WO2020119636A1 - 数据访问请求响应方法、装置、终端和存储介质 - Google Patents

数据访问请求响应方法、装置、终端和存储介质 Download PDF

Info

Publication number
WO2020119636A1
WO2020119636A1 PCT/CN2019/124018 CN2019124018W WO2020119636A1 WO 2020119636 A1 WO2020119636 A1 WO 2020119636A1 CN 2019124018 W CN2019124018 W CN 2019124018W WO 2020119636 A1 WO2020119636 A1 WO 2020119636A1
Authority
WO
WIPO (PCT)
Prior art keywords
request
data
data items
packaged
calculate
Prior art date
Application number
PCT/CN2019/124018
Other languages
English (en)
French (fr)
Inventor
黄冬
范小朋
王洋
须成忠
Original Assignee
深圳先进技术研究院
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 深圳先进技术研究院 filed Critical 深圳先进技术研究院
Publication of WO2020119636A1 publication Critical patent/WO2020119636A1/zh

Links

Images

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network arrangements or protocols for supporting network services or applications
    • H04L67/50Network services
    • H04L67/60Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources

Definitions

  • the present invention relates to the field of computer technology, and in particular, to a data access request response method, device, terminal, and storage medium.
  • the invention provides a data access request response method, device, terminal and storage medium to solve the problems of excessive delay and excessive load of the existing mobile cloud service data access request response.
  • the present invention provides a data access request response method, which includes:
  • the greedy algorithm is used to calculate the optimal service strategy that can satisfy the request and respond to the request.
  • d i and d j represent two data items,
  • the correlation value exceeds the preset correlation threshold, if the two data items corresponding to the correlation value are not packaged with other data items, the two data items corresponding to the correlation value are packaged.
  • the method further includes:
  • an offline algorithm is used to calculate the optimal service strategy that can satisfy the request and respond to the request.
  • a greedy algorithm is used to calculate the optimal service strategy that can satisfy the request, and the step of responding to the request includes:
  • the present invention also provides a data access request response device, which includes:
  • the packaging confirmation module is used to confirm whether the target data item has been packaged after receiving the request to access the target data item
  • the data package confirmation module is used to confirm the data package corresponding to the target data item when the target data item has been packaged
  • the first judgment module is used to judge whether the remaining data items in the data packet are requested to be accessed
  • the first response module is used to calculate the optimal service strategy that can satisfy the request when the rest of the data items in the data packet are requested to be accessed, and respond to the request;
  • the second response module is used to calculate the optimal service strategy that can satisfy the request when the rest of the data items in the data packet are not accessed by the request, and respond to the request.
  • the correlation calculation module is used to obtain all data items stored in the server and calculate the correlation value between all data items, Among them, d i and d j represent two data items,
  • the second judgment module is used to judge whether the correlation value exceeds a preset correlation threshold
  • the data packaging module is used to package the two data items corresponding to the correlation value if the two data items corresponding to the correlation value are not packaged with other data items when the correlation value exceeds the preset correlation threshold.
  • the third response module is used to calculate an optimal service strategy that can satisfy the request by using an offline algorithm when the target data item is not packaged, and respond to the request.
  • the second response module includes:
  • the calculation unit is used to calculate the service cost of the cache service strategy, migration service strategy, and direct packet service strategy respectively;
  • the selection unit is used to select the service strategy with the lowest service cost to respond to the request.
  • the present invention also provides a terminal, which includes a memory and a processor, the processor is coupled to the memory, and the memory stores a computer program that can run on the processor;
  • the processor executes the computer program, it implements any of the steps in the above data access request response method.
  • the present invention also provides a storage medium on which a computer program is stored, which is characterized in that when the computer program is executed by a processor, any of the steps in the above data access request response method is implemented.
  • the present invention confirms whether the accessed target data item has been packaged.
  • different service strategies are adopted according to the packaging situation to meet the data access request in different situations.
  • the response time of data access requests is reduced, the load is reduced, the service quality is improved, and the user experience is improved.
  • FIG. 1 is a schematic flowchart of a first embodiment of a data access request response method of the present invention
  • FIG. 2 is a schematic flowchart of a second embodiment of a data access request response method of the present invention.
  • FIG. 3 is a schematic flowchart of a third embodiment of a data access request response method of the present invention.
  • FIG. 4 is a schematic flowchart of a fourth embodiment of a data access request response method of the present invention.
  • FIG. 5 is a schematic diagram of functional modules of a first embodiment of a device for responding to a data access request according to the present invention
  • FIG. 6 is a schematic diagram of functional modules of a second embodiment of a device for responding to a data access request according to the present invention.
  • FIG. 7 is a schematic diagram of functional modules of a third embodiment of a device for responding to a data access request according to the present invention.
  • FIG. 8 is a schematic diagram of functional modules of a fourth embodiment of a device for responding to a data access request according to the present invention.
  • FIG. 9 is a schematic diagram of an embodiment of a terminal of the present invention.
  • FIG. 1 shows an embodiment of the data access request response method of the present invention.
  • the data access request response method includes the following steps:
  • Step S1 after receiving the request to access the target data item, confirm whether the target data item has been packaged.
  • step S2 is executed.
  • a data access request will access multiple data items.
  • Step S2 confirm the data packet corresponding to the target data item.
  • the data packet corresponding to the target data item is confirmed, and the remaining data items in the data packet are confirmed.
  • Step S3 Determine whether the remaining data items in the data packet are requested to be accessed. If yes, go to step S4; if no, go to step S5.
  • step S4 an offline algorithm is used to calculate an optimal service strategy that can satisfy the request and respond to the request.
  • the data package with two data items is also taken as an example for illustration.
  • the calculation of the service cost can be completed by the following cost calculation model:
  • ri (si, ti, Di)
  • the mathematical expression is as follows:
  • S and T represent the cache cost per unit time on each server and the migration cost of data items between servers
  • is a preset discount factor, usually, ⁇ takes 0.8.
  • step S5 a greedy algorithm is used to calculate an optimal service strategy that can satisfy the request and respond to the request.
  • a greedy algorithm is used to calculate all service strategies that can satisfy the request, and The service strategy with the lowest service cost and cost is selected as the optimal service strategy to respond to the request.
  • the other data items in the data package corresponding to the target data items are confirmed Whether they are all accessed by the request, if so, call this packet, which is lower than the service cost required to call each data item in the packet separately, if not, then use the greedy algorithm to confirm the optimal service strategy. It should be requested.
  • the final service cost can be lower, thereby reducing the response time of the data access request, reducing the load, and improving the quality of service. At the same time improve the user experience.
  • step S1 before responding to the data access request, the data items stored in the server also need to be packaged. Therefore, based on the above embodiment, in other embodiments, as shown in FIG. 2, before step S1, the following items are included: step:
  • Step S10 Obtain all data items stored in the server, and calculate correlation values between all data items.
  • d i and d j represent two data items,
  • the data correlation should not only reflect the number of times the two data items co-occur, but should also be able to express the two data items
  • the number of simultaneous occurrences accounts for the proportion of the total occurrences of these two data items. Therefore, the data correlation between all data items is confirmed by the above correlation value calculation formula.
  • Step S11 Determine whether the correlation value exceeds a preset correlation threshold. When the correlation value exceeds the preset correlation threshold, step S12 is executed.
  • the correlation value exceeds a preset correlation threshold, and when the correlation value exceeds the preset correlation threshold, the two data items corresponding to the correlation value are explained
  • the data has a high degree of data correlation and can be packaged; when the correlation value does not exceed the preset correlation threshold, it means that the two data items corresponding to the correlation value have a low degree of data correlation and do not need to be packaged.
  • the preset relevant threshold is preset.
  • step S12 if the two data items corresponding to the correlation value are not packaged with other data items, the two data items corresponding to the correlation value are packaged.
  • the two data items corresponding to the correlation value can be packaged.
  • confirm that the correlation value exceeds the preset correlation threshold After that, it is necessary to determine whether the two data items corresponding to the correlation value have been packaged with other data items; if so, the two data items are not packaged to avoid repeated packing of the data items; if not, the two data items are packaged Items.
  • the final packaging result may be that 1 and 5 are packaged as a data packet, 4 and 6 are packaged as a data packet, 2, 3, 7, 8, 9, 10 are not
  • data items 1 and 5 are packaged together for service
  • data items 4 and 6 are packaged together for service
  • data items 2, 3, 7, 8, 9, 10 are still separate services.
  • the correlation value between the data items is calculated according to the number of times the two data items co-occur and the number of simultaneous occurrences of the two data items accounts for the total number of occurrences of the two data items, and according to the correlation value
  • the size of the data confirms whether the two data items need to be packed.
  • the data packaging strategy described in this embodiment is applicable to the packaging of two data items. In some embodiments, it is also applicable to the packaging of multiple data items. The number of data items in the data package is not limited.
  • step S1 when the target data item is not packaged, after step S1, it further includes:
  • Step S20 an offline algorithm is used to calculate an optimal service strategy that can satisfy the request, and the request is responded to.
  • the server strategy with the lowest service cost is selected as the optimal service strategy to respond to the request.
  • the service cost is The price when serving alone.
  • step S5 includes:
  • Step S30 Calculate the service cost of the cache service strategy, migration service strategy, and direct packet service strategy respectively.
  • the first service cost of the cache service strategy, the second service cost of the migration service strategy, and the third service cost of the direct data packet service strategy are calculated.
  • the cache service strategy refers to satisfying the request by caching data on the same server
  • the migration service strategy refers to performing data migration from another server to satisfy the request
  • the direct packet service strategy refers to directly uploading target data items To satisfy the request.
  • step S31 a service strategy with the lowest service cost is selected to respond to the request.
  • the strategy with the lowest service cost is selected as the optimal strategy to respond to the request.
  • FIG. 5 shows an embodiment of the data access request response device of the present invention.
  • the data access request response device includes a packaging confirmation module 10, a data packet confirmation module 11, a first judgment module 12, a first response module 13 and a second response module 14.
  • the packaging confirmation module 10 is used to confirm whether the target data item has been packaged after receiving the request to access the target data item; the data package confirmation module 11 is used to confirm that the target data item corresponds to when the target data item has been packaged.
  • the first judgment module 12 is used to judge whether the remaining data items in the data packet are requested to be accessed; the first response module 13 is used to use the offline algorithm when the remaining data items in the data packet are all requested to be accessed Calculate the optimal service strategy that can satisfy the request and respond to the request; the second response module 14 is used to calculate the optimal service strategy that can satisfy the request when the remaining data items in the data packet are not accessed by the request. And respond to requests.
  • the data access request response device further includes a correlation calculation module 20, a second judgment module 21, and a data packaging module 22.
  • the correlation calculation module 20 is used to obtain all the data items stored in the server and calculate the correlation value between all the data items, Among them, d i and d j represent two data items,
  • the data access request response device further includes a third response module 30, which is used to calculate the content that can be satisfied by using an offline algorithm when the target data item is not packaged. Request the optimal service strategy and respond to the request.
  • the second response module 14 includes a calculation unit 141 and a selection unit 142.
  • the calculation unit 141 is used to calculate the service cost of the cache service strategy, migration service strategy, and direct packet service strategy respectively; the selection unit 142 is used to select the service strategy with the lowest service cost to respond to the request.
  • FIG. 9 shows a schematic block diagram provided by an embodiment of a terminal of the present invention.
  • the terminal in this embodiment includes: one or at least two processors 80, a memory 81, and a processor stored in the memory 81 and available in the processor Computer program 810 running on 80.
  • the processor 80 executes the computer program 810, it implements the steps in the data access request response method described in the above embodiment, for example, steps S1 to S5 shown in FIG. 1.
  • the processor 80 executes the computer program 810, the functions of each module/unit in the embodiment of the data access request response device described above, for example, the functions of the module 10-module 14 shown in FIG. 5 are realized.
  • the computer program 810 may be divided into one or more modules/units, and the one or more modules/units are stored in the memory 81 and executed by the processor 80 to complete the present application.
  • the one or more modules/units may be a series of computer program instruction segments capable of performing specific functions. The instruction segments are used to describe the execution process of the computer program 810 in the terminal.
  • the terminal includes but is not limited to the processor 80 and the memory 81.
  • FIG. 9 is only an example of a terminal, and does not constitute a limitation on the terminal, and may include more or fewer components than those illustrated, or combine certain components, or different components, such as a terminal It can also include input devices, output devices, network access devices, buses, etc.
  • the processor 80 may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processors, digital signal processors (Digital Signal Processors, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), ready-made Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • the general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
  • the memory 81 may be a read-only memory, a static storage device that can store static information and instructions, a random access memory, or a dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory, a read-only optical disc , Or other optical disk storage, optical disk storage, magnetic disk storage media, or other magnetic storage devices.
  • the memory 81 and the processor 80 may be connected through a communication bus, or may be integrated with the processor 80.
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are only schematic.
  • the division of modules or units is only a division of logical functions.
  • there may be other divisions for example, multiple units or components may be combined or Can be integrated into another device, or some features can be ignored, or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above integrated unit may be implemented in the form of hardware or software functional unit.
  • An embodiment of the present application further provides a storage medium for storing a computer program, which includes program data designed to execute the above-described data access request response method embodiment of the present application.
  • a storage medium for storing a computer program, which includes program data designed to execute the above-described data access request response method embodiment of the present application.
  • the integrated module/unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.
  • the present application can implement all or part of the processes in the methods of the above embodiments, or it can be completed by instructing related hardware through a computer program 810.
  • the computer program 810 can be stored in a computer-readable storage medium, and the computer program When executed by the processor 80, 810 may implement the steps of the foregoing method embodiments.
  • the computer program 810 includes computer program code.
  • the computer program code may be in the form of source code, object code, executable file, or some intermediate form.
  • Computer-readable media may include: any entity or device capable of carrying computer program code, recording media, U disk, removable hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access Memory (RAM, Random Access), electrical carrier signal, telecommunication signal, software distribution media, etc.
  • ROM Read-Only Memory
  • RAM random access Memory
  • electrical carrier signal telecommunication signal
  • software distribution media etc.
  • the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in jurisdictions.
  • the computer-readable medium does not include It is electric carrier signal and telecommunication signal.

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)
  • Information Transfer Between Computers (AREA)

Abstract

本发明公开了一种数据访问请求响应方法、装置、终端和存储介质,该方法包括:接收到访问目标数据项的请求后,确认目标数据项是否已被打包;当目标数据项已被打包时,确认目标数据项对应的数据包;判断数据包中的其余数据项是否被请求访问;若是,则采用离线算法计算出能够满足请求的最优服务策略,并响应请求;若否,则采用贪心算法计算出能够满足请求的最优服务策略,并响应请求。本发明基于数据打包服务的服务代价低于单独服务的服务代价这一事实,根据打包情况分别采取不同的服务策略来满足不同情况下的数据请求,以使得最终的服务代价较低,提高了服务质量,减少了网络延迟和负载。

Description

数据访问请求响应方法、装置、终端和存储介质 技术领域
本发明涉及计算机技术领域,尤其涉及一种数据访问请求响应方法、装置、终端和存储介质。
背景技术
据2018年6月第42次中国互联网发展状况统计报告显示,我国网民拥有移动终端的规模已经达到7.88亿,使用移动设备上网的人群所占的比例提升至98.3%,移动设备已经取代电脑成为网络用户获取信息的最主要平台。随着移动设备的普及,移动云计算也得到了广泛的关注,并逐渐成为云服务的一种主要形式,越来越多的出现在人们的生活之中,比如远程管理、无限推送、存储备份、在线搜索等。由于移动云服务多为访问时间敏感的服务,如何降低服务的延迟、减少网络负载,从而最大化提高数据访问效率,对提高服务质量,降低服务成本,改善用户体验来说始终是移动云计算一个至关重要的问题。
发明内容
本发明提供了一种数据访问请求响应方法、装置、终端和存储介质,以解决现有的移动云服务数据访问请求响应延迟过高,负载过大的问题。
为了解决上述问题,本发明提供了一种数据访问请求响应方法,其包括:
接收到访问目标数据项的请求后,确认目标数据项是否已被打包;
当目标数据项已被打包时,确认目标数据项对应的数据包;
判断数据包中的其余数据项是否被请求访问;
若是,则采用离线算法计算出能够满足请求的最优服务策略,并响应请求;
若否,则采用贪心算法计算出能够满足请求的最优服务策略,并响应请求。
作为本发明的进一步改进,接收到访问目标数据项的请求后,确认目标数据项是否已被打包的步骤之前,还包括:
获取服务器中存储的所有数据项,并计算所有数据项之间的相关性值,
Figure PCTCN2019124018-appb-000001
其中,d i和d j代表两个数据项,|d i∩d j|代表所有请求中数据项d i和d j共同出现的请求的个数,|d i∪d j|代表所有包含d i或d j的请求的个数;
判断相关性值是否超过预设相关阈值;
当相关性值超过预设相关阈值时,若相关性值对应的两个数据项未与其他数据项打包,则将相关性值对应的两个数据项进行打包。
作为本发明的进一步改进,,确认所述目标数据项是否已被打包的步骤之后,还包括:
当目标数据项未被打包时,采用离线算法计算出能够满足请求的最优服务策略,并响应请求。
作为本发明的进一步改进,采用贪心算法计算出能够满足请求的最优服务策略,并响应请求的步骤,包括:
分别计算缓存服务策略、迁移服务策略、直接数据包服务策略的服务代价;
选取服务代价最低的服务策略响应请求。
为了解决上述问题,本发明还提供了一种数据访问请求响应装置,其包括:
打包确认模块,用于接收到访问目标数据项的请求后,确认目标数据项是 否已被打包;
数据包确认模块,用于当目标数据项已被打包时,确认目标数据项对应的数据包;
第一判断模块,用于判断数据包中的其余数据项是否被请求访问;
第一响应模块,用于当数据包中的其余数据项均被请求访问时,采用离线算法计算出能够满足请求的最优服务策略,并响应请求;
第二响应模块,用于当数据包中的其余数据项未均被请求访问时,采用贪心算法计算出能够满足请求的最优服务策略,并响应请求。
作为本发明的进一步改进,其还包括:
相关性计算模块,用于获取服务器中存储的所有数据项,并计算所有数据项之间的相关性值,
Figure PCTCN2019124018-appb-000002
其中,d i和d j代表两个数据项,|d i∩d j|代表所有请求中数据项d i和d j共同出现的请求的个数,|d i∪d j|代表所有包含d i或d j的请求的个数;
第二判断模块,用于判断相关性值是否超过预设相关阈值;
数据打包模块,用于当相关性值超过预设相关阈值时,若相关性值对应的两个数据项未与其他数据项打包,则将相关性值对应的两个数据项进行打包。
作为本发明的进一步改进,其还包括:
第三响应模块,用于当目标数据项未被打包时,采用离线算法计算出能够满足请求的最优服务策略,并响应请求。
作为本发明的进一步改进,第二响应模块包括:
计算单元,用于分别计算缓存服务策略、迁移服务策略、直接数据包服务策略的服务代价;
选取单元,用于选取服务代价最低的服务策略响应请求。
为了解决上述问题,本发明还提供了一种终端,其包括存储器和处理器,处理器耦接存储器,存储器上存储有可在处理器上运行的计算机程序;
处理器执行计算机程序时,实现上述任一项数据访问请求响应方法中的步骤。
为了解决上述问题,本发明还提供了一种存储介质,其上存储有计算机程序,其特征在于,计算机程序被处理器执行时,实现上述任一项数据访问请求响应方法中的步骤。
相比于现有技术,本发明通过确认被访问的目标数据项是否已被打包,当目标数据项已被打包时,根据打包情况分别采取不同的服务策略来满足不同情况下的数据访问请求,而基于数据打包服务的服务代价低于单独服务的服务代价这一事实,因此,根据打包情况分别采取不同的服务策略来满足不同情况下的数据请求,可以使得最终的服务代价较低,从而减少了数据访问请求响应时间,降低了负载,提高了服务质量,提升了用户体验。
附图说明
图1为本发明数据访问请求响应方法第一个实施例的流程示意图;
图2为本发明数据访问请求响应方法第二个实施例的流程示意图;
图3为本发明数据访问请求响应方法第三个实施例的流程示意图;
图4为本发明数据访问请求响应方法第四个实施例的流程示意图;
图5为本发明数据访问请求响应装置第一个实施例的功能模块示意图;
图6为本发明数据访问请求响应装置第二个实施例的功能模块示意图;
图7为本发明数据访问请求响应装置第三个实施例的功能模块示意图;
图8为本发明数据访问请求响应装置第四个实施例的功能模块示意图;
图9为本发明终端一个实施例的框架示意图。
具体实施方式
为了使本发明的目的、技术方案及优点更加清楚明白,以下结合附图及实施例,对本发明进行进一步详细说明。应当理解,此处所描述的具体实施例仅仅用以解释本发明,并不用来限定本发明。
图1展示了本发明数据访问请求响应方法的一个实施例。本实施例中,如图1所示,该数据访问请求响应方法包括以下步骤:
步骤S1,接收到访问目标数据项的请求后,确认目标数据项是否已被打包。当目标数据项已被打包时,执行步骤S2。
通常地,一个数据访问请求会访问到多个数据项,在本实施例中,接收到数据访问请求之后,首先确认请求中请求访问的数据项具体为哪些数据项,并确定其中之一为目标数据项,再确认该目标数据项是否已被打包。
步骤S2,确认目标数据项对应的数据包。
具体地,当目标数据项已被打包时,则确认该目标数据项对应的数据包,并确认该数据包中的其余数据项。
步骤S3,判断数据包中的其余数据项是否被请求访问。若是,则执行步骤S4;若否,则执行步骤S5。
具体地,以打包有两个数据项的数据包为例进行说明,在确认其中一个数据项为该请求访问的目标数据项之后,需要判断另一数据项是否同样为该请求访问的对象。
步骤S4,采用离线算法计算出能够满足请求的最优服务策略,并响应请求。
具体地,当数据包中的其余数据项均被该请求访问时,根据离线算法计算出所有能够满足该请求的服务策略,并从中挑选出服务代价最低的服务器策略作为最优服务策略来响应该请求。
进一步的,同样以打包有两个数据项的数据包为例进行说明,针对于该打包的两个数据项,其中,服务代价的计算可通过下述代价计算模型来完成:
以rn=(sn,tn,Dn)表示一个请求,其代表在tn时刻服务器sn上有一个请求访问数据集的一个真子集Dn,
Figure PCTCN2019124018-appb-000003
假设ri=(si,ti,Di),rj=(sj,tj,Dj)分布代表两个不同的请求,该两个请求都访问了数据项dp,我们用
Figure PCTCN2019124018-appb-000004
表示从ri到rj的服务代价,其数学表达式如下:
Figure PCTCN2019124018-appb-000005
其中,S和T分别代表每个服务器上单位时间的缓存代价和数据项在服务器之间的迁移代价,ε用来指示rj是通过哪种方式服务的,当si=sj时,ε=0,表示对于数据项dp来说,rj和ri发生在同一个服务器上,rj直接通过数据缓存服务来满足;当si≠sj,ε=1,表示对于数据项dp来说,rj和ri分别发生在两个服务器上,数据项dp先在si上缓存一段时间(ti时间到tj时间),然后通过一个数据迁移服务来满足sj上的rj。
而假如ri和rj同时请求了d1和d2,则将两个数据项打包从r1到r2比单独的分别用d1和d2来满足r1和r2代价上更优,所以,对于数据单独服务和打包服务,参考下表1:
表1 数据单独服务与打包服务代价模型
Figure PCTCN2019124018-appb-000006
Figure PCTCN2019124018-appb-000007
其中,α为预设打折因子,通常地,α取0.8。
由上表1可知,对于两个数据项dp和dq,单独服务时ri到rj(ri和rj同时请求了数据项dp和dq)的代价为
Figure PCTCN2019124018-appb-000008
其中
Figure PCTCN2019124018-appb-000009
Figure PCTCN2019124018-appb-000010
分别表示从ri=(si,ti,Di)到rj=(sj,tj,Dj)(tj>ti)服务数据项dp和dq的代价。根据上述代价计算模型可知,本实施例中,如果这两个数据项打包服务,其服务代价可表示为α*2*
Figure PCTCN2019124018-appb-000011
或者是α*2*
Figure PCTCN2019124018-appb-000012
步骤S5,采用贪心算法计算出能够满足请求的最优服务策略,并响应请求。
具体地,同样以数据包中打包有两个数据项为例进行说明,当数据包中的另一个数据项未被该请求访问时,采用贪心算法计算出所有能够满足该请求的服务策略,并从中选取服务代价成本最低的服务策略作为最优服务策略来并响应请求。
本实施例通过分别确认数据访问请求中需要访问的多个目标数据项是已打包或单独存在的,针对于已打包的目标数据项,则确认该目标数据项对应的数据包中其他的数据项是否均被该请求访问,若是,则调用此数据包,其比分别调用该数据包中的每个数据项所需的服务代价低,若不是,则采用贪心算法确认最优的服务策略来响应该请求,通过根据打包情况分别采取不同的服务策略来满足不同情况下的数据访问请求,可以使得最终的服务代价较低,从而减少了数据访问请求响应时间,并降低负载,提高了服务质量,同时提升了用户体验。
进一步地,在响应数据访问请求之前,还需要对服务器中存储的数据项进 行打包,因此,上述实施例的基础上,其他实施例中,如图2所示,在步骤S1之前,还包括以下步骤:
步骤S10,获取服务器中存储的所有数据项,并计算所有数据项之间的相关性值。
需要说明的是,
Figure PCTCN2019124018-appb-000013
其中,d i和d j代表两个数据项,|d i∩d j|代表所有请求中数据项d i和d j共同出现的请求的个数,|d i∪d j|代表所有包含d i或d j的请求的个数。
具体地,不同数据项之间是否需要进行打包处理需要通过数据项之间的相关性来确认,而数据相关性不仅要能反映两个数据项共同出现的次数,更应该能够表示两个数据项同时出现的次数占这两个数据项一共出现次数的比例,因此,通过上述相关性值计算公式来确认所有数据项之间的数据相关性。
步骤S11,判断相关性值是否超过预设相关阈值。当相关性值超过预设相关阈值时,执行步骤S12。
具体地,在计算出数据项之间的相关性值之后,判断该相关性值是否超过预设相关阈值,当相关性值超过预设相关阈值时,说明该相关性值对应的两个数据项的数据相关性程度较高,可进行打包;当相关性值未超过预设相关阈值时,说明该相关性值对应的两个数据项的数据相关性程度较低,不需要进行打包。其中,该预设相关阈值为预先设定。
步骤S12,若相关性值对应的两个数据项未与其他数据项打包,则将相关性值对应的两个数据项进行打包。
具体地,当相关性值超过预设相关阈值时,该相关性值对应的两个数据项即可进行打包,但是,为了避免对数据项进行重复打包,在确认相关性值超过 预设相关阈值之后,需要判断该相关性值对应的两个数据项是否已经与其他数据项打包;若是,则将该两个数据项不进行打包,以避免数据项重复打包;若否,则将两个数据项进行打包。例如:一共10个数据项(1-10),最后得到的打包结果可能是1和5打包为一个数据包,4和6打包为一个数据包,2、3、7、8、9、10不进行打包,在响应数据访问请求是,数据项1和5打包一起服务,数据项4和6打包在一起服务,而数据项2、3、7、8、9、10还是单独服务。
本实施例通过根据两个数据项共同出现的次数以及两个数据项同时出现的次数占这两个数据项一共出现次数的比例,计算出数据项之间的相关性值,并根据相关性值的大小确认是否需要将两个数据项进行打包。
本实施例所述的数据打包策略适用于两个数据项的打包,在一些实施例中,其同样适用于多数据项的打包,数据包中的数据项的数量不做限制。
进一步的,如图3所示,当目标数据项未被打包时,在步骤S1之后,还包括:
步骤S20,采用离线算法计算出能够满足请求的最优服务策略,并响应请求。
具体地,当目标数据项未被打包时,根据离线算法计算出所有能够满足该请求的服务策略,并从中挑选出服务代价最低的服务器策略作为最优服务策略来响应该请求,其服务代价即单独服务时的代价。
进一步的,如图4所示,步骤S5包括:
步骤S30,分别计算缓存服务策略、迁移服务策略、直接数据包服务策略的服务代价。
具体地,当数据包中的另一个数据项未被该请求访问时,计算出缓存服务 策略的第一服务代价、迁移服务策略的第二服务代价、直接数据包服务策略的第三服务代价。其中,缓存服务策略是指通过同一个服务器上的缓存数据来满足该请求,迁移服务策略是指从另一个服务器上进行数据迁移来满足该请求,直接数据包服务策略是指直接上传目标数据项来满足该请求。
步骤S31,选取服务代价最低的服务策略响应请求。
具体地,在获得缓存服务策略、迁移服务策略、直接数据包服务策略的服务代价之后,选取其中服务代价最低的策略作为最优策略来响应该请求。
图5展示了本发明数据访问请求响应装置的一个实施例。如图5所示,该数据访问请求响应装置包括打包确认模块10、数据包确认模块11、第一判断模块12、第一响应模块13和第二响应模块14。
其中,打包确认模块10,用于接收到访问目标数据项的请求后,确认目标数据项是否已被打包;数据包确认模块11,用于当目标数据项已被打包时,确认目标数据项对应的数据包;第一判断模块12,用于判断数据包中的其余数据项是否被请求访问;第一响应模块13,用于当数据包中的其余数据项均被请求访问时,采用离线算法计算出能够满足请求的最优服务策略,并响应请求;第二响应模块14,用于当数据包中的其余数据项未被请求访问时,采用贪心算法计算出能够满足请求的最优服务策略,并响应请求。
上述实施例的基础上,其他实施例中,如图6所示,该数据访问请求响应装置还包括相关性计算模块20、第二判断模块21和数据打包模块22。
其中,相关性计算模块20,用于获取服务器中存储的所有数据项,并计算所有数据项之间的相关性值,
Figure PCTCN2019124018-appb-000014
其中,d i和d j代表两个数据项,|d i∩d j|代表所有请求中数据项d i和d j共同出现的请 求的个数,|d i∪d j|代表所有包含d i或d j的请求的个数;第二判断模块21,用于判断相关性值是否超过预设相关阈值;数据打包模块22,用于当相关性值超过预设相关阈值时,若相关性值对应的两个数据项未与其他数据项打包,则将相关性值对应的两个数据项进行打包。
上述实施例的基础上,其他实施例中,如图7所示,该数据访问请求响应装置还包括第三响应模块30,用于当目标数据项未被打包时,采用离线算法计算出能够满足请求的最优服务策略,并响应请求。
上述实施例的基础上,其他实施例中,如图8所示,第二响应模块14包括计算单元141和选取单元142。
其中,计算单元141,用于分别计算缓存服务策略、迁移服务策略、直接数据包服务策略的服务代价;选取单元142,用于选取服务代价最低的服务策略响应请求。
关于上述实施例中数据访问请求响应装置各模块实现技术方案的其他细节,可参见上述实施例中的数据访问请求响应方法中的描述,此处不再赘述。
需要说明的是,本说明书中的各个实施例均采用递进的方式描述,每个实施例重点说明的都是与其他实施例的不同之处,各个实施例之间相同相似的部分互相参见即可。对于装置类实施例而言,由于其与方法实施例基本相似,所以描述的比较简单,相关之处参见方法实施例的部分说明即可。
图9展示了本发明终端一个实施例提供的示意框图,参见图9,该实施例中的终端包括:一个或至少两个处理器80、存储器81以及存储在该存储器81中并可在处理器80上运行的计算机程序810。处理器80执行计算机程序810时,实现上述实施例描述的数据访问请求响应方法中的步骤,例如:图1所示的步骤S1-步骤S5。或者,处理器80执行计算机程序810时,实现上述数据 访问请求响应装置实施例中各模块/单元的功能,例如:图5所示模块10-模块14的功能。
计算机程序810可以被分割成一个或多个模块/单元,一个或者多个模块/单元被存储在存储器81中,并由处理器80执行,以完成本申请。一个或多个模块/单元可以是能够完成特定功能的一系列计算机程序指令段,该指令段用于描述计算机程序810在终端中的执行过程。
终端包括但不仅限于处理器80、存储器81。本领域技术人员可以理解,图9仅仅是终端的一个示例,并不构成对终端的限定,可以包括比图示更多或更少的部件,或者组合某些部件,或者不同的部件,例如终端还可以包括输入设备、输出设备、网络接入设备、总线等。
处理器80可以是中央处理单元(Central Processing Unit,CPU),还可以是其他通用处理器、数字信号处理器(Digital Signal Processor,DSP)、专用集成电路(Application Specific Integrated Circuit,ASIC)、现成可编程门阵列(Field-Programmable Gate Array,FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
存储器81可以是只读存储器、可存储静态信息和指令的静态存储设备、随机存取存储器、或者可存储信息和指令的动态存储设备,也可以是电可擦可编程只读存储器、只读光盘、或其他光盘存储、光碟存储、磁盘存储介质或者其他磁存储设备。存储器81与处理器80可以通过通信总线相连接,也可以和处理器80集成在一起。
在上述实施例中,对各个实施例的描述都各有侧重,某个实施例中没有详述或记载的部分,可以参见其它实施例的相关描述。
本领域普通技术人员可以意识到,结合本文中所公开的实施例描述的各示例的单元及算法步骤,能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行,取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能,但是这种实现不应认为超出本申请的范围。
在本申请所提供的实施例中,应该理解到,所揭露的装置和方法,可以通过其它的方式实现。例如,以上所描述的装置实施例仅仅是示意性的,例如,模块或单元的划分,仅仅为一种逻辑功能划分,实际实现时可以有另外的划分方式,例如多个单元或组件可以结合或者可以集成到另一个装置,或一些特征可以忽略,或不执行。另一点,所显示或讨论的相互之间的耦合或直接耦合或通讯连接可以是通过一些接口,装置或单元的间接耦合或通讯连接,可以是电性,机械或其它的形式。
另外,在本申请各个实施例中的各功能单元可以集成在一个处理单元中,也可以是各个单元单独物理存在,也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现,也可以采用软件功能单元的形式实现。
本申请实施例还提供了一种存储介质,用于存储计算机程序,其包含用于执行本申请上述数据访问请求响应方法实施例所设计的程序数据。通过执行该存储介质中存储的计算机程序,可以实现本申请提供的数据访问请求响应方法。
集成的模块/单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时,可以存储在一个计算机可读取存储介质中。基于这样的理解,本申请实现上述实施例方法中的全部或部分流程,也可以通过计算机程序810来指令相关的硬件来完成,计算机程序810可存储于一计算机可读存储介质中,该 计算机程序810在被处理器80执行时,可实现上述各个方法实施例的步骤。其中,计算机程序810包括计算机程序代码,计算机程序代码可以为源代码形式、对象代码形式、可执行文件或某些中间形式等。计算机可读介质可以包括:能够携带计算机程序代码的任何实体或装置、记录介质、U盘、移动硬盘、磁碟、光盘、计算机存储器、只读存储器(ROM,Read-Only Memory)、随机存取存储器(RAM,Random Access Memory)、电载波信号、电信信号以及软件分发介质等。需要说明的是,计算机可读介质包含的内容可以根据司法管辖区内立法和专利实践的要求进行适当的增减,例如在某些司法管辖区,根据立法和专利实践,计算机可读介质不包括是电载波信号和电信信号。
以上对发明的具体实施方式进行了详细说明,但其只作为范例,本发明并不限制于以上描述的具体实施方式。对于本领域的技术人员而言,任何对该发明进行的等同修改或替代也都在本发明的范畴之中,因此,在不脱离本发明的精神和原则范围下所作的均等变换和修改、改进等,都应涵盖在本发明的范围内。

Claims (10)

  1. 一种数据访问请求响应方法,其特征在于,其包括:
    接收到访问目标数据项的请求后,确认所述目标数据项是否已被打包;
    当所述目标数据项已被打包时,确认所述目标数据项对应的数据包;
    判断所述数据包中的其余数据项是否被所述请求访问;
    若是,则采用离线算法计算出能够满足所述请求的最优服务策略,并响应所述请求;
    若否,则采用贪心算法计算出能够满足所述请求的最优服务策略,并响应所述请求。
  2. 根据权利要求1所述的数据访问请求响应方法,其特征在于,所述接收到访问目标数据项的请求后,确认所述目标数据项是否已被打包的步骤之前,还包括:
    获取服务器中存储的所有数据项,并计算所有数据项之间的相关性值,所述
    Figure PCTCN2019124018-appb-100001
    其中,d i和d j代表两个数据项,|d i∩d j|代表所有请求中数据项d i和d j共同出现的请求的个数,|d i∪d j|代表所有包含d i或d j的请求的个数;
    判断所述相关性值是否超过预设相关阈值;
    当所述相关性值超过预设相关阈值时,若所述相关性值对应的两个数据项未与其他数据项打包,则将所述相关性值对应的两个数据项进行打包。
  3. 根据权利要求1所述的数据访问请求响应方法,其特征在于,所述,确认所述目标数据项是否已被打包的步骤之后,还包括:
    当所述目标数据项未被打包时,采用离线算法计算出能够满足所述请求的 最优服务策略,并响应所述请求。
  4. 根据权利要求1所述的数据访问请求响应方法,其特征在于,所述采用贪心算法计算出能够满足所述请求的最优服务策略,并响应所述请求的步骤,包括:
    分别计算缓存服务策略、迁移服务策略、直接数据包服务策略的服务代价;
    选取所述服务代价最低的服务策略响应所述请求。
  5. 一种数据访问请求响应装置,其特征在于,其包括:
    打包确认模块,用于接收到访问目标数据项的请求后,确认所述目标数据项是否已被打包;
    数据包确认模块,用于当所述目标数据项已被打包时,确认所述目标数据项对应的数据包;
    第一判断模块,用于判断所述数据包中的其余数据项是否被所述请求访问;
    第一响应模块,用于当所述数据包中的其余数据项均被所述请求访问时,采用离线算法计算出能够满足所述请求的最优服务策略,并响应所述请求;
    第二响应模块,用于当所述数据包中的其余数据项未被所述请求访问时,采用贪心算法计算出能够满足所述请求的最优服务策略,并响应所述请求。
  6. 根据权利要求5所述的数据访问请求响应装置,其特征在于,其还包括:
    相关性计算模块,用于获取服务器中存储的所有数据项,并计算所有数据项之间的相关性值,所述
    Figure PCTCN2019124018-appb-100002
    其中,d i和d j代表两个数据项,|d i∩d j|代表所有请求中数据项d i和d j共同出现的请求的个数,|d i∪d j|代表所有包含d i或d j的请求的个数;
    第二判断模块,用于判断所述相关性值是否超过预设相关阈值;
    数据打包模块,用于当所述相关性值超过预设相关阈值时,若所述相关性 值对应的两个数据项未与其他数据项打包,则将所述相关性值对应的两个数据项进行打包。
  7. 根据权利要求5所述的数据访问请求响应装置,其特征在于,其还包括:
    第三响应模块,用于当所述目标数据项未被打包时,采用离线算法计算出能够满足所述请求的最优服务策略,并响应所述请求。
  8. 根据权利要求5所述的数据访问请求响应装置,其特征在于,所述第二响应模块包括:
    计算单元,用于分别计算缓存服务策略、迁移服务策略、直接数据包服务策略的服务代价;
    选取单元,用于选取所述服务代价最低的服务策略响应所述请求。
  9. 一种终端,其特征在于,其包括存储器和处理器,所述处理器耦接所述存储器,所述存储器上存储有可在所述处理器上运行的计算机程序;
    所述处理器执行所述计算机程序时,实现权利要求1-4任一项所述数据访问请求响应方法中的步骤。
  10. 一种存储介质,其上存储有计算机程序,其特征在于,所述计算机程序被处理器执行时,实现权利要求1-4任一项所述数据访问请求响应方法中的步骤。
PCT/CN2019/124018 2018-12-13 2019-12-09 数据访问请求响应方法、装置、终端和存储介质 WO2020119636A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201811525615.0 2018-12-13
CN201811525615.0A CN109561152B (zh) 2018-12-13 2018-12-13 数据访问请求响应方法、装置、终端和存储介质

Publications (1)

Publication Number Publication Date
WO2020119636A1 true WO2020119636A1 (zh) 2020-06-18

Family

ID=65869981

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2019/124018 WO2020119636A1 (zh) 2018-12-13 2019-12-09 数据访问请求响应方法、装置、终端和存储介质

Country Status (2)

Country Link
CN (1) CN109561152B (zh)
WO (1) WO2020119636A1 (zh)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023087452A1 (zh) * 2021-11-17 2023-05-25 中国科学院深圳先进技术研究院 人工智能模型请求响应机制优化方法、系统、终端及介质

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109561152B (zh) * 2018-12-13 2020-07-24 深圳先进技术研究院 数据访问请求响应方法、装置、终端和存储介质

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103064927A (zh) * 2012-12-21 2013-04-24 曙光信息产业(北京)有限公司 分布式文件系统的数据访问方法和装置
WO2013177193A2 (en) * 2012-05-21 2013-11-28 Google Inc. Organizing data in a distributed storage system
CN105279240A (zh) * 2015-09-28 2016-01-27 暨南大学 客户端起源信息关联感知的元数据预取方法及系统
CN109561152A (zh) * 2018-12-13 2019-04-02 深圳先进技术研究院 数据访问请求响应方法、装置、终端和存储介质

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101252589B (zh) * 2008-03-25 2011-01-05 中国科学院计算技术研究所 数据缓存装置和采用该装置的网络存储系统及缓存方法
US8477730B2 (en) * 2011-01-04 2013-07-02 Cisco Technology, Inc. Distributed load management on network devices
CN102156730B (zh) * 2011-04-07 2013-03-20 江苏省电力公司 基于文件存储动态聚合的优化方法
CN103297485B (zh) * 2012-03-05 2016-02-24 日电(中国)有限公司 分布式缓存自动管理系统和分布式缓存自动管理方法
CN107526762A (zh) * 2017-02-28 2017-12-29 天津转知汇网络技术有限公司 服务端、多数据源搜索方法和系统

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013177193A2 (en) * 2012-05-21 2013-11-28 Google Inc. Organizing data in a distributed storage system
CN103064927A (zh) * 2012-12-21 2013-04-24 曙光信息产业(北京)有限公司 分布式文件系统的数据访问方法和装置
CN105279240A (zh) * 2015-09-28 2016-01-27 暨南大学 客户端起源信息关联感知的元数据预取方法及系统
CN109561152A (zh) * 2018-12-13 2019-04-02 深圳先进技术研究院 数据访问请求响应方法、装置、终端和存储介质

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
HUANG, DONG ET AL.: "DP_Greedy: A Two-Phase Caching Algorithm for Mobile Cloud Services", 2019 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING (CLUSTER), 7 November 2019 (2019-11-07), XP033647957, DOI: 20200226171508PX *
WANG, YANG ET AL.: "Data Caching in Next Generation Mobile Cloud Services, Online vs. Off-line", 46TH INTERNATIONAL CONFERENCE ON PARALLEL PROCESSING, 7 September 2017 (2017-09-07), XP033148497, DOI: 20200226171636PX *
黄冬 (HUANG, DONG): "基于数据相关性的移动云服务数据缓存研究 (Research on Data Caching Based on Data Correlation in Mobile Cloud Service)", 中国优秀硕士学位论文全文数据库 信息科技辑 (CHINESE MASTER’S THESES FULL-TEXT DATABASE, INFORMATION SCIENCE & TECHNOLOGY), no. 6, 15 June 2019 (2019-06-15), DOI: 20200226171913PX *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023087452A1 (zh) * 2021-11-17 2023-05-25 中国科学院深圳先进技术研究院 人工智能模型请求响应机制优化方法、系统、终端及介质

Also Published As

Publication number Publication date
CN109561152A (zh) 2019-04-02
CN109561152B (zh) 2020-07-24

Similar Documents

Publication Publication Date Title
US10684995B2 (en) Storage optimization in computing devices
TW202038173A (zh) 基於區塊鏈的資料處理系統、方法、計算設備及儲存媒體
WO2017114206A1 (zh) 短链接处理方法、装置及短链接服务器
CN110417879A (zh) 一种消息处理方法、装置、设备及存储介质
US8832218B2 (en) Determining priorities for cached objects to order the transfer of modifications of cached objects based on measured network bandwidth
CN110602156A (zh) 一种负载均衡调度方法及装置
WO2019128357A1 (zh) 图片请求方法、响应图片请求的方法及客户端
WO2019041738A1 (zh) 客户资源获取方法、装置、终端设备及存储介质
US20140067898A1 (en) Cost-aware cloud-based content delivery
CN109104336A (zh) 服务请求处理方法、装置、计算机设备及存储介质
WO2020119636A1 (zh) 数据访问请求响应方法、装置、终端和存储介质
WO2017054540A1 (zh) 一种数据处理方法、装置、服务器及控制器
WO2021258512A1 (zh) 数据的聚合处理装置、方法和存储介质
CN113392863A (zh) 一种机器学习训练数据集的获取方法、获取装置及终端
WO2016008338A1 (zh) 一种i/o请求处理方法及存储系统
CN111597213A (zh) 一种缓存方法、软件服务器及存储介质
WO2023116219A1 (zh) Cdn节点分配方法、装置、电子设备、介质及程序产品
WO2022121216A1 (zh) 一种数据处理方法、装置、终端和可读存储介质
CN110168513B (zh) 在不同存储系统中对大文件的部分存储
CN107797758B (zh) 数据存储方法、数据访问方法及装置
CN108804351B (zh) 一种缓存置换方法以及装置
CN111597041A (zh) 一种分布式系统的调用方法、装置、终端设备及服务器
AU2014349181A1 (en) Techniques to rate-adjust data usage with a virtual private network
CN107003980A (zh) 内容传送框架中的请求处理
CN113590699B (zh) 一种接口请求处理方法、系统及计算设备

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19896544

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205 DATED 03/11/2021)

122 Ep: pct application non-entry in european phase

Ref document number: 19896544

Country of ref document: EP

Kind code of ref document: A1