
7. The method according to claim 1, wherein when the locking of the pre-allocated resource fails, analyzing the task execution time of the resource to be allocated to determine that a next step of the cloud-edge cooperative resource allocation method is to end or restart the method, includes:
recording the pre-allocated resources with locking failure into a resource locking failure list;
when the current execution time of the task of the resources to be distributed is less than the maximum time of task cooperation, re-determining the cloud-edge cooperation scheme and carrying out the next step;
or the like, or, alternatively,
and when the current execution time of the task of the resource to be allocated is greater than the maximum time of the task cooperation, performing fault analysis processing, deleting the pre-allocated resource from the resource locking list and finishing.
8. A cloud-edge coordinated resource allocation apparatus, comprising:
the system comprises a first module, a second module and a third module, wherein the first module is used for acquiring a task of a resource to be allocated, sending the task of the resource to be allocated to a cloud-side cooperative platform, performing task analysis on the task of the resource to be allocated and determining a task parameter of the resource to be allocated;
the second module is used for determining a cloud edge coordination scheme according to the task parameters of the resources to be distributed and a task resource coordination algorithm;
the third module is used for pre-allocating resources according to the cloud edge coordination scheme and determining pre-allocated resources;
the fourth module is used for adding the pre-allocated resources into a resource locking list and informing a cooperative platform cloud agent of locking the resources of the pre-allocated resources;
a fifth module, configured to delete the pre-allocated resource that is successfully locked from the resource locking list, construct a block, add the block to a block chain, and determine the block chain;
a sixth module, configured to analyze the task execution time of the resource to be allocated, and determine that a next step of the resource allocation method for cloud-edge coordination is to end or restart;
a seventh module, configured to perform resource allocation on the task of the resource to be allocated according to the block chain and the cloud-edge coordination scheme.
9. An electronic device comprising a processor and a memory;
the memory is used for storing programs;
the processor executing the program realizes the method according to any one of claims 1-7.
10. A computer-readable storage medium, characterized in that the storage medium stores a program, which is executed by a processor to implement the method according to any one of claims 1-7.
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