Cloud computing resource allocation method in multi-user MEC system

A cloud computing and resource allocation technology, applied in resource allocation, computing, multiprogramming devices, etc., can solve the problem of not being able to balance the task completion rate and revenue well.

Active Publication Date: 2020-01-03
GUILIN UNIV OF ELECTRONIC TECH
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Problems solved by technology

[0005] The present invention provides a method for allocating cloud computing resources in a multi-user MEC system, which solves the problem in the prior art that the relationship between task completion rate and income cannot be well balanced

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  • Cloud computing resource allocation method in multi-user MEC system
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  • Cloud computing resource allocation method in multi-user MEC system

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Embodiment Construction

[0039] The present invention will be further described below in conjunction with examples, but the present invention is not limited to these examples.

[0040] A multi-user MEC system includes K (K ≥ 2, K is a positive integer) mobile users and a MEC server. Each mobile user has a computationally intensive task and requests to offload the task to the MEC server. For the MEC server, each offload request is a task s(k), k(k∈{1,2,...,K}). Every task for every mobile user has a strict deadline. The structural block diagram of the multi-user MEC system is as follows: figure 2 shown.

[0041]The process for the MEC server to obtain revenue is: the mobile user sends an offload request message to the MEC server. The offload request message includes task information and channel information collected by the client middleware; , the MEC server refuses to accept such tasks whose completion time is greater than or equal to the deadline, and initializes and sorts the remaining tasks acc...

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Abstract

The invention discloses a cloud computing resource allocation method in a multi-user MEC system. The method is based on task information of a mobile user and channel information between the mobile user and an MEC server. A miswork loss model is established by taking income maximization as a target; task waiting time is not included. Tasks of which the completion time is greater than or equal to the deadline are rejected by utilizing a function in the miss work loss model. EDD sorting is performed on remaining tasks. An execution sequence is determined by utilizing a branch and bound method; the MEC server executes the tasks of which the completion time is less than the deadline according to the execution sequence to acquire maximum income. According to the invention, benefit maximizationis taken as a target. An MEC server miss work minimization problem is modeled into an optimization problem taking a task execution sequence as an optimization variable. The problem is solved, a miswork loss model is established, a sorting algorithm based on a branch and bound method is provided to search for the optimal solution of the problem, tasks with small loss are refused as much as possiblewhile the deadline of an unloading task is met, and income maximization is achieved.

Description

technical field [0001] The present invention relates to the technical field of Mobile Edge Computing (MEC), in particular to a method for allocating cloud computing resources in a multi-user MEC system. Background technique [0002] With the development of the Internet of Things and 5G mobile communication technologies, it has become a trend to run computing-intensive and latency-critical applications on mobile devices such as smartphones, sensors, and wearable computing devices, but limited by their own computing power and energy, mobile devices Usually do not have the ability to run such applications. Mobile edge computing (MEC) realizes the vision of running computation-intensive and latency-critical applications on mobile devices by offloading computing tasks from mobile devices to edge servers with relatively abundant computing resources for execution. [0003] In the scenario of heavy business load, on the one hand, the MEC server is limited by computing power, and ca...

Claims

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Application Information

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IPC IPC(8): G06F9/50
CPCG06F9/5083G06F9/505Y02D10/00
Inventor 黄冬艳付中卫王波任英琦陈斌冯彤李浪肖培剑
Owner GUILIN UNIV OF ELECTRONIC TECH
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