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Task unloading and parameter optimization method and system of MAR client in edge computing

An edge computing and optimization method technology, applied in computing, program control design, electrical digital data processing, etc., can solve problems such as large power consumption, network delay, and lack of computing power, and achieve the goal of reducing energy consumption and service delay Effect

Pending Publication Date: 2021-10-15
SHANDONG NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there are some challenges in developing MAR on mobile devices, (i) the battery capacity of mobile devices is limited, and running augmented reality applications requires a lot of power (ii) MAR is sometimes very computationally intensive, and mobile devices have limited resources and do not have such powerful computing ability
In order to solve the above problems, several different research directions have emerged. One of them is to study computationally intensive computer algorithms to run on mobile devices. Although it can reduce the delay to a certain extent, it is longer than the service delay expected by MAR.
The other is to transfer intensive calculations to the cloud server for calculation. Relying on the powerful CPU of the cloud server can significantly reduce the calculation delay, but in the process of unloading the video or picture to the cloud server, the time-varying and capacity of the wireless channel will be limited, which can easily cause network delays

Method used

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  • Task unloading and parameter optimization method and system of MAR client in edge computing
  • Task unloading and parameter optimization method and system of MAR client in edge computing
  • Task unloading and parameter optimization method and system of MAR client in edge computing

Examples

Experimental program
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Embodiment 1

[0050] Such as figure 1 As shown, this embodiment provides a method for task offloading and parameter optimization of a MAR client in edge computing. This embodiment uses this method to be applied to a server for illustration. It can be understood that this method can also be applied to a terminal , can also be applied to a terminal, a server and a system, and can be realized through the interaction between the terminal and the server. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or it can provide cloud services, cloud database, cloud computing, cloud function, cloud storage, network server, cloud communication, intermediate Cloud servers for basic cloud computing services such as software services, domain name services, security service CDN, and big data and artificial intelligence platforms. The terminal may be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smar...

Embodiment 2

[0146] This embodiment provides a system for task offloading and parameter optimization of a MAR client in edge computing.

[0147] MAR client task offloading and parameter optimization system in edge computing, including:

[0148] The fitness function determination module is configured to: determine the fitness function according to the real-time information of all tasks to be performed, the service characteristics of all MAR client users, the energy consumption of all MAR clients, the service period delay of all MAR clients, and the target detection function. degree function;

[0149] an offloading decision generation module configured to: generate an offloading decision according to the state of the edge server and the state of the MAR client;

[0150] A parameter optimization module configured to: use server selection and parameter optimization algorithms to calculate relevant parameters, return the calculation parameters to the MAR client for adjustment, and then the MAR...

Embodiment 3

[0193] This embodiment provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the method for task offloading and parameter optimization of the MAR client in edge computing as described in the first embodiment above is implemented in the steps.

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PUM

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Abstract

The invention belongs to the field of mobile communication, and provides a task unloading and parameter optimization method and system of an MAR client in edge computing. The method comprises the following steps: determining a fitness function according to real-time information of all tasks to be executed, business characteristics of all MAR client users, energy loss of all MAR clients, service period delays of all MAR clients and a target detection function; generating an unloading decision according to the state of the edge server and the state of the MAR client; carrying out related parameter calculation by using a server selection and parameter optimization algorithm, returning calculation parameters to the MAR client for adjustment, and then sending a single image frame to an associated edge server by the MAR client for target detection; and repeating the processes of parameter calculation and target detection until the fitness function converges, and obtaining a final parameter value and an unloading decision.

Description

technical field [0001] The invention belongs to the field of mobile communication, and in particular relates to a method and system for task offloading and parameter optimization of a mobile augmented reality (Mobile Augmented Reality, MAR) client in edge computing. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] With the continuous popularization of mobile devices and the rapid development of the Internet, the sensitivity of mobile applications to resource requirements and delays is also increasing, and the development of mobile edge computing has become a mainstream trend. Although traditional cloud computing can provide centralized services for application tasks, the distance between the cloud and users is very long. If the task is offloaded to the remote cloud, it will easily cause a huge end-to-end delay. The MAR we studied has great...

Claims

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Application Information

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IPC IPC(8): G06F9/445G06F9/48G06F9/50
CPCG06F9/44594G06F9/4881G06F9/5038G06F9/505G06F9/5072G06F2209/5021G06F2209/509
Inventor 翟临博李玉美杨峰赵景梅
Owner SHANDONG NORMAL UNIV
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