CN112995280B - Data distribution method and device for multi-content demand service - Google Patents
Data distribution method and device for multi-content demand service Download PDFInfo
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Abstract
The application discloses a data distribution method and device for multi-content demand service, wherein the method comprises the following steps: a data acquisition period, wherein based on the data block acquisition requirement of a user in the current period, the data block transmission total delay of the user is the minimum, a repeated game mode is adopted, the data block acquisition strategy in the current period is determined for the user, and corresponding user equipment is informed; the data block acquisition strategy comprises a target edge node of each type of data block requested by a user; and the user equipment acquires all data blocks required by the current period according to the data block acquisition strategy. By adopting the invention, the data transmission performance of the mobile edge calculation can be improved.
Description
Technical Field
The present invention relates to a mobile edge computing technology, and in particular, to a data distribution method and apparatus for a multi-content demand service.
Background
As a concept in network architecture, mobile edge computing allows mobile users to migrate portions of computing tasks from a remote central cloud into an edge network represented by cellular base stations and WI-FI access points. Compared with the traditional centralized mobile cloud computing mode, the computing resources for processing the user tasks in the mobile edge computing are closer to the user in geographic position and logical position. Through the sinking of the computing resources, the problems of high transmission delay, network congestion and the like are solved by the mobile edge computing, and the user experience in the mobile service is improved.
In a mobile edge computing environment, a large number of multi-content demanding services exist, and for such services, on one hand, processing of each user request requires acquiring a plurality of content data; on the other hand, in order to ensure the reliability of data storage, the same content data is stored and backed up on a plurality of edge nodes in the form of data blocks. Due to the limitation and difference of computation and communication capabilities between edge nodes, the transmission capability of each edge node for each data block is also limited and different. When multiple users request the same data block at the same time, the users compete for the limited transmission capability corresponding to the data block. Therefore, in such many-to-many allocation mode, how to allocate data blocks based on multi-user requirements to improve the data transmission performance of the mobile edge calculation is an important issue in the mobile edge calculation. At present, no corresponding solution is proposed for the problem.
Disclosure of Invention
In view of the above, the main objective of the present invention is to provide a method and an apparatus for distributing data for a multiple content demand service, which can improve data transmission performance of mobile edge computing.
In order to achieve the purpose, the technical scheme provided by the invention is as follows:
a data distribution method facing to multi-content demand service comprises the following steps:
in each preset data acquisition period, based on the data block acquisition requirement of a user in the current period, determining a data block acquisition strategy in the current period for the user and informing corresponding user equipment by adopting a repeated game mode with the aim of minimizing the total data block transmission delay of the user; the data block acquisition strategy comprises a target edge node of each type of data block requested by a user;
and the user equipment acquires all data blocks required by the current period according to the data block acquisition strategy.
Preferably, the determining the data block acquisition policy in the current period for the user includes:
a. initializing a candidate optimization user set into all online users, and initializing a data block acquisition strategy of each user;
b. if the candidate optimization user set is an empty set, quitting the data block acquisition strategy adopted by the user in the current period; otherwise, executing step c;
c. randomly selecting a user k from the candidate optimization user set, and determining the request quantity of other online users corresponding to each type of data block on each edge node according to the current data block acquisition strategy and data block acquisition requirement of other online users except the user k;
d. for each type of data block i, calculating the transmission duration of the type of data block i obtained by the user k from each edge node storing the type of data block i according to the number of the other online user requests; selecting the edge node with the minimum transmission duration as a candidate target edge node of the data block i requested by the user k;
e. according to the request quantity of other online users, calculating the total transmission time length T of all data blocks required by the user k for acquiring the current period by using the data block acquisition strategy corresponding to the candidate target edge nodek,new；
f. If said T isk,newIf the total transmission time of all the data blocks required by the current period is less than the total transmission time required by the current data block acquisition strategy of the user k, updating the current data block acquisition strategy of the user k into the data block acquisition strategy corresponding to the candidate target edge node, updating the candidate optimized user set into the whole online users, and executing the step c; otherwise, taking the current data block acquisition strategy of the user k as the data block acquisition strategy of the user k in the current period, deleting the user k from the candidate optimized user set, and executing the step b.
Preferably, in the step a, a data block acquisition policy of each user is initialized in a random selection manner.
Preferably, the calculating, according to the number of the other online user requests in step d, the transmission duration for the user k to respectively obtain the data block i from each edge node storing the data block i includes:
for each edge node v from which a data block i of this type is stored, according to
Calculating the transmission time t for the user k to obtain the data block i from the edge nodek,i(ii) a Wherein v represents an edge node number storing the ith type data block; c. CiDenotes the size of the i-th class data block, mv,iRepresenting the number of the other online user requests corresponding to the ith type data block on the edge node v; b isv,iIndicating the amount of data of the i-th class data block transmitted by the edge node v in a unit time.
The embodiment of the invention also discloses a data distribution device facing the multi-content demand service, which comprises:
the acquisition strategy determining module is used for determining a data block acquisition strategy in the current period for the user in a repeated game mode by taking the minimum total data block transmission delay of the user as a target based on the data block acquisition requirement of the user in the current period in each preset data acquisition period; the data block acquisition strategy comprises a target edge node of each type of data block requested by a user;
and the acquisition strategy notification module is used for notifying the data block acquisition strategy to corresponding user equipment.
Preferably, the obtaining policy determining module is configured to determine a data block obtaining policy in a current period for the user, and includes:
a. initializing a candidate optimization user set into all online users, and initializing a data block acquisition strategy of each user;
b. if the candidate optimization user set is an empty set, quitting the data block acquisition strategy adopted by the user in the current period; otherwise, executing step c;
c. randomly selecting a user k from the candidate optimization user set, and determining the request quantity of other online users corresponding to each type of data block on each edge node according to the current data block acquisition strategy and data block acquisition requirement of other online users except the user k;
d. for each type of data block i, calculating the transmission duration of the type of data block i obtained by the user k from each edge node storing the type of data block i according to the number of the other online user requests; selecting the edge node with the minimum transmission duration as a candidate target edge node of the data block i requested by the user k;
e. according to the request quantity of other online users, calculating the total transmission time length T of all data blocks required by the user k for acquiring the current period by using the data block acquisition strategy corresponding to the candidate target edge nodek,new；
f. If said T isk,newIf the total transmission time of all the data blocks required by the current period is less than the total transmission time required by the current data block acquisition strategy of the user k, updating the current data block acquisition strategy of the user k into the data block acquisition strategy corresponding to the candidate target edge node, updating the candidate optimized user set into the whole online users, and executing the step c; otherwise, taking the current data block acquisition strategy of the user k as the data block acquisition strategy of the user k in the current period, deleting the user k from the candidate optimized user set, and executing the step b.
Preferably, the obtaining policy determining module is configured to initialize a data block obtaining policy of each user in a random selection manner in step a.
Preferably, the obtaining policy determining module is configured to calculate, according to the number of the other online user requests in step d, a transmission duration for the user k to obtain the data block i from each edge node storing the data block i, and includes:
for each edge node v from which a data block i of this type is stored, according to
Calculating the k from the edgeThe node acquires the transmission time t of the data block ik,i(ii) a Wherein v represents an edge node number storing the ith type data block; c. CiDenotes the size of the i-th class data block, mv,iRepresenting the number of the other online user requests corresponding to the ith type data block on the edge node v; b isv,iIndicating the amount of data of the i-th class data block transmitted by the edge node v in a unit time.
The embodiment of the invention also discloses data distribution equipment for the multi-content demand service, which comprises a processor and a memory;
the memory stores an application program executable by the processor for causing the processor to execute the data distribution method for the multiple content demand service as described above.
The embodiment of the invention also discloses a computer readable storage medium, wherein computer readable instructions are stored, and the computer readable instructions are used for executing the data distribution method for the multi-content demand service.
In summary, in the data distribution scheme for the multi-content demand service provided in the embodiment of the present invention, in each data acquisition period, based on the data block acquisition requirement of the user in the current period, the target edge node that requests each type of data block in the current period is determined for the user in a repeated game manner with the target that the total data block transmission delay of the user is the minimum, so that the total data block acquisition delay of the user for acquiring the required data block is the lowest by dynamically setting the target edge node that the user acquires each type of data block according to the data acquisition requirement of the user, and thus the data transmission performance of the mobile edge calculation can be improved.
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FIG. 1 is a schematic flow chart of a method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Fig. 1 is a schematic flow chart of a method according to an embodiment of the present invention, and as shown in fig. 1, the data distribution method for a multiple content demand service implemented according to the embodiment mainly includes:
The data block acquisition policy comprises target edge nodes of each type of data block requested by a user, namely the data block acquisition policy is used for limiting the edge nodes to which the user requests each type of data block.
In this way, the minimum total data block transmission delay of the user is taken as the target, and the target edge nodes required to be requested by acquiring various data blocks are reasonably configured for the user according to the current data acquisition requirement of the user, so that the data transmission performance of the mobile edge calculation can be improved.
In practical applications, the data acquisition period can be set by those skilled in the art according to practical needs.
In one embodiment, the following method can be used in step 101 to determine the data chunk acquisition strategy in the current cycle for each user in a repeated game mode:
step a, initializing a candidate optimization user set into all online users, and initializing a data block acquisition strategy of each user.
In one embodiment, a data block acquisition policy for each of the users may be initialized in a randomly selected manner, i.e., for user k e U, randomly from each ViIn which a node is selected
Together forming user kInitial data acquisition strategy
Wherein U represents the online user set, n represents the number of data block categories, ViRepresenting a collection of edge nodes storing class i data blocks.
In another embodiment, the data block acquisition policy in the current period may also be initialized based on the data block acquisition policy used by the user in the previous data acquisition period.
Step b, if the candidate optimization user set is an empty set, quitting the data block acquisition strategy adopted by the user in the current period; otherwise, executing step c.
And c, randomly selecting a user k from the candidate optimization user set, and determining the request quantity of other online users corresponding to each type of data block on each edge node according to the current data block acquisition strategy and data block acquisition requirement of other online users except the user k.
This step is used to determine the number of other users, except user k, simultaneously requesting the data block for each type of data block stored on each edge node, so as to determine the candidate target edge node requesting each type of data block for user k based on this in step d.
Step d, for each type of data block i, calculating the transmission duration of the type of data block i obtained by the user k from each edge node storing the type of data block i according to the number of the other online user requests; and selecting the edge node with the minimum transmission time length as a candidate target edge node of the data block i requested by the user k.
In an embodiment, the following method may be specifically adopted in step d to calculate, according to the number of the other online user requests, a transmission duration for the currently selected user k to respectively obtain the data block i from each edge node storing the data block i:
for each edge node v from which a data block i of this type is stored, according to
Calculating the transmission time t for the user k to obtain the data block i from the edge nodek,i(ii) a Wherein v represents an edge node number storing the ith type data block; c. CiDenotes the size of the i-th class data block, mv,iRepresenting the number of the other online user requests corresponding to the ith type data block on the edge node v; b isv,iIndicating the amount of data of the i-th class data block transmitted by the edge node v in a unit time.
In the method, a plurality of users simultaneously requesting the same type of data block from the same node determine that each user obtains the data sending capability of the type of data block by adopting a mode of equally dividing the data sending capability, namely
Step e, according to the request quantity of other online users, calculating the total transmission time length T of all data blocks required by the user k to acquire the current period by using the data block acquisition strategy corresponding to the candidate target edge nodek,new。
Here, the data block acquisition policy corresponding to the candidate target edge node is the candidate target edge node of each type of data block requested by the user k determined in step d.
The step can be specifically according to
Calculating Tk,newWherein x isk,iFor indicating whether user k needs to obtain the ith class data block, x in the current periodk,i1 indicates that the user k needs to acquire the ith class data block in the current period, xk,i0 means that user k does not need to acquire class i data block in the current period, vk,iAn edge node number indicating that user k requests the i-th class data block,
indicating the simultaneous movement to the v-th except for user kk,iNumber of other users requesting class i data block by each nodeThe amount of the compound (A) is,
denotes the v thk,iThe data transmission capability of the individual node to the ith type data block is the data volume for transmitting the ith type data block in unit time.
T abovek,newObtaining a utility function value of a strategy for a data block corresponding to the candidate target edge node; the corresponding potential function is
Therefore, the determination of the data block acquisition policy for each cycle has convergence.
Step f, if said Tk,newIf the total transmission time of all the data blocks required by the current period is less than the total transmission time required by the current data block acquisition strategy of the user k, updating the current data block acquisition strategy of the user k into the data block acquisition strategy corresponding to the candidate target edge node, updating the candidate optimized user set into the whole online users, and executing the step c; otherwise, taking the current data block acquisition strategy of the user k as the data block acquisition strategy of the user k in the current period, deleting the user k from the candidate optimized user set, and executing the step b.
In this step, the specific calculation method for obtaining the total transmission duration of all the data blocks required by the current period by using the current data block obtaining strategy of the user k is the same as that of the step T in the step ek,newThe calculation of (2) is not described herein again.
Here, if said T isk,newThe total transmission time length of all the data blocks required by the current period acquired by the current data block acquisition strategy of the user k is shorter than the total transmission time length of all the data blocks required by the current period acquired by the current data block acquisition strategy of the user k, and the data block acquisition strategy corresponding to the candidate target edge node is superior to the data block acquisition strategy of the user kThe obtaining of the optimal data block obtaining strategies is determined based on the data block obtaining strategies of the users k before updating, at this time, the data block obtaining strategies of the users k are changed, and correspondingly, the data block obtaining strategies of other users which are deleted from the candidate optimization user set before cannot be guaranteed to be optimal, so that the candidate optimization user set needs to be reset to be the whole online users at this time, and the current data block obtaining strategies of all the users in the candidate optimization user set are continuously judged or adjusted optimally.
If said T isk,newAnd (b) the total transmission time length of all the data blocks required by the current period acquired by adopting the current data block acquisition strategy of the user k is not less than the total transmission time length of all the data blocks required by the current period acquired by adopting the current data block acquisition strategy of the user k, which indicates that the current data block acquisition strategy of the user k is optimal when the current data block acquisition strategies of other online users are not changed, at this moment, the user k needs to be deleted from the candidate optimization user set, and the step b is returned to continuously judge whether the current data block acquisition strategy of each other user in the candidate optimization user set is optimal or not.
When the candidate optimization user set is empty, it indicates that the current data block acquisition strategy of all users is already optimal after the candidate optimization user set is updated to all online users for the last time, and therefore, the data block acquisition strategy in the current period is determined to be completed.
And 102, the user equipment acquires all data blocks required by the current period according to the data block acquisition strategy.
It can be seen from the foregoing technical solutions that, in the data distribution method for multi-content demand services according to the embodiments of the present invention, by targeting that the total data block transmission delay of a user is the minimum according to the data acquisition requirements of the user, and by using a repeated game manner, a target edge node for the user to acquire each type of data block is dynamically set, so that the total delay for the user to acquire a required data block is the minimum, and thus, the data transmission performance of mobile edge calculation can be effectively improved.
Corresponding to the above method embodiment, the embodiment of the present invention further discloses a data distribution device for a multi-content demand service, where the device is disposed at a network side, and as shown in fig. 2, the device includes:
an obtaining policy determining module 201, configured to determine, in each preset data obtaining period, a data block obtaining policy for a user in a current period in a repeated game manner, with a target of minimum total data block transmission delay of the user based on a data block obtaining requirement of the user in the current period; the data block acquisition strategy comprises a target edge node of each type of data block requested by a user;
an obtaining policy notifying module 201, configured to notify the corresponding user equipment of the data block obtaining policy.
Preferably, the obtaining policy determining module 201 is configured to determine a data block obtaining policy in the current period for the user, and includes:
a. initializing a candidate optimization user set into all online users, and initializing a data block acquisition strategy of each user;
b. if the candidate optimization user set is an empty set, quitting the data block acquisition strategy adopted by the user in the current period; otherwise, executing step c;
c. randomly selecting a user k from the candidate optimization user set, and determining the request quantity of other online users corresponding to each type of data block on each edge node according to the current data block acquisition strategy and data block acquisition requirement of other online users except the user k;
d. for each type of data block i, calculating the transmission duration of the type of data block i obtained by the user k from each edge node storing the type of data block i according to the number of the other online user requests; selecting the edge node with the minimum transmission duration as a candidate target edge node of the data block i requested by the user k;
e. according to the request quantity of other online users, calculating the total transmission time length T of all data blocks required by the user k for acquiring the current period by using the data block acquisition strategy corresponding to the candidate target edge nodek,new；
f. If said T isk,newIf the total transmission time of all the data blocks required by the current period is less than the total transmission time required by the current data block acquisition strategy of the user k, updating the current data block acquisition strategy of the user k into the data block acquisition strategy corresponding to the candidate target edge node, updating the candidate optimized user set into the whole online users, and executing the step c; otherwise, taking the current data block acquisition strategy of the user k as the data block acquisition strategy of the user k in the current period, deleting the user k from the candidate optimized user set, and executing the step b.
Preferably, the obtaining policy determining module 201 is configured to initialize a data block obtaining policy of each user in a randomly selected manner in the step a.
Preferably, the obtaining policy determining module 201 is configured to calculate, according to the number of the other online user requests in step d, a transmission duration for the user k to obtain the data block i from each edge node storing the data block i, and includes:
for each edge node v from which a data block i of this type is stored, according to
Calculating the transmission time t for the user k to obtain the data block i from the edge nodek,i(ii) a Wherein v represents an edge node number storing the ith type data block; c. CiDenotes the size of the i-th class data block, mv,iRepresenting the number of the other online user requests corresponding to the ith type data block on the edge node v; b isv,iIndicating the amount of data of the i-th class data block transmitted by the edge node v in a unit time.
Based on the embodiment of the data distribution method facing the multi-content demand service, the embodiment of the application also discloses data distribution equipment facing the multi-content demand service, which comprises a processor and a memory;
the memory stores an application program executable by the processor for causing the processor to execute the data distribution method for the multiple content demand service as described above.
The memory may be embodied as various storage media such as an Electrically Erasable Programmable Read Only Memory (EEPROM), a Flash memory (Flash memory), and a Programmable Read Only Memory (PROM). The processor may be implemented to include one or more central processors or one or more field programmable gate arrays, wherein the field programmable gate arrays integrate one or more central processor cores. In particular, the central processor or central processor core may be implemented as a CPU or MCU.
It should be noted that not all steps and modules in the above flows and structures are necessary, and some steps or modules may be omitted according to actual needs. The execution order of the steps is not fixed and can be adjusted as required. The division of each module is only for convenience of describing adopted functional division, and in actual implementation, one module may be divided into multiple modules, and the functions of multiple modules may also be implemented by the same module, and these modules may be located in the same device or in different devices.
The hardware modules in the various embodiments may be implemented mechanically or electronically. For example, a hardware module may include a specially designed permanent circuit or logic device (e.g., a special purpose processor such as an FPGA or ASIC) for performing specific operations. A hardware module may also include programmable logic devices or circuits (e.g., including a general-purpose processor or other programmable processor) that are temporarily configured by software to perform certain operations. The implementation of the hardware module in a mechanical manner, or in a dedicated permanent circuit, or in a temporarily configured circuit (e.g., configured by software), may be determined based on cost and time considerations.
Embodiments of the present invention also provide a machine-readable storage medium storing instructions for causing a machine to perform a method as described herein. Specifically, a system or an apparatus equipped with a storage medium on which a software program code that realizes the functions of any of the embodiments described above is stored may be provided, and a computer (or a CPU or MPU) of the system or the apparatus is caused to read out and execute the program code stored in the storage medium. Further, part or all of the actual operations may be performed by an operating system or the like operating on the computer by instructions based on the program code. The functions of any of the above-described embodiments may also be implemented by writing the program code read out from the storage medium to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion unit connected to the computer, and then causing a CPU or the like mounted on the expansion board or the expansion unit to perform part or all of the actual operations based on the instructions of the program code.
Examples of the storage medium for supplying the program code include floppy disks, hard disks, magneto-optical disks, optical disks (e.g., CD-ROMs, CD-R, CD-RWs, DVD-ROMs, DVD-RAMs, DVD-RWs, DVD + RWs), magnetic tapes, nonvolatile memory cards, and ROMs. Alternatively, the program code may be downloaded from a server computer or the cloud by a communication network.
"exemplary" means "serving as an example, instance, or illustration" herein, and any illustration, embodiment, or steps described as "exemplary" herein should not be construed as a preferred or advantageous alternative. For the sake of simplicity, the drawings are only schematic representations of the parts relevant to the invention, and do not represent the actual structure of the product. In addition, in order to make the drawings concise and understandable, components having the same structure or function in some of the drawings are only schematically illustrated or only labeled. In this document, "a" does not mean that the number of the relevant portions of the present invention is limited to "only one", and "a" does not mean that the number of the relevant portions of the present invention "more than one" is excluded. In this document, "upper", "lower", "front", "rear", "left", "right", "inner", "outer", and the like are used only to indicate relative positional relationships between relevant portions, and do not limit absolute positions of the relevant portions.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. 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 (6)
1. A data distribution method facing to multi-content demand service is characterized by comprising the following steps:
in each preset data acquisition period, based on the data block acquisition requirement of a user in the current period, determining a data block acquisition strategy in the current period for the user and informing corresponding user equipment by adopting a repeated game mode with the aim of minimizing the total data block transmission delay of the user; the data block acquisition strategy comprises a target edge node of each type of data block requested by a user;
the user equipment acquires all data blocks required by the current period according to the data block acquisition strategy;
wherein the determining a data block acquisition policy in a current cycle for the user comprises:
a. initializing a candidate optimization user set into all online users, and initializing a data block acquisition strategy of each user;
b. if the candidate optimization user set is an empty set, quitting the data block acquisition strategy adopted by the user in the current period; otherwise, executing step c;
c. randomly selecting a user k from the candidate optimization user set, and determining the request quantity of other online users corresponding to each type of data block on each edge node according to the current data block acquisition strategy and data block acquisition requirement of other online users except the user k;
d. for each type of data block i, calculating the transmission duration of the type of data block i obtained by the user k from each edge node storing the type of data block i according to the number of the other online user requests; selecting the edge node with the minimum transmission duration as a candidate target edge node of the data block i requested by the user k; the calculating that the user k obtains the transmission duration of the data block i from each edge node storing the data block i respectively comprises: for each edge node v from which a data block i of this type is stored,according to
Calculating the transmission time t for the user k to obtain the data block i from the edge nodek,i(ii) a Wherein v represents an edge node number storing the ith type data block; c. CiDenotes the size of the i-th class data block, mv,iRepresenting the number of the other online user requests corresponding to the ith type data block on the edge node v; b isv,iRepresenting the data quantity of the ith type data block transmitted by the edge node v in unit time;
e. according to the request quantity of other online users, calculating the total transmission time length T of all data blocks required by the user k for acquiring the current period by using the data block acquisition strategy corresponding to the candidate target edge nodek,new；
f. If said T isk,newIf the total transmission time of all the data blocks required by the current period is less than the total transmission time required by the current data block acquisition strategy of the user k, updating the current data block acquisition strategy of the user k into the data block acquisition strategy corresponding to the candidate target edge node, updating the candidate optimized user set into the whole online users, and executing the step c; otherwise, taking the current data block acquisition strategy of the user k as the data block acquisition strategy of the user k in the current period, deleting the user k from the candidate optimized user set, and executing the step b.
2. The method according to claim 1, wherein the step a initializes the data block acquisition policy of each user by using a random selection method.
3. A data distribution apparatus for a multiple content demand service, comprising:
an obtaining strategy determining module, configured to, in each preset data obtaining period, based on a data block obtaining requirement of a user in a current period, target that a total data block transmission delay of the user is minimum, and adopt a repeated game modeDetermining a data block acquisition strategy in the current period for the user; the data block acquisition strategy comprises a target edge node of each type of data block requested by a user; the obtaining policy determining module is configured to determine a data block obtaining policy in a current period for the user, and includes: a. initializing a candidate optimization user set into all online users, and initializing a data block acquisition strategy of each user; b. if the candidate optimization user set is an empty set, quitting the data block acquisition strategy adopted by the user in the current period; otherwise, executing step c; c. randomly selecting a user k from the candidate optimization user set, and determining the request quantity of other online users corresponding to each type of data block on each edge node according to the current data block acquisition strategy and data block acquisition requirement of other online users except the user k; d. for each type of data block i, calculating the transmission duration of the type of data block i obtained by the user k from each edge node storing the type of data block i according to the number of the other online user requests; selecting the edge node with the minimum transmission duration as a candidate target edge node of the data block i requested by the user k; the calculating that the user k obtains the transmission duration of the data block i from each edge node storing the data block i includes: for each edge node v from which a data block i of this type is stored, according to
Calculating the transmission time t for the user k to obtain the data block i from the edge nodek,i(ii) a Wherein v represents an edge node number storing the ith type data block; c. CiDenotes the size of the i-th class data block, mv,iRepresenting the number of the other online user requests corresponding to the ith type data block on the edge node v; b isv,iRepresenting the data quantity of the ith type data block transmitted by the edge node v in unit time; e. according to the request quantity of other online users, calculating the total transmission time length T of all data blocks required by the user k for acquiring the current period by using the data block acquisition strategy corresponding to the candidate target edge nodek,new(ii) a f. If said T isk,newIf the total transmission time of all the data blocks required by the current period is less than the total transmission time required by the current data block acquisition strategy of the user k, updating the current data block acquisition strategy of the user k into the data block acquisition strategy corresponding to the candidate target edge node, updating the candidate optimized user set into the whole online users, and executing the step c; otherwise, taking the current data block acquisition strategy of the user k as the data block acquisition strategy of the user k in the current period, deleting the user k from the candidate optimization user set, and executing the step b;
and the acquisition strategy notification module is used for notifying the data block acquisition strategy to corresponding user equipment.
4. The apparatus according to claim 3, wherein said acquisition policy determining module is configured to initialize a data block acquisition policy for each of said users in a randomly selected manner in said step a.
5. A data distribution device for a multiple content demand service, comprising a processor and a memory;
the memory stores an application program executable by the processor for causing the processor to perform the method of data distribution for a multiple content demand service according to any one of claims 1 to 2.
6. A computer-readable storage medium having stored therein computer-readable instructions for executing the method for data distribution to a multiple content demand service according to any one of claims 1 to 2.
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