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Hybrid collaborative computing unloading method and device, electronic equipment and storage medium

A computing offloading and equipment technology, applied in electrical components, network traffic/resource management, wireless communication, etc., can solve problems such as information exchange and task completion delay not guaranteed.

Active Publication Date: 2021-04-16
GUANGDONG POLYTECHNIC NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004]The main purpose of this invention is to propose a hybrid collaborative computing offloading method, which aims to solve the frequent information interaction with the base station and the delay in completing tasks in the existing centralized scheme Technical issues not guaranteed

Method used

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  • Hybrid collaborative computing unloading method and device, electronic equipment and storage medium
  • Hybrid collaborative computing unloading method and device, electronic equipment and storage medium
  • Hybrid collaborative computing unloading method and device, electronic equipment and storage medium

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Embodiment 1

[0063] The invention proposes a hybrid collaborative computing offloading method. Hybrid collaborative computing offload method for wireless communication such as Internet of Things etc.

[0064] figure 1 It is a flow chart of an embodiment of the hybrid collaborative computing offloading method of the present invention. In an embodiment of the present invention, as figure 1 As shown, the present invention proposes a hybrid collaborative computing offloading method, at least including steps:

[0065] S1. When the calculation amount of the task to be processed cannot be borne, send a task unloading request to be processed, and the unloading request of the task to be processed carries task division information;

[0066] There can be multiple user tasks, and each user task can be divided into multiple subtasks. Some subtasks will have dependencies among multiple subtasks.

[0067] Task segmentation information includes: several subtask information obtained from task segmenta...

Embodiment 2

[0133] Figure 4 It is a schematic structural diagram of an embodiment of the hybrid collaborative computing offloading device of the present invention, as Figure 4 As shown, a hybrid collaborative computing offloading device at least includes:

[0134] The unloading request module 10 is used to issue a pending task unloading request when the calculation amount of the pending task cannot be borne, and the pending task unloading request carries task division information;

[0135] There can be multiple user tasks, and each user task can be divided into multiple subtasks. Some subtasks will have dependencies among multiple subtasks.

[0136]Task segmentation information includes: several subtask information obtained from task segmentation and dependency information between several subtasks; a directed graph G(V,E) can be used to represent the dependency relationship between several subtasks, where each subtask The workload of the task and the size of the data to be transferre...

Embodiment 3

[0201] Figure 5 It is a schematic diagram of a physical structure of an electronic device provided according to an embodiment of the present invention. Based on the content of the above-mentioned embodiments, such as Figure 5 As shown, the electronic device may include: a processor (processor) 301, a memory (memory) 302, and a bus 303; wherein, the processor 301 and the memory 302 complete mutual communication through the bus 303; the processor 301 is used to call the memory stored in The computer program instructions in the memory 302 and operable on the processor 301 to execute the hybrid collaborative computing offloading methods provided by the above method embodiments include, for example:

[0202] S1. When the calculation amount of the task to be processed cannot be borne, send a task unloading request to be processed, and the unloading request of the task to be processed carries task division information;

[0203] S2. Design a task computing offloading model accordi...

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Abstract

The invention discloses a hybrid collaborative computing unloading method and device, electronic equipment and a storage medium, and the method comprises the steps: sending a to-be-processed task unloading request when the calculation amount of a to-be-processed task cannot be borne, the to-be-processed task unloading request carrying task segmentation information; designing a task calculation unloading model according to the feedback and task segmentation information of the to-be-processed task unloading request; and calculating task execution time delay according to the task calculation unloading model. According to the hybrid cooperative computing unloading method and device, the electronic equipment and the storage medium, the user task is divided into the plurality of sub-tasks, the dependency relationship among the plurality of sub-tasks is analyzed, and when the user computing resources are insufficient, the plurality of sub-tasks can be unloaded to other user equipment or an edge computing server, and by adopting a single-task hybrid unloading mechanism based on deep reinforcement learning, the task completion time delay can be reduced, the network bandwidth can be saved, the task completion efficiency can be improved, and the method can be universally applied to the technical fields of Internet of Things and the like.

Description

technical field [0001] The present invention relates to the technical field of mobile edge computing, in particular to a hybrid collaborative computing offloading method, device, electronic equipment, and storage medium. Background technique [0002] Mobile edge computing (MEC) improves the computing power of mobile devices by offloading computing tasks on mobile devices to MEC service execution, so it is a very promising technology, which is applied to the Internet of Vehicles (Vehicle Networks) and the Internet of Things. (Internet of Things) and Smart City (Smart City) and other fields. Compared with the centralized cloud computing system (Cloud Computing System), the distributed structure of the MEC system has many advantages, including reducing energy consumption and reducing delay [0003] Collaborative computing offloading, an approach that has only been considered by a few researchers in previous work. Existing computing offloading solutions generally do not divide...

Claims

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Application Information

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IPC IPC(8): H04W28/08H04W28/02H04W24/06
CPCY02D10/00
Inventor 蔡君丁可可刘燕罗建桢
Owner GUANGDONG POLYTECHNIC NORMAL UNIV