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A multi-task cross-server resource allocation method based on two-way auction in mec

A technology of server resources and allocation methods, which is applied in the field of mobile edge computing resource allocation, can solve problems such as inapplicability and low system efficiency, achieve high system efficiency, and resolve conflicts of interest

Active Publication Date: 2022-03-25
NORTHWESTERN POLYTECHNICAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the current method is only suitable for single-server task resource allocation, not for cross-server resource allocation, and the system efficiency is low; there may be a large number of people in the current base station coverage area (such as concentrated commercial buildings), and there are many MEC service requests. The task load of adjacent base stations may be very small. If the edge servers of multiple base stations can cooperate to form a system, more MEC service requests can be effectively served, and system efficiency can be improved.

Method used

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  • A multi-task cross-server resource allocation method based on two-way auction in mec
  • A multi-task cross-server resource allocation method based on two-way auction in mec
  • A multi-task cross-server resource allocation method based on two-way auction in mec

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0156] DAMB incentive mechanism:

[0157] (1) Sort the elements in A in ascending order:

[0158] A'=(a q1 =a 3 =2, a q2 =a 1 =3, a q3 =a 2 =4, a q4 =a 5 =5, a q5 =a 4 = 6).

[0159] (2) Sort the elements in B in descending order:

[0160] b'=(b 2，3 =10, b 3，1 =10, b 1，3 =9, b 4，1 =8, b 1，2 =7, b 1，1 =7, b 2，1 =6, b 4，2 =6, b 3，3 =6, b 1，4 =6, b 4，4 =6, b 2，5 =5, b 4，5 = 4).

[0161] (3)A′: Median:

[0162]

[0163] (4) Remove all B' less than Elements:

[0164] B c =(b2，3 =10, b 3，1 =10, b 1，3 =9, b 4，1 =8, b 1，2 =7, b 1，1 =7, b 2，1 =6, b 4，2 =6, b 3，3 =6, b 1，4 =6, b 4，4 =6, b 2，5 = 5).

[0165] (5) Delete greater than or equal to A' Elements:

[0166] A c =(a 3 =2, a 1 = 3).

[0167] (6) Find B c where the first element is b 2，3 =10, because a 3 ∈A c , then the task of buyer 2 can be offloaded to seller 3. From Table 2, it is known that the app deployment situation of seller 3 is R 3 = (1, 0, 1, 0), the task situation...

Embodiment 2

[0178] ASDA Incentive Mechanism

[0179] (1) Sort the elements in A in ascending order:

[0180] A'=(a q1 =a 3 =2, a q2 =a 1 =3, a q3 =a 2 =4, a q4 =a 5 =5, a q5 =a 4 =6);

[0181] (2) Traverse from the first element of A', for a 3 =2 It is known from Table 2 that App1 and App3 are deployed by Seller 3. Suppose we randomly select App1 to start the auction. All bids for seller 3App1 are extracted from B. Q from Table 2 1 and Q 2 It can be seen that only buyer 1 and buyer 2 need services, and we will form a new vector with the extracted bids then buyer 2 is the winner, b 1，3 =9 is the highest lost bid. N ω ={2}, M ω ={3}, φ(2)=3, g 2，3 =1,r 3，1 =0,q 2，1 =0. by Q 1 , Q 2 and Q 3 It can be seen that buyer 1, buyer 2, and buyer 3 need App3, and we extract all bids for seller 3App3 from B then buyer 2 is the winner, b 1，3 =9 is the highest lost bid. N ω ={2}, M ω ={3}, g 2，3 =2,r 3，3 =0,q 2，3 =0.

[0182] (3) For a 1 =3, according to R 1 , S...

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Abstract

The invention discloses a two-way auction-based multi-task cross-server resource allocation method in MEC, comprising: collecting information on the type and quantity of application programs deployed by each edge server of the seller, and determining that each edge server of the seller handles a single task The asking price information; collect the type, quantity, and maximum tolerance delay information of each mobile device of the buyer to be processed tasks; and determine the bidding information of each pending task in each mobile device of the buyer; combine the asking price information and bidding information It is only disclosed to the auctioneer. The auctioneer determines the price and the winners of both parties according to the price strategy, and completes the resource allocation according to the information of the winners of both parties. The price strategy is a two-way auction mechanism based on the break-even point or an application-separated two-way auction mechanism. The multi-task cross-server resource allocation method of the present invention has high system efficiency.

Description

technical field [0001] The invention belongs to the technical field of mobile edge computing resource allocation, in particular to a multi-task cross-server resource allocation method based on two-way auction in MEC. Background technique [0002] Mobile Edge Computing (MEC) is an emerging computing architecture that provides low latency and high reliability for mobile devices (MD) through mobile enhanced and small-scale data centers, namely edge servers. Sexual computing services. Due to resource constraints, only a limited number of apps can be deployed on an edge server. An MD may have multiple different application needs at the same time, and the nearest edge server may not be able to meet its needs. If multiple tasks are offloaded to other edge servers, it not only solves the problem that a single edge server cannot meet MD requirements, but also makes reasonable use of edge server resources to improve system efficiency. Edge servers can cooperate with each other to s...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q30/06G06Q30/08G06F9/50
CPCG06Q30/0611G06Q30/08G06F9/5027G06F2209/502
Inventor 刘家佳孙文郭鸿志张海宾宋强岳燕林
Owner NORTHWESTERN POLYTECHNICAL UNIV
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