Distributed dynamic service deployment method based on mobile edge computing

An edge computing and dynamic service technology, applied in computer components, constraint-based CAD, computing, etc., can solve problems such as the inability to meet the requirements of users and operators' system utility, and achieve efficient algorithm convergence time and system utility. The effect of sexual and efficient unloading

Active Publication Date: 2021-02-12
DALIAN UNIV OF TECH
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AI Technical Summary

Problems solved by technology

Conventional service deployment methods such as the nearest distance principle (DMP) cannot meet the requirements of users and operators

Method used

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  • Distributed dynamic service deployment method based on mobile edge computing
  • Distributed dynamic service deployment method based on mobile edge computing
  • Distributed dynamic service deployment method based on mobile edge computing

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Embodiment Construction

[0044] In order to make the purpose, technical solutions and advantages of the present invention clearer, the specific implementation of the present invention will be further described in detail below.

[0045] The example of the present invention provides a distributed dynamic service deployment method based on mobile edge computing, the method includes:

[0046] Step 1: Build a random mobility model to determine the utility of users and operators.

[0047] Step 2: Transform the long-term optimization problem in step 1) into an online optimization problem by using the Lyapunov optimization method.

[0048] The dynamic service queue of server k can be expressed as follows:

[0049] Q k (t+1)=max{Q k (t)+ΔD k (t)-D k ,0},

[0050] where the queue length Q k (t) represents the overloaded data volume of server k in time slot t. Variable ΔD k (t) represents the throughput of server k in time slot t. Step 1) The constraint C1 in the optimization problem can be obtained by...

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Abstract

The invention discloses a distributed dynamic service deployment method based on mobile edge computing, which considers the high mobility of a user and the limited storage capacity of an edge server,maximizes the long-term system utility while ensuring the stability of a storage queue of the server, and achieves efficient unloading in a mobile edge network environment. According to the method, the long-term system utility maximization problem is decomposed into the online Lyapunov drift and penalty function minimization problem by utilizing Lyapunov optimization. Under the condition of no priori knowledge of the future moving track of the user, the future system utility is obtained through a sampling average approximation algorithm. In addition, service deployment probability distributionis introduced, and a Markov approximation model is utilized to dynamically deploy service request data. Theoretical analysis shows that the hybrid strategy service deployment decision provided by theinvention is a progressive optimal solution. The invention provides a new method for distributed dynamic service data deployment.

Description

technical field [0001] The present invention relates to a method for distributed and dynamic deployment of user service data based on mobile edge computing in the academic field, and in particular to a dynamic service deployment method based on a Lyapunov model. Background technique [0002] The explosive growth of mobile devices has promoted the prosperity of new mobile applications. With the support of edge computing servers, users can enjoy low-latency services through task migration. However, the computing and storage capacity of a single server is limited, and the real-time requirements of mobile applications cannot be met. Building a ubiquitous mobile edge computing network through multi-server cooperation is expected to enable service migration in highly dynamic mobile networks. Conventional service deployment methods such as the closest distance principle (DMP) cannot meet the requirements of users and operators for system utility, and the deployment methods with ex...

Claims

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Application Information

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IPC IPC(8): G06F30/20G06F9/50G06K9/62G06F111/04
CPCG06F30/20G06F9/5027G06F2111/04G06F2209/502G06F18/295
Inventor 董沛然宁兆龙王小洁郭磊
Owner DALIAN UNIV OF TECH
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