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Distributed uplink unloading strategy for mobile edge computing

An edge computing and strategy technology, applied in digital transmission systems, electrical components, transmission systems, etc., can solve problems such as lack of description and derivation of algorithms, and reduce core network signal loads

Active Publication Date: 2018-11-13
ELECTRIC POWER RES INST OF STATE GRID ZHEJIANG ELECTRIC POWER COMAPNY +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This invention reduces the signal load of the core network, and can host applications and services in a cheaper way. The description of the process is more detailed, but it lacks explanation and derivation of the algorithm

Method used

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  • Distributed uplink unloading strategy for mobile edge computing
  • Distributed uplink unloading strategy for mobile edge computing
  • Distributed uplink unloading strategy for mobile edge computing

Examples

Experimental program
Comparison scheme
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Embodiment

[0086] (1) Build a system model

[0087] First, the present invention establishes a network model based on the HetNet network scene.

[0088]Given a Macro Cell and N Small Cells, each Small Cell contains K mobile devices, and each macro base station MBS and small base station SCeNB are connected by wire. Small Cells are numbered N={1,2,...,N}, and mobile devices are numbered K={1,2,...,K}. Assuming that each user has a delay-sensitive task, the task can be split, and the users in the MacroCell can directly offload some tasks to their MEC Server (because the proportion of such users in the total number of users is very small, in order to simplify the model, its neglect). Users in Small Cells offload their tasks to the MEC Server of Macro Cells with the aid of their SCeNB.

[0089] Secondly, the present invention establishes a communication model.

[0090] It is considered that the uplink data transmission adopts the OFDMA method, that is, there is no interference in the Sma...

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PUM

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Abstract

The invention discloses a distributed uplink unloading strategy for mobile edge computing. The invention obtains an adaptive computing unloading strategy based on the Lyapunov theory and a proposed deviation degree update decision algorithm DUDA. The strategy comprises two main aspects: first, obtaining an optimal unloading decision set of users in Small Cells based on the Lyapunov theory on the premise of ensuring the system stability and minimized overhead; and secondly, proposing the DUDA to decide an unloading decision update sequence of the Small Cells in each time slot according to the deviation degree; and in the distributed uplink unloading strategy disclosed by the invention, it is considered that a user terminal has partial task unloading capability, that is, the tasks of a single users can be subdivided, a part of tasks are selected for local calculation according to specific application requirements and available resources with the target of minimizing the system overhead,and the remaining tasks are unloaded to an edge server of a Macro Cell in the HetNet scene. According to the distributed uplink unloading strategy disclosed by the invention, the system stability andthe optimal overhead are ensured by determining a drift penalty function, and an optimal unloading strategy set of users in the Small Cell under the condition is obtained.

Description

technical field [0001] The invention belongs to the field of mobile edge computing, in particular to a distributed uplink unloading strategy for mobile edge computing. Background technique [0002] At present, emerging user-oriented mobile applications such as face recognition, augmented reality, and interactive games have attracted widespread attention and quickly occupied the market. The common point of this type of application is that it requires high real-time data transmission, and the data processing process consumes a lot of energy. It is difficult for mobile devices with limited resources to strongly support the high demand of the application. MEC (Mobile edge computing, Mobile Edge Computing) proposed by ETSI is considered to be the most effective computing method for delay-sensitive applications. MEC can directly perform dynamic updates and load "micro-applications" on edge nodes such as devices, communication modules, and gateways, for real-time massive data proc...

Claims

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Application Information

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IPC IPC(8): H04L12/24
CPCH04L41/145
Inventor 汪自翔刘周斌邱雪松丰雷
Owner ELECTRIC POWER RES INST OF STATE GRID ZHEJIANG ELECTRIC POWER COMAPNY
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