Multi-user slice resource allocation method based on competitive game

Patent metadata

Field	Value
Publication number	US-11716748-B2
Application number	US-202117797049-A
Country	US
Kind code	B2
Filing date	Jun 15, 2021
Priority date	Jun 15, 2020
Publication date	Aug 1, 2023
Grant date	Aug 1, 2023

Abstract

The present disclosure provides a multi-user slice resource allocation method based on competitive game. In the method, first model a system as a two-tier architecture of virtual infrastructure service providers (VInPs) and users, and build a VInP utility model and a user utility model; then divide slice resource allocation into nodes and links, and build a node power consumption model and a link power consumption model, then determine a revenue of the VInP and a revenue of a user; and calculate a total revenue of a slice according to the revenue of the VInP and the revenue of the user, and use the total revenue of the slice as a network model; then solve the network model, where the VInP is used as a seller, the user is used as a buyer, the seller determines an initial price according to a total quantity of slice resources, and the buyer bids on the slice, and allocate the slice resources by using a competitive game mechanism. The method of the present disclosure may enhance the utility of the user, and improve a resource allocation effect.

First claim

What is claimed is:

1. A multi-user network slice resource allocation method based on competitive game, comprising:
S1: modeling a network system as a two-tier architecture of virtual infrastructure network service providers (VInPs) and users, wherein a VInP layer comprises a plurality of VInPs and a user layer comprises a plurality of users;
S2: building a VInP utility model and a user utility model;
S3: dividing a network slice resource into nodes and links for allocation, and building a node power consumption model and a link power consumption model;
S4: determining a revenue of each VInP according to the VInP utility model, the node power consumption model, and the link power consumption model, and determining a revenue of each user according to the user utility model, the node power consumption model, and the link power consumption model;
S5: calculating a total revenue of a slice according to the revenue of the VInP and the revenue of the user, and using the total revenue of the slice as a network model;
S6: solving the network model, wherein the VInP is used as a seller, the user is used as a buyer, the seller determines an initial price according to a total quantity of slice resources, and the buyer bids on the slice; and allocating the slice resources by using a competitive game mechanism; and
S7: implementing the network model on a network.

2. The allocation method according to claim 1 , wherein the VInP utility model in S2 is built as:
G ( p,q )= pq−cq,   (1)

wherein p represents an initial unit price of the slice resources given by the VInP, q represents a quantity of slice resources allocated by the VInP, and c represents a cost unit price of the slice resources;
the user utility model is:
F ( p,q )= u ( q )− l ( p,q )+ v ( q ),   (2)

wherein u(q) represents a utility generated from the slice resources acquired by user, l(p,q) represents a cost expended by the user for the resource, v(q) represents the user satisfaction, u(q)=wln(1+q), l(p,q)=pq,

v
⁡
(
q
)

=

ln
⁡
(

m
+
q

m

)

,

wherein w is a constant greater than 0 and represents a user weight, ln( ) represents a logarithmic function with the mathematical constant e as its base, m represents a quantity of resources requested by the user.

3. The allocation method according to claim 1 , wherein the building a node power consumption model in S3 specifically comprises:
calculating power consumption of a single node:
P i =P i SE +P i RE ,   (3)

wherein P i represents link power consumption of a accessed node i in a slice, P i SE represents transmission power consumption of the accessed node i, and P i RE represents reception power consumption of the accessed node i;
calculating node power consumption of the slice according to power consumption of the single node:
p i s =Σh i,l s p i ,  (4)

wherein h i,l s represents whether the node I is used in a path l, the path represents a complete link from a source node to a destination node, and s represents a label of the slice; and
determining a node price ρ i (p i s ) according to the node power consumption of the slice, wherein the node price is a function of the node power consumption, and ρ i (p i s ) is used as the node power consumption model.

4. The allocation method according to claim 3 , wherein the building a link power consumption model in S3 specifically comprises:
calculating a bandwidth of a link e:

x
e
s

=

∑

l
∈
Ψ

y
l
s

=

∑

l
∈
Θ

g

e
,
l

s

⁢

y
l
s

,

(
5
)

wherein a network controller calculates L s candidate paths from the source node to the destination node that meet user demands, paths from the source node to the destination node are denoted by Ψ and amount to O paths in total, the candidate paths, denoted by Θ, are comprised in all paths from the source node to the destination node, wherein Θ⊆Ψ, Ψ={l 1 , l 2 , . . . , l L s , . . . , l O f }, y l s represents bandwidth allocation on a path l, and g e,l s represents whether a link e is used in the path l of a slice s, l 1 is a first candidate path from the source node to the destination node, l 2 is a second candidate path, l L s is an L s th candidate path, and l O f is an O f th path from the source node to the destination node, wherein a method for calculating the candidate paths comprises:
starting, through using a primal-dual algorithm, from any feasible flow in a network with a flow value x≤v, increasing the flow values of links in the network and modify potentials of nodes; and
iterating the links and the nodes in the network until a flow that meets a predetermined constraint condition is obtained, to obtain a target candidate path, wherein v represents a flow value requested by the user, the flow value being a requested data transmission rate,

wherein if an initial flow value is greater than v, the target candidate path is directly obtained; and a link price ρ e (x e s ) is calculated according to the bandwidth of the link e, wherein the link price is a function of the link bandwidth, ρ e (x e s ) is used as the link power consumption model, and x e s represents the bandwidth of the link e.

5. The allocation method according to claim 1 , wherein the determining a revenue of each VInP according to the VInP utility model, the node power consumption model, and the

Assignees

• Univ Wuhan Tech

Inventors

• Yan Xin
• Xu Huixian
• Liu Ruijun

Classifications

• H04W72/53 Primary

  based on regulatory allocation policies · CPC title

• H04W24/02 Primary

  Arrangements for optimising operational condition · CPC title

• H04L41/0896 Primary

  Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities (flow or congestion control using dynamic resource allocation, e.g. in-call renegotiation, H04L47/76) · CPC title

• H04W24/06

  Testing, {supervising or monitoring} using simulated traffic · CPC title

• H04W4/24

  Accounting or billing · CPC title