Strategy method for minimizing energy consumption of mobile edge computing network under time-sensitive condition

An edge computing technology with minimum energy consumption, applied in the field of resource allocation technology, can solve problems such as only considering complete offloading technology

Active Publication Date: 2020-12-18
YUNNAN UNIV
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Problems solved by technology

Khalili, Ata considered the QoE requirements for time-sensitive computing tasks in the article "Jointresource ...

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  • Strategy method for minimizing energy consumption of mobile edge computing network under time-sensitive condition
  • Strategy method for minimizing energy consumption of mobile edge computing network under time-sensitive condition
  • Strategy method for minimizing energy consumption of mobile edge computing network under time-sensitive condition

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Embodiment Construction

[0101] The present invention assumes that the topology of the entire network is as figure 1 shown. Consider a wireless network in which there is a base station integrated with a MEC server that loads data computing tasks for users. There are K user terminals in the network, and each user terminal has the same maximum transmission capacity, and is independently distributed in a circular area with the MEC server as the center and a radius of 30 meters. Each user node in the network is equipped with a single antenna. remember set for users, remember It is a set of orthogonal subcarriers, each subcarrier has a bandwidth of B, and one subcarrier can only be allocated to one user. The path loss function of the network transmission in the simulation environment obeys the variance |β|d -2 The Rayleigh distribution of , where β represents the short-term channel fading coefficient, and d represents the distance between two nodes.

[0102] Using four parameters {R k , c k ,λ k...

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Abstract

The invention relates to a strategy method for minimizing energy consumption of a mobile edge computing network under a time-sensitive condition, which is characterized by comprising the following steps of: 1, an initialization stage: acquiring basic configuration information of the network by a node in the network at the stage, and initializing related parameters; 2, establishing an energy consumption minimum system optimization model; 3, solving an initial optimal unloading ratio according to constraint conditions; 4, when the constraint condition is met, returning to the step 2, and entering the next round of iterative loop calculation according to the block coordinate descent algorithm; and 5, obtaining the optimal unloading ratio, computing resources and subcarrier allocation expressions of different computing tasks of each user node after reaching the maximum limit frequency in a circulating manner. Under the condition that the QoE requirement of a user for a timeliness calculation task is met, the total energy consumption of the whole mobile edge calculation network is minimized through three strong coupling optimization variables including decoupling optimization, unloadingratio optimization, calculation resource allocation and subcarrier allocation.

Description

technical field [0001] The present invention relates to the technical field of information and communication engineering, in particular to the orthogonal frequency division multiple access technology in the wireless communication system, the partial offloading technology of mobile edge computing and the resource allocation technology. Background technique [0002] Mobile edge computing (Mobile edge computing, MEC) provides users with a high quality of experience (QoE) by placing servers close to end users. Compared with local computing, MEC helps to save energy, but it also causes communication delays. A number of studies have been conducted successively on the problem of meeting user quality experience requirements in a multi-user environment while reducing mobile device energy consumption as much as possible. In the article "Joint computation offloading and userassociation in multitask mobile edge", Dai Yueyue studied the minimization of the total energy consumption of th...

Claims

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Application Information

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IPC IPC(8): H04W28/16H04W28/08H04W72/04H04L29/08G06F17/10
CPCH04W28/16H04W28/08H04L67/10G06F17/10H04W72/52Y02D30/70
Inventor 赵明雄罗佳余俊杰李文涛包聆言邓彪
Owner YUNNAN UNIV
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