CN107333267A - A kind of edge calculations method for 5G super-intensive networking scenes - Google Patents

A kind of edge calculations method for 5G super-intensive networking scenes Download PDF

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Publication number
CN107333267A
CN107333267A CN201710485333.1A CN201710485333A CN107333267A CN 107333267 A CN107333267 A CN 107333267A CN 201710485333 A CN201710485333 A CN 201710485333A CN 107333267 A CN107333267 A CN 107333267A
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user
subchannel
mec
task
base station
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CN107333267B (en
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欧阳昊
王鹏飞
杨杰
但黎琳
肖悦
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University of Electronic Science and Technology of China
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/02—Resource partitioning among network components, e.g. reuse partitioning
    • H04W16/06—Hybrid resource partitioning, e.g. channel borrowing
    • H04W16/08—Load shedding arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/02—Resource partitioning among network components, e.g. reuse partitioning
    • H04W16/10—Dynamic resource partitioning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/02—Traffic management, e.g. flow control or congestion control
    • H04W28/0231—Traffic management, e.g. flow control or congestion control based on communication conditions
    • H04W28/0236—Traffic management, e.g. flow control or congestion control based on communication conditions radio quality, e.g. interference, losses or delay

Abstract

The invention belongs to 5G and the edge calculations technical field of communicating, specifically a kind of edge calculations method for 5G super-intensive networking scenes.The basic ideas of the present invention are to place a MEC server in one small base station to provide edge calculations service for the phone user of the Microcell, while phone user can select the cloud computing service being connected with macro base station according to the characteristic of pending task.Beneficial effects of the present invention are that method of the invention can cause user's selection is most suitable to calculate service, improve delay performance.

Description

A kind of edge calculations method for 5G super-intensive networking scenes
Technical field
The invention belongs to 5G and edge calculations (Mobile Edge Computing, the MEC) technical field of communicating, specifically Say it is a kind of edge calculations method for 5G super-intensive networking scenes；Invention is related to convex optimization (Convex Optimal), Super-intensive networking (Ultra-Density Network, UDN), edge calculations, the technology such as cloud computing (Cloud Computing).
Background technology
Cloud computing is the technology that one kind is intended to break through mobile terminal computing capability (storage capacity) limitation.Terminal device is selected By the calculating task (store tasks) of oneself transfer to high in the clouds perform with save itself limited computing resource (storage resource) and Energy consumption.
And edge calculations this concepts is relative to cloud computing.Because the computing capability of cloud server is very powerful, But the time delay from terminal to Cloud Server may be very big.And the development with mobile communication technology and various new industries Rise.Some applications in terminal propose higher requirement, such as augmented reality (Augmented to delay performance Reality, AR).Therefore in order to meet this demand, this concept of edge calculations is arisen at the historic moment.What it is different from cloud computing is side Edge calculates the edge calculations server that cloud computing server is inferior in the neighbouring geographical position deployment computing capability of user.Come with this Reduce time delay caused by physical distance.
The access density of upcoming 5G mobile communication technologies design is 106Every square kilometre, in order to meet such Pang Big access demand, 5G employs super-intensive networking technology：One cell is made up of a macro base station and substantial amounts of micro-base station, Each micro-base station is responsible for neighbouring phone user's service.But so many accessing user, gone to meet with which type of technology The problem of various capability requirements of terminal are still to be solved.
The content of the invention
In view of the above-mentioned problems, the present invention proposes a kind of edge calculations method for 5G super-intensive networking scenes, it is intended to Improve the computing capability and delay performance of access terminal in cellular system.The basic ideas of the present invention are a small base station (Small Base Station, SBS) places a MEC server to provide edge calculations clothes for the phone user of the Microcell Business, while phone user can select and macro base station (Macro Base Station, MBS) according to the characteristic of pending task Connected cloud computing service.The program can cause user's selection is most suitable to calculate service, improve delay performance.
Introducing system model first：
As shown in Figure 1, it is considered to the cellular system of a up super-intensive networking, the macro base station MSB that there is a center, It is connected with cloud computing server, and several small base station SBS, each SBS placed an edge calculations server；Each There is the phone user that several are accessed small base station, and each user has a pending task, and each task has two attributes：It is defeated Enter data volume and CPU execution cycle numbers, and each task can select to be performed locally, perform or cloud meter on MEC servers Calculate and performed on server.Here by taking a small base station as an example：Assuming that the access phone user number of small base station is N, there is K individual independent Subchannel is available for distribution.User, MEC servers simultaneously, the computing capability of cloud computing server is respectively：Fmes, Fcloud。 Other variables are as shown in the table：
Table 1
The method of the present invention is divided into four steps：
S1, initialising subscriber unloading strategy：
First of all for the user task initialized, unloading strategy assumes first that the meter of subchannel and MEC servers Calculation ability gives each user, and channel gain averageInstead of.And calculate the time delay of three kinds of unloading situations：
Wherein
So, the tactful one kind strategy to take time delay minimum under three kinds of strategies of unloading of the initialization of each user is used as just Beginningization unloading strategy；
S2, the subchannel number that all users are planned with distribution：
In the case where the first step is given initial unloading strategy, it is necessary to the distribution of subchannel is carried out to user.This The subchannel number C that each user is assigned to will be determined by walkingiRepresent, it should be noted that the user that selection is performed locally 0 sub-channels should be assigned to.
The number of users for offloading tasks to MEC servers in the first step is N*, and assume that they divide equally MEC in this step The computing resource of server.Then compared to the first step,The two parameters have occurred that change, after renewal Parameter be updated in (1) formula, you can obtain the time delay of each user
Introduce utility functionSet up and obtain CiMathematical modeling be expressed as follows
Here propose to propose a kind of suboptimum solution based on the thought divided and ruled：The user of all subchannels to be allocated is divided into two Individual subsetIt is first the two set distribution number of subchannels. Introduce two functionsThen C is obtainediMathematical modeling (3) be changed into：
Two constraintss are introduced simultaneouslyThen model (4) is changed into：
The Lagrangian of (5) formula of construction：
According to
Introduce variable
Then have：
Dichotomy can be used to solve equation group and obtain numerical solution C1,C2, as gatherThe son letter being assigned to Road number.Then again by subclassTwo are divided into setBy C1, C2Respectively instead of this step In K be iterated distribution.Finally it can just calculate the subchannel number C that each user is allocatedi。
S3, to all users carry out subchannel distribution：
The allocated subchannel number C of user is being determinediIt is every afterwards, it is necessary to distribute specific subchannel for user The algorithm steps of individual user's distribution subchannel are as follows：
Step1, selection user
Step2, for 1 arrive Ci, iteration execution：
By subchannelDistribute to user i；
Hik=0, i ∈ { 1,2..N }；
Step3, repeat step Step1 and step Step2 are until subchannel is assigned in all users；
S4, the users for being discharged in MEC servers to all carry out computational resource allocations：
In unloading strategy, in the case that subchannel distribution strategy is all determined.It there remains last part：MEC computing resources Allocation strategy.All it is the thought using algorithm of dividing and ruling by MEC meter and the allocation algorithm of MEC computing resources is identical with step 2 Resource -- cpu frequency is divided into two parts and is iterated distribution for calculation.Here no longer repeat.
Beneficial effects of the present invention are that method of the invention can cause user's selection is most suitable to calculate service, improve Delay performance.
Brief description of the drawings
Fig. 1 is the cellular system type schematic diagram of super-intensive networking.
Embodiment
The solution of the present invention is described in detail for Summary, will not be repeated here.

Claims (1)

1. a kind of edge calculations method for 5G super-intensive networking scenes, this method is used for the cellular system of super-intensive networking, If described system includes the macro base station MSB at the center that is connected with cloud computing server, and several small base station SBS, Each SBS placed an edge calculations server MEC；There are the phone user that several are accessed, each user in each small base station There is a pending task, each task there are two attributes：Input data amount and CPU execution cycle numbers, and each task can To select to be performed locally, perform on MEC servers or cloud computing server on perform, the access phone user of a base station Number is N, has K independent subchannels to be available for distribution, while user, MEC servers, the computing capability difference of cloud computing server For：WithIt is characterised in that it includes following steps：
S1, initialising subscriber unloading strategy：
For the user task initialized, unloading strategy assumes first that the computing capability of subchannel and MEC servers is equal Give each user, and channel gain averageInstead of；Obtained simultaneously by equation below 1- formula 3 and be unloaded to use respectively Family, the time delay in the case of three kinds of MEC servers and cloud computing server：
Wherein, τ is time delay, and subscript ue is that user, mec are that MEC servers, subscript cloud are cloud computing server, αiFor user i Task input data amount, βiFor the execution cycle number of user i task,For the cpu frequency of user,Taken for MEC The cpu frequency of business device,For cloud computing server CPU frequency, K is The subchannel number of Microcell, B is subchannel bandwidth, σ2For thermal noise power, P is user emission power, diFor user i and SBS Distance, γ be large scale fading coefficients；
The tactful one kind strategy to take time delay minimum under three kinds of strategies of unloading of the initialization of each user is used as initialization unloading It is tactful then according to formula 1 build initialization unloading strategy be：
S2, to all users distribute subchannel number：
The subchannel number C that each user is assigned to will be determinediRepresent, it is assumed that offload tasks to the user of MEC servers Number is N*, and they divide equally the computing resource of MEC servers, then relative to formula 1,The two parameters have been sent out Change has been given birth to, the parameter after renewal is brought into formula 1, you can obtain the time delay of each user
Introducing utility function isSet up and obtain CiMathematical modeling equation below 3：
The user of all subchannels to be allocated is divided into two subsetsWithAnd meet For subsetWithDistribute number of subchannels：
Introduce two functionsFormula 3 is changed into：
Two constraintss are introduced simultaneouslyFormula 4 is changed into：
Construct Lagrangian：
According to
Introduce variable
It can obtain：
Numerical solution C is obtained using the equation group shown in dichotomy solution formula 81、C2, as gatherThe son being assigned to Channel number, then again by subclassTwo are divided into setBy C1、C2Respectively instead of K in this step is iterated calculating, finally obtains the subchannel number C that each user is allocatedi；
S3, to all users carry out subchannel distribution：
If user gathersTask input data set Α={ α of user1,α2,α3,…,αN, subchannel SetUser is allocated subchannel number setIncluding：
S31, selection user
S32, for 1 arrive Ci, iteration execution：
By subchannelDistribute to user i；
Hik=0, i ∈ { 1,2..N }；
S33, repeat step S31 and step S32 are until subchannel is assigned in all users；
S4, the users for being discharged in MEC servers to all carry out computational resource allocations.
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CN111372268B (en) * 2019-12-24 2022-07-08 中国石油大学(华东) Method for optimizing joint wireless resource management and task unloading in ultra-dense network
CN111131835A (en) * 2019-12-31 2020-05-08 中南大学 Video processing method and system
CN111200831A (en) * 2020-01-08 2020-05-26 中国科学院计算技术研究所 Cellular network computing unloading method fusing mobile edge computing

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