WO2021098403A1 - 资源分配方法、服务器及存储介质 - Google Patents

资源分配方法、服务器及存储介质 Download PDF

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Publication number
WO2021098403A1
WO2021098403A1 PCT/CN2020/120161 CN2020120161W WO2021098403A1 WO 2021098403 A1 WO2021098403 A1 WO 2021098403A1 CN 2020120161 W CN2020120161 W CN 2020120161W WO 2021098403 A1 WO2021098403 A1 WO 2021098403A1
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task
data transmission
uplink
temporary
downlink
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PCT/CN2020/120161
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English (en)
French (fr)
Inventor
何大治
徐胤
何雯
张奕喆
张祎蔚
张文军
牟博语
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中兴通讯股份有限公司
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Publication of WO2021098403A1 publication Critical patent/WO2021098403A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/53—Allocation or scheduling criteria for wireless resources based on regulatory allocation policies
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation

Definitions

  • the embodiments of the present application relate to the field of communication technology, and particularly relate to a resource allocation method, a server, and a storage medium.
  • MEC Mobile Edge ComKuting
  • MEC Mobile Edge ComKuting
  • MEC Mobile Edge ComKuting
  • the MEC server is close to the user terminal and has relatively strong computing power
  • the MEC can provide mobile users with low-latency and high-bandwidth services.
  • the transmission delay is an important part of the total system delay; the user unloads the task to the MEC server to perform the tasks including task upload, task calculation and result download.
  • the transmission delay of the upload and download process affects the MEC.
  • the total system delay has a great influence. With the continuous increase of MEC computing and offloading users, the total delay of the MEC system in the current half-duplex mode is also increasing, which seriously affects the timeliness of data transmission.
  • the purpose of the embodiments of the present application is to provide a resource allocation method, server, and storage medium, which can reduce the total system delay in the MEC scenario.
  • the embodiment of the present application provides a resource allocation method, including: identifying a user who has a communication requirement with a base station with a mobile edge computing MEC function; and grouping the user's uplink tasks and downlink tasks to obtain A plurality of task groups arranged in sequence to allow the base station to complete data transmission of the plurality of task groups in sequence in a time-division multiplexing manner in a full-duplex mode; wherein, each of the task groups includes At least one of the uplink task and the downlink task.
  • the uplink tasks and downlink tasks of the same MEC computing offload user are divided into different task groups, and the task group in which the uplink task is located is arranged in different task groups. In front of the task group where the down task is located.
  • An embodiment of the present application also provides a server, including: at least one processor; and, a memory communicatively connected with the at least one processor; wherein the memory stores the memory that can be executed by the at least one processor; Instructions, the instructions are executed by the at least one processor, so that the at least one processor can execute the foregoing method.
  • the embodiment of the present application also provides a computer-readable storage medium storing a computer program, wherein the computer program is executed by a processor to implement the above-mentioned resource allocation method.
  • Fig. 1 is a flowchart of a resource allocation method according to the first embodiment of the present application
  • Fig. 2 is a schematic diagram of communication between a user terminal and a base station in an MEC scenario according to the first embodiment of the present application;
  • Fig. 3 is a flowchart of a resource allocation method according to a second embodiment of the present application.
  • Fig. 4 is a block diagram of a server according to a third embodiment of the present application.
  • the first embodiment of the present application relates to a resource allocation method.
  • the specific process is shown in Figure 1.
  • Step 101 Identify users who have communication needs with a base station with a mobile edge computing MEC function.
  • Step 102 Group the user's uplink tasks and downlink tasks to obtain multiple task groups arranged in sequence, so as to allow the base station to complete the data transmission of the multiple task groups sequentially in a full-duplex mode in a time-division multiplexing manner; Among them, each task group contains at least one of an uplink task and a downlink task.
  • the uplink tasks and downlink tasks of the same MEC computing offload user are divided into different task groups, and the task group where the uplink task is located Ranked in front of the task group where the down task is located.
  • the resource allocation method of this embodiment can be applied to a server, and the server is set in a base station with mobile edge computing MEC function; wherein, the MEC function of the base station can be integrated in the server, or it can be used by a base station located in the base station. Independent MEC server to achieve.
  • the communication request can include the task type and the data transmission volume of the task; the task type can reflect the user type, for example, the task type is a single uplink task, then The user is a normal uplink user; the task type is a separate downlink task, then the user is a normal downlink user; the task type is an MEC computing offloading task, then the user is an MEC computing offloading user; among them, the MEC computing offloading task includes uplink tasks and Down mission.
  • Figure 2 shows a schematic diagram of the communication between the user terminal and the base station in the MEC scenario. The figure includes a normal uplink user A, a normal downlink user B, and an MEC computing offload user C.
  • the server can consider the user who has received the communication request to be a user who has communication needs with the base station; it should be noted that in this embodiment, data is transmitted in a time-division multiplexing manner, that is, each user is time-division multiplexing the same channel Therefore, all users who have communication needs with the base station identified by the server are users who share the same channel; therefore, in step 101, the server can identify all users who have communication needs with the base station and share the same channel. Among them, in addition to the MEC calculation offload users, the identified users may also include ordinary uplink users and ordinary downlink users.
  • the server may periodically execute the resource allocation method of this embodiment with a preset duration as a period; in this case, each time it is identified from the users who have access to the same channel of the base station in the current period that they are connected to the base station. All users with communication needs.
  • each task group includes at least one of an uplink task and a downlink task, that is, an uplink task and a downlink task can be divided into one group, It is also possible to divide an uplink task into a group independently, or divide a downlink task into a group independently; and the uplink tasks and downlink tasks of the same MEC computing offload user are divided into different task groups, and the uplink tasks are located in different task groups.
  • the task group is arranged in front of the task group where the downstream task is located.
  • each task group in this embodiment Since the users of each task group in this embodiment are in full-duplex mode and transmit data on the same channel in a time-division multiplexing manner, it is impossible for the same MEC to calculate and unload the uplink tasks and downlink tasks of users. They are executed at the same time, so the uplink tasks and downlink tasks of the same MEC computing and offloading users cannot be divided into the same task group. In addition, since each task only needs to be executed once to complete, each task will only be assigned to one task group.
  • the number of uplink tasks as M, the number of downlink tasks as N, and the number of task groups as K in one example, if the number of uplink tasks M is different from the number of downlink tasks N, that There are task groups that only contain uplink tasks or only downlink tasks in K task groups; for example, if M is less than N, then there are task groups that only contain uplink tasks among K task groups; if N is less than M, then K tasks There is a task group that contains only downstream tasks in the group.
  • the K task groups are also sorted. Since the uplink tasks of the same MEC calculation and offloading users need to be executed before the downlink tasks, the K task groups after sorting need to meet the requirements of the same
  • the task group of the MEC computing unloading user's uplink task is ranked in front of the task group of the MEC computing unloading user's downlink task.
  • the base station can complete the data transmission of the K task groups in a full-duplex mode in a time-division multiplexing manner in accordance with the sequence of the K task groups.
  • the user terminal can transmit data to the base station based on the preset transmission power to complete the uplink task, and the base station can also transmit data to the user terminal based on the preset transmission power to complete the downlink task.
  • the time occupied by each task group is the larger of the data transmission time length of the uplink task and the data transmission time length of the downlink task in the task group.
  • the user's uplink tasks and downlink tasks are grouped into multiple task groups arranged in sequence, so as to allow the base station to complete the data of multiple task groups in a full-duplex mode in a time-division multiplexing manner.
  • the second embodiment of the present application relates to a resource allocation method.
  • the second embodiment is roughly the same as the first embodiment.
  • the main difference is that: in the second embodiment, another specific method for obtaining K task groups arranged in sequence is provided; The flowchart of the resource allocation method in the second embodiment.
  • Step 201 Identify users who have communication needs with a base station with a mobile edge computing MEC function. This step is similar to step 101 in the first embodiment, and will not be repeated here.
  • Step 202 Group the user's uplink tasks and downlink tasks to obtain a plurality of task groups arranged in sequence; including the following sub-steps.
  • Sub-step 2011, combine the user's uplink task and downlink task to obtain multiple temporary task groups; among them, each temporary task group includes an uplink task and a downlink task, and each uplink task exists in several temporary task groups , Each down task exists in several temporary task groups.
  • sub-step 2012 the data transmission time difference between each temporary task group in the full-duplex mode and in the half-duplex mode is estimated.
  • sub-step 2013, based on the data transmission time difference of each temporary task group, multiple task groups arranged in sequence are determined.
  • the users identified in step 201 include: N MEC computing offload users, P ordinary uplink users, and Q ordinary downlink users.
  • Each MEC computing offload user has one uplink task and one For downlink tasks, each ordinary uplink user has an uplink task, and each ordinary downlink user has a downlink task.
  • the task combination forms a temporary task group; the downlink task of each ordinary downlink user can be combined with any uplink task to form a temporary task group; each MEC calculates the downlink task of the offload user, and can be combined with the uplink task of the offload user except the MEC. Any combination of upstream tasks outside the task forms a temporary task group.
  • the data transmission time difference between the temporary task group in the full-duplex mode and in the half-duplex mode is estimated.
  • Minimum data transmission duration in duplex mode and calculate the difference between the minimum data transmission duration of each temporary task group in full-duplex mode and the minimum data transmission duration in half-duplex mode as each temporary task group The data transmission time difference.
  • the minimum data transmission duration of each temporary task group in the full-duplex mode can be estimated using, for example, a binary search method, as follows.
  • each temporary task group needs to meet the following conditions.
  • t m, n represents the data transmission time occupied by the temporary task group (m, n)
  • B represents the channel bandwidth, with Represents the transmit power of the user terminal performing the uplink task and the transmit power of the base station performing the downlink task in the temporary task group (m, n);
  • h m,n represents the channel power gain, Indicates the data transmission volume of the uplink task and the data transmission volume of the downlink task; Respectively represent the maximum transmission power of the uplink task and the maximum transmission power of the downlink task, and ⁇ represents the full-duplex self-interference cancellation ratio of the base station segment.
  • the optimal transmit power corresponding to one of the tasks is the maximum power value allowed by the system; and the binary search method is used to obtain the optimal value of the other power, that is, the optimal transmit power of the other task.
  • the ending condition of the binary search method is that the difference between the solutions found two adjacent times is within a preset error interval.
  • the minimum data transmission duration of the temporary task group in full-duplex mode can be obtained, which is recorded as That is to say, the minimum delay that can be achieved for the data transmission of the temporary task group. Therefore, the time required for the base station and the users of each temporary task group to complete the data transmission of each temporary task group based on the optimal transmission power is the minimum data transmission duration.
  • the minimum data transmission duration of each temporary task group in half-duplex mode refers to the sum of the minimum data transmission duration of the uplink task in the temporary task group and the minimum data transmission duration of the downlink task in the temporary task group; uplink task or downlink
  • the minimum data transmission duration of the uplink task m and the minimum data transmission duration of the downlink task n can be recorded as The difference between the minimum data transmission time of the temporary task group in full-duplex mode and the data transmission time in half-duplex mode can be expressed as:
  • filtering can be performed based on the greedy algorithm to obtain K task groups.
  • the greedy algorithm may include the following steps.
  • Sub-step 3.1.1 filter out the first-type task group from all the currently existing temporary task groups (when sub-step 3.1.1 is executed for the first time, all the current existing temporary task groups are L), and the first-type task group
  • Each task group in the group includes: uplink tasks for ordinary uplink users or MEC computing offload users, and downlink tasks for ordinary downlink users.
  • Sub-step 3.1.2 filter out a temporary task group with the largest data transmission time difference from the first type of task group, as the first task group K1(m1, n1) filtered out; among them, task group K1(m1, n1)
  • the minimum data transmission duration in full-duplex mode, the optimal transmit power of the uplink task, and the optimal transmit power of the downlink task have been determined in the above substep 2012; and the optimal transmit power of the uplink task It can be sent to the user terminal to which the uplink task belongs, so that the user terminal can subsequently transmit data to the base station based on the optimal transmit power when completing the uplink task.
  • Sub-step 3.1.3 delete the temporary task group containing the upstream task m1 and the downstream task n1 from all the temporary task groups currently existing (when sub-step 3.1.3 is executed for the first time, there are all temporary task groups currently existing).
  • step 3.1.3 if it is determined that the uplink task m1 in K1 is the uplink task of the MEC calculation and offloading users, then go to step 3.2.
  • each temporary task group in the second-type task group contains: the MEC computing uninstall user ’S downstream task n2;
  • Sub-step 3.2.2 filter out a temporary task group with the largest data transmission time difference from the second type of task group, as the second task group K2(m2, n2) selected;
  • Sub-step 3.2.3 delete the temporary task group containing the uplink task m2 and the downlink task n2 from the remaining temporary task groups after the execution of sub-step 3.1.3, at this time there are L-2 temporary task groups left.
  • Sub-step 3.2.4 if it is judged that the uplink task m2 in task group K2 is the uplink task of another MEC computing offloading user, then return to step 3.2; if it is judged that the uplink task m2 in task group K2 is the uplink task of ordinary uplink users Uplink task, then return to step 3.1.
  • the binary search method is used to find the optimal transmit power of each task group, and based on this, the minimum data transmission duration of each task group is determined; K task groups arranged in sequence are selected based on the greedy algorithm;
  • the time complexity of the binary search method and the greedy algorithm is relatively low, so it can greatly reduce the time consumption of the calculation process of resource allocation, thereby greatly reducing the total system delay in the MEC scenario.
  • this embodiment does not impose any limitation on this.
  • other algorithms can also be used for calculation. Generally, algorithms with a time complexity less than polynomial time can be used.
  • the third embodiment of the present application relates to a server, as shown in FIG. 4, comprising: at least one processor 401; and a memory 402 communicatively connected with the at least one processor 401; wherein, the memory 402 stores An instruction that can be executed by the at least one processor 401, and the instruction is executed by the at least one processor 401, so that the at least one processor 401 can execute the foregoing resource allocation method.
  • the server is set in the base station.
  • the memory 402 and the processor 401 are connected in a bus manner.
  • the bus may include any number of interconnected buses and bridges.
  • the bus connects one or more various circuits of the processor 401 and the memory 402 together.
  • the bus can also connect various other circuits such as peripheral devices, voltage regulators, power management circuits, etc., which are all well-known in the art, and therefore, no further description will be given in this application.
  • the bus interface provides an interface between the bus and the transceiver.
  • the transceiver may be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on the transmission medium.
  • the data processed by the processor 401 is transmitted on the wireless medium through the antenna, and further, the antenna also receives the data and transmits the data to the processor 401.
  • the processor 401 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions.
  • the memory 402 may be used to store data used by the processor 401 when performing operations.
  • the fourth embodiment of the present application relates to a computer-readable storage medium storing a computer program.
  • the computer program is executed by the processor, the above method embodiment is realized.
  • the embodiment of this application forms an uplink task and a downlink task into a task group and completes the data transmission of the task group in full duplex mode, and the grouping method in this application allows users in the MEC scenario to communicate with each other.
  • the base station performs normal data transmission, which can reduce the total system delay in the MEC scenario.
  • the embodiment of the present application provides a specific way to determine multiple task groups arranged in sequence; the data transmission time difference between the task group in the full-duplex mode and the half-duplex mode can reflect the task group The time saved in full-duplex mode is compared with that in half-duplex mode. Therefore, filtering based on the difference in data transmission time can filter out multiple task groups that make the total system delay as small as possible.
  • the embodiment of the present application provides a specific method for estimating the minimum data transmission duration of each temporary task group in full-duplex mode: binary search method.
  • the time complexity of this method is low, so it can be estimated faster. , Thereby further reducing the total system delay.
  • the optimal transmission power and the minimum data transmission duration can also be configured, which is highly flexible.
  • the greedy algorithm which has a low time complexity, so it can be screened faster, thereby further reducing The total delay of the small system.
  • the program is stored in a storage medium and includes several instructions to make A device (may be a single-chip microcomputer, a chip, etc.) or a processor (Krocessor) executes all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disks or optical disks and other media that can store program codes. .

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Abstract

本申请实施例涉及通信技术领域，公开了一种资源分配方法、服务器及存储介质。本申请实施例中，资源分配方法包括，识别出与具有移动边缘计算MEC功能的基站有通信需求的用户；对用户的上行任务和下行任务分组得到依序排列的多个任务组，以允许基站在全双工模式下，以分时复用的方式依序完成多个任务组的数据传输；其中，每个任务组包含一个上行任务和一个下行任务的至少其中之一，用户中，同一个MEC计算卸载用户的上行任务和下行任务被分在不同任务组中，且上行任务所在的任务组排在下行任务所在的任务组前面。

Description

资源分配方法、服务器及存储介质
相关申请的交叉引用
本申请要求享有2019年11月19日提交的名称为“资源分配方法、服务器及存储介质”的中国专利申请CN201911133214.5的优先权，其全部内容通过引用并入本申请中。
技术领域
本申请实施例涉及通信技术领域，特别涉及资源分配方法、服务器及存储介质。
背景技术
随着移动设备数量的爆炸式增长，移动视频流、增强现实、虚拟现实和自动驾驶等各类新兴的应用服务给移动通信网络带来了前所未有的数据流量。然而，移动终端往往不具备较强的计算能力，针对这些低延时和高计算量的应用服务，移动终端本地计算难以保证其服务质量。
移动边缘计算(Mobile Edge ComKuting，MEC)能够在网络边缘提供计算、存储和通信源。移动用户可将其计算任务卸载到MEC服务器进行计算。由于MEC服务器靠近用户终端且具有相对强的计算能力，MEC能够为移动用户提供低时延、高带宽的服务。在MEC系统中，传输延时是影响系统总延时的重要组成部分；用户将任务卸载到MEC服务器上执行包括任务上传、任务计算与结果下载过程，其中上传和下载过程的传输延时对MEC系统总延时有很大影响。随着MEC计算卸载用户的不断增加，目前的半双工模式下，MEC系统的总时延也不断增大，严重影响了数据传输的及时性。
发明内容
本申请实施例的目的在于提供一种资源分配方法、服务器及存储介质，可以减小MEC场景下的系统总时延。
为解决上述技术问题，本申请的实施例提供了一种资源分配方法，包括：识别出与具有移动边缘计算MEC功能的基站有通信需求的用户；对所述用户的上行任务和下行任务分组得到依序排列的多个任务组，以允许所述基站在全双工模式下，以分时复用的方式依序完成多个所述任务组的数据传输；其中，每个所述任务组包含一个所述上行任务和一个所述下行任务的至少其中之一，所述用户中，同一个MEC计算卸载用户的上行任务和下行任务被分在不同任务组中，且上行任务所在的任务组排在下行任务所在的任务组前面。
本申请的实施例还提供了一种服务器，包括：至少一个处理器；以及，与所述至少一个处理器通信连接的存储器；其中，所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行上述方法。
本申请的实施例还提供了一种计算机可读存储介质，存储有计算机程序，其中，所述计算机程序被处理器执行时实现上述资源分配方法。
附图说明
一个或多个实施例通过与之对应的附图中的图片进行示例性说明，这些示例性说明并不构成对实施例的限定，附图中具有相同参考数字标号的元件表示为类似的元件，除非有特别申明，附图中的图不构成比例限制。
图1是根据本申请第一实施例中资源分配方法的流程图；
图2是根据本申请第一实施例中MEC场景下用户终端与基站通信的示意图；
图3是根据本申请第二实施例中资源分配方法的流程图；
图4是根据本申请第三实施例的服务器的方框图。
具体实施方式
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合附图对本申请的各实施例进行详细的阐述。然而，本领域的普通技术人员可以理解，在本申请各实施例中，为了使读者更好地理解本申请而提出了许多技术细节。但是，即使没有这些技术细节和基于以下各实施例的种种变化和修改，也可以实现本申请所要求保护的技术方案。以下各个实施例的划分是为了描述方便，不应对本申请的具体实现方式构成任何限定，各个实施例在不矛盾的前提下可以相互结合相互引用。
本申请的第一实施例涉及一种资源分配方法。具体流程如图1所示。
步骤101，识别出与具有移动边缘计算MEC功能的基站有通信需求的用户。
步骤102，对用户的上行任务和下行任务分组得到依序排列的多个任务组，以允许基站在全双工模式下，以分时复用的方式依序完成多个任务组的数据传输；其中，每个任务组包含一个上行任务和一个下行任务的至少其中之一，用户中，同一个MEC计算卸载用户的上行任务和下行任务被分在不同任务组中，且上行任务所在的任务组排在下行任务所在的任务组前面。
下面对本实施例的资源分配方法的实现细节进行具体的说明，以下内容仅为方便理解提供的实现细节，并非实施本方案的必须。
本实施例的资源分配方法可以应用于服务器，该服务器设置在具备移动边缘计算MEC 功能的基站中；其中，该基站的该MEC功能可以集成在该服务器中，也可以是由位于基站中的一个独立的MEC服务器来实现。
用户需要与基站通信，通常都是会通过用户终端发送通信请求，该通信请求中可以包含任务类型以及任务的数据传输量；任务类型可以反应用户类型，例如，任务类型是单独的上行任务，那么该用户是普通上行用户；任务类型是单独的下行任务，那么该用户是普通下行用户；任务类型是MEC计算卸载任务，那么该用户是MEC计算卸载用户；其中，MEC计算卸载任务包含上行任务和下行任务。如图2所示为MEC场景下用户终端与基站通信的示意图，图中包含普通上行用户A、普通下行用户B以及MEC计算卸载用户C。
服务器可以将接收到通信请求的用户认为是与基站有通信需求的用户；需要说明的是，本实施例中是以分时复用的方式传输数据的，即各用户是分时复用同一信道的；因此，服务器识别出的与基站有通信需求的所有用户，是共用同一信道的用户；因此，在步骤101中，服务器可以识别出与基站有通信需求且共用同一信道的所有用户。其中，识别出的用户中除了包含MEC计算卸载用户，还可以包含普通上行用户和普通下行用户。
在一个例子中，服务器可以以预设时长为周期，周期性地执行本实施例的资源分配方法；此时，每次都是从当前周期内接入基站同一信道的用户中识别出与基站有通信需求的所有用户。
在步骤102中，依序排列的多个任务组中，每个任务组包含一个上行任务和一个下行任务的至少其中之一，即，可以将一个上行任务和一个下行任务划分在一组内，也可以将一个上行任务独立划分为一组，或将一个下行任务独立划分为一组；并且，同一个MEC计算卸载用户的上行任务和下行任务被分在不同任务组中，且上行任务所在的任务组排在下行任务所在的任务组前面。由于本实施例中各任务组的用户是在全双工模式下，以分时复用的方式同一个信道上进行传输数据的，而同一个MEC计算卸载用户的上行任务和下行任务不可能在同一时刻执行，因此同一个MEC计算卸载用户的上行任务和下行任务不能被划分在同一个任务组内。另外，由于每个任务只需要执行一次即可完成，因此，每个任务仅会被分配在一个任务组内。
将上行任务的个数记作M、下行任务的个数记作N、任务组的个数记作K；在一个例子中，如果上行任务的个数M与下行任务的个数N不同，那个K个任务组中存在仅包含上行任务或仅包含下行任务的任务组；例如，若M小于N，则K个任务组中存在仅包含上行任务的任务组；若N小于M，则K个任务组中存在仅包含下行任务的任务组。
并且，在步骤102中，还会对K个任务组进行排序，由于同一个MEC计算卸载用户的上行任务需要先于下行任务被执行，因此，排序后的K个任务组，需要满足，同一个MEC计算卸载用户的上行任务所在的任务组排在该MEC计算卸载用户的下行任务所在的 任务组前面。基于上述分组以及对各任务组的排列后，基站可以按照K个任务组的排列顺序，在全双工模式下，以分时复用的方式完成K个任务组的数据传输。其中，用户终端可以基于预先设定的发射功率将数据传输至基站以完成上行任务，基站也可以基于预先设定的发射功率将数据传输至用户终端以完成下行任务。每个任务组所占用的时间，是该任务组中上行任务的数据传输时长与下行任务的数据传输时长的较大者。
本实施例中，将用户的上行任务和下行任务分组得到依序排列的多个任务组，以允许所述基站在全双工模式下，以分时复用的方式完成多个任务组的数据传输；其中，同一个MEC计算卸载用户的上行任务和下行任务被分在不同任务组中，且上行任务所在的任务组排在下行任务所在的任务组前面。即本申请中，将一个上行任务和一个下行任务形成任务组并以全双工模式完成任务组的数据传输，且本申请中的分组方式允许MEC场景下的用户与基站进行正常的数据传输，从而可以减小MEC场景下的系统总时延。
本申请的第二实施例涉及一种资源分配方法。第二实施例与第一实施例大致相同，主要区别之处在于：第二实施例中提供了得到依序排列的K个任务组的另一种具体方式；如图3所示为本申请第二实施例中资源分配方法的流程图。
步骤201，识别出与具有移动边缘计算MEC功能的基站有通信需求的用户。此步骤与第一实施例中的步骤101类似，此处不再赘述。
步骤202，对用户的上行任务和下行任务分组得到依序排列的多个任务组；包含如下子步骤。
子步骤2011，将用户的上行任务和下行任务组合，并得到多个临时任务组；其中，每个临时任务组包含一个上行任务和一个下行任务，每个上行任务存在于若干个临时任务组内，每个下行任务存在于若干个临时任务组内。
子步骤2012，估算每个临时任务组在全双工模式下与在半双工模式下的数据传输时间差。
子步骤2013，基于每个临时任务组的数据传输时间差，确定出依序排列的多个任务组。
如下是对上述各子步骤的详细说明。
在子步骤2011中，假设，步骤201中识别出的用户中，包括：N个MEC计算卸载用户，P个普通上行用户和Q个普通下行用户，每个MEC计算卸载用户具有一个上行任务和一个下行任务，每个普通上行用户具有一个上行任务，每个普通下行用户具有一个下行任务，那么，临时任务组的数量可以为：L＝(P+N)*(Q+N)-N。即，每个普通上行用户的上行任务，可以与任何一个下行任务组合形成一个临时任务组；每个MEC计算卸载用户的上行任务，可以与除该MEC计算卸载用户的下行任务外的任何一个下行任务组合形成一个临时任务组；每个普通下行用户的下行任务，可以与任何一个上行任务组合形成一个临时 任务组；每个MEC计算卸载用户的下行任务，可以与除该MEC计算卸载用户的上行任务外的任何一个上行任务组合形成一个临时任务组。
在子步骤2012中，对于每个临时任务组，估算该临时任务组在全双工模式下与在半双工模式下的数据传输时间差。在一个例子中，可以至少根据预设的用于传输数据的最大发射功率和每个临时任务组的数据传输量，估算每个临时任务组在全双工模式下的最小数据传输时长和在半双工模式下的最小数据传输时长；并计算每个临时任务组在全双工模式下的最小数据传输时长与在半双工模式下的最小数据传输时长的差值，作为每个临时任务组的数据传输时间差。
每个临时任务组在全双工模式下的最小数据传输时长例如可以使用二分查找法来进行估算，具体如下。
将临时任务组中的上行任务记作m、下行任务记作n；则，每个临时任务组需要满足如下条件。
Figure PCTCN2020120161-appb-000001
Figure PCTCN2020120161-appb-000002
Figure PCTCN2020120161-appb-000003
Figure PCTCN2020120161-appb-000004
其中，t m，n表示临时任务组(m,n)所占用的数据传输时长，B表示信道带宽，
Figure PCTCN2020120161-appb-000005
和
Figure PCTCN2020120161-appb-000006
表示临时任务组(m,n)中执行上行任务的用户终端的发射功率和执行下行任务的基站的发射功率；
Figure PCTCN2020120161-appb-000007
h m,n表示信道功率增益，
Figure PCTCN2020120161-appb-000008
表示上行任务的数据传输量和下行任务的数据传输量；
Figure PCTCN2020120161-appb-000009
分别表示上行任务的最大发射功率和下行任务的最大发射功率，α表示基站段的全双工自干扰消除比率。
为了使得每个临时任务组所分配的t m,n最小，可以先确定
Figure PCTCN2020120161-appb-000010
和
Figure PCTCN2020120161-appb-000011
的其中一个取 最大值，即令
Figure PCTCN2020120161-appb-000012
或者令
Figure PCTCN2020120161-appb-000013
即，其中一个任务对应的最优发射功率为系统允许的最大功率值；并采用二分查找法得到另一个功率的最优值，即另一个任务的最优发射功率。其中，二分查找法的结束条件是，相邻两次查找到的解的差值在预设的误差区间内。
如上，利用二分查找法将临时任务组的
Figure PCTCN2020120161-appb-000014
和
Figure PCTCN2020120161-appb-000015
的取值都确定后，即可以得到该临时任务组在全双工模式下的最小数据传输时长，记作
Figure PCTCN2020120161-appb-000016
即表示该临时任务组的数据传输可以达到的最小时延。因此，基站与每个临时任务组的用户基于最优发射功率完成每个临时任务组的数据传输的耗时为最小数据传输时长。
每个临时任务组在半双工模式下的最小数据传输时长是指该临时任务组中上行任务的最小数据传输时长和该临时任务组中下行任务的最小数据传输时长的和；上行任务或下行任务的最小数据传输时长的估算方式，例如可以是，上行任务的最小数据传输时长＝上行任务的传输数据量/上行任务的最大发射功率；下行任务的最小数据传输时长＝下行任务的传输数据量/下行任务的最大发射功率。将上行任务m的最小传输数据时长、下行任务n的最小传输数据时长可以分别记作
Figure PCTCN2020120161-appb-000017
临时任务组在全双工模式下的最小数据传输时长和在半双工模式下的数据传输时间差可以表示为：
Figure PCTCN2020120161-appb-000018
在子步骤2013中，可以基于贪心算法进行筛选，从而得到K个任务组。在一些实施方式中，贪心算法可以包含以下步骤。
步骤3.1：
子步骤3.1.1，从当前存在的所有临时任务组中(首次执行子步骤3.1.1时，当前存在的所有临时任务组为L个)筛选出第一类任务组群，第一类任务组群中的每个任务组包含：普通上行用户或MEC计算卸载用户的上行任务，以及普通下行用户的下行任务。
子步骤3.1.2，从第一类任务组群中筛选出数据传输时间差最大的一个临时任务组，作 为筛选出的第一个任务组K1(m1，n1)；其中，任务组K1(m1，n1)在全双工模式下的最小数据传输时长、上行任务的最优发射功率、下行任务的最优发射功率，均在上述子步骤2012中已确定出来了；且上行任务的最优发射功率可以被发送给该上行任务所属的用户终端，以供后续该用户终端在完成该上行任务中，基于该最优发射功率向基站传输数据。
子步骤3.1.3，从当前存在的所有临时任务组中(首次执行子步骤3.1.3时，当前存在的所有临时任务组为L个)删除包含上行任务m1和下行任务n1的临时任务组。
子步骤3.1.3，如果判断出K1中的上行任务m1为MEC计算卸载用户的上行任务，那么，进入步骤3.2。
步骤3.2：
子步骤3.2.1，从子步骤3.1.3执行后剩下的临时任务组中筛选出第二类任务组群，第二类任务组群中的每个临时任务组包含：该MEC计算卸载用户的下行任务n2；
子步骤3.2.2，从第二类任务组群中筛选出数据传输时间差最大的一个临时任务组，作为筛选出的第二个任务组K2(m2，n2)；
子步骤3.2.3，从子步骤3.1.3执行后剩下的临时任务组中删除包含上行任务m2和下行任务n2的临时任务组，此时剩下L-2个临时任务组。
子步骤3.2.4，如果判断出任务组K2中的上行任务m2为另一MEC计算卸载用户的上行任务，那么，返回步骤3.2；如果判断出任务组K2中的上行任务m2为普通上行用户的上行任务，那么返回步骤3.1。
通过上述步骤3.1、步骤3.2的不断循环计算，直至选出依次排列的全部K个任务组。
本实施例中，采用二分查找法查找每个任务组的最优发射功率，并基于此确定每个任务组的最小数据传输时长；再基于贪心算法来筛选出依次排列的K个任务组；由于二分查找法和贪心算法的时间复杂度都比较低，所以可以极大程度地减少资源分配的计算过程所产生的耗时，从而极大程度地降低MEC场景下的系统总时延。然本实施例对此不作任何限制，在其他例子中，也可以采用其他算法进行计算，一般的，时间复杂度小于多项式时间的算法均可以被采用。
上面各种方法的步骤划分，只是为了描述清楚，实现时可以合并为一个步骤或者对某些步骤进行拆分，分解为多个步骤，只要包括相同的逻辑关系，都在本专利的保护范围内；对算法中或者流程中添加无关紧要的修改或者引入无关紧要的设计，但不改变其算法和流程的核心设计都在该专利的保护范围内。
本申请的第三实施例涉及一种服务器，如图4所示，包括：至少一个处理器401；以及，与所述至少一个处理器401通信连接的存储器402；其中，所述存储器402存储有可被所述至少一个处理器401执行的指令，所述指令被所述至少一个处理器401执行，以使所述 至少一个处理器401能够执行上述资源分配方法。
其中，该服务器设置于基站中。
其中，存储器402和处理器401采用总线方式连接，总线可以包括任意数量的互联的总线和桥，总线将一个或多个处理器401和存储器402的各种电路连接在一起。总线还可以将诸如外围设备、稳压器和功率管理电路等之类的各种其他电路连接在一起，这些都是本领域所公知的，因此，本申请不再对其进行进一步描述。总线接口在总线和收发机之间提供接口。收发机可以是一个元件，也可以是多个元件，比如多个接收器和发送器，提供用于在传输介质上与各种其他装置通信的单元。经处理器401处理的数据通过天线在无线介质上进行传输，进一步，天线还接收数据并将数据传送给处理器401。
处理器401负责管理总线和通常的处理，还可以提供各种功能，包括定时，外围接口，电压调节、电源管理以及其他控制功能。而存储器402可以被用于存储处理器401在执行操作时所使用的数据。
本申请的第四实施例涉及一种计算机可读存储介质，存储有计算机程序。计算机程序被处理器执行时实现上述方法实施例。
本申请实施例相对于现有技术而言，将一个上行任务和一个下行任务形成任务组并以全双工模式完成任务组的数据传输，且本申请中的分组方式允许MEC场景下的用户与基站进行正常的数据传输，从而可以减小MEC场景下的系统总时延。
此外，本申请实施例提供了确定出依序排列的多个任务组的一种具体方式；任务组在全双工模式下与在半双工模式下的数据传输时间差，可以体现出该任务组在全双工模式下相对于在半双工模式下进行数据传输所节约的时间，因此，基于数据传输时间差进行筛选，可以筛选出使得系统总时延尽可能小的多个任务组。
此外，本申请实施例提供了估算每个临时任务组在全双工模式下的最小数据传输时长的一种具体方式：二分查找法，该方法的时间复杂度较低，因此可以较快进行估算，从而进一步减小系统总时延。
此外，本申请实施例中，除了可以对上行任务和下行任务的组合进行配置，还可以对最优发射功率和最小数据传输时长进行配置，灵活度高。
此外，本申请实施例中，提供了估算确定出依序排列的多个任务组的一种具体方式：贪心算法，该算法的时间复杂度较低，因此可以较快地进行筛选，从而进一步减小系统总时延。
应当说明的是，本领域技术人员可以理解，实现上述实施例方法中的全部或部分步骤 是可以通过程序来指令相关的硬件来完成，该程序存储在一个存储介质中，包括若干指令用以使得一个设备(可以是单片机，芯片等)或处理器(Krocessor)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
本领域的普通技术人员可以理解，上述各实施例是实现本申请的具体实施例，而在实际应用中，可以在形式上和细节上对其作各种改变，而不偏离本申请的精神和范围。

Claims (10)

  1. 一种资源分配方法，其中，包括：
    识别出与具有移动边缘计算MEC功能的基站有通信需求的用户；
    对所述用户的上行任务和下行任务分组得到依序排列的多个任务组，以允许所述基站在全双工模式下，以分时复用的方式依序完成多个所述任务组的数据传输；
    其中，每个所述任务组包含一个所述上行任务和一个所述下行任务的至少其中之一，所述用户中，同一个MEC计算卸载用户的上行任务和下行任务被分在不同任务组中，且上行任务所在的任务组排在下行任务所在的任务组前面。
  2. 根据权利要求1所述的资源分配方法，其中，所述对所述所有用户的上行任务和下行任务分组得到依序排列的多个任务组，包括：
    将所述上行任务和所述下行任务组合，并得到多个临时任务组；其中，每个所述临时任务组包含一个所述上行任务和一个所述下行任务，每个所述上行任务存在于若干个所述临时任务组内，每个所述下行任务存在于若干个所述临时任务组内；
    估算每个所述临时任务组在全双工模式下与在半双工模式下的数据传输时间差；
    基于每个所述临时任务组的所述数据传输时间差，确定出依序排列的多个所述任务组。
  3. 根据权利要求2所述的资源分配方法，其中，所述估算每个所述临时任务组在全双工模式下与在半双工模式下的数据传输时间差，包括：
    至少根据预设的用于传输数据的最大发射功率和每个所述任务组的数据传输量，估算每个所述临时任务组在全双工模式下的最小数据传输时长和在半双工模式下的最小数据传输时长；
    计算每个所述临时任务组在全双工模式下的最小数据传输时长与在半双工模式下的最小数据传输时长的差值，作为每个所述临时任务组的所述数据传输时间差。
  4. 根据权利要求3所述的资源分配方法，其中，所述至少根据预设的用于传输数据的最大发射功率和每个所述任务组的数据传输量，估算每个所述临时任务组在全双工模式下的最小数据传输时长中，基于二分查找法估算每个所述临时任务组在全双工模式下的最小数据传输时长。
  5. 根据权利要求4所述的资源分配方法，其中，所述在基于所述二分查找法估算每个所述临时任务组在全双工模式下的最小数据传输时长中，还估算出每个所述临时任务组对应的最优发射功率；
    其中，所述基站与每个所述临时任务组的用户基于所述最优发射功率完成每个所 述临时任务组的数据传输的耗时为所述最小数据传输时长。
  6. 根据权利要求2所述的资源分配方法，其中，所述基于每个所述临时任务组的所述数据传输时间差，确定出依序排列的多个所述任务组中，基于贪心算法确定出依序排列的多个所述任务组。
  7. 根据权利要求1所述的资源分配方法，其中，所述资源分配方法周期性地被执行；所述识别出与具有移动边缘计算MEC功能的基站有通信需求的用户中，识别出当前周期内与所述基站有通信需求的所有用户。
  8. 一种服务器，其中，包括：
    至少一个处理器；以及，
    与所述至少一个处理器通信连接的存储器；其中，
    所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行如权利要求1至7中任一所述的资源分配方法。
  9. 根据权利要求8所述的服务器，其中，所述服务器设置于所述基站中。
  10. 一种计算机可读存储介质，存储有计算机程序，其中，所述计算机程序被处理器执行时实现权利要求1至7中任一项所述的资源分配方法。
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