Multi-user computation unloading method and device based on chemical reaction optimization algorithm

Abstract

The invention discloses a multi-user computation unloading method and device based on a chemical reaction optimization algorithm. A computation unloading device collects real-time information of a mobile terminal and an edge server, and the real-time information comprises the CPU load, the current electric quantity, the network bandwidth and like information of the terminal and the state information of a virtual machine of the edge server, the completion time of an application and the energy consumption occupied weight of the terminal are adjusted so as to establish an application completion time model, a terminal energy consumption model and a scheduler module; according to the collected real-time information and the established model, a selection decision is worked out by adopting the multi-user computation unloading method based on the chemical reaction optimization algorithm to obtain a quasi-optimal result of an application program, thereby improving the application performance and reducing the terminal energy consumption.

Description

technical field [0001] The invention belongs to the technical field of mobile cloud computing, and relates to a multi-user computing offloading and resource allocation method in mobile edge computing, in particular to a multi-user computing offloading method and device based on a chemical reaction optimization algorithm. Background technique [0002] According to the forecast of Cisco Visual Networking Index, by 2021, the global mobile data traffic will reach 49 exabytes (EB) per month, which puts forward new requirements for the performance of mobile terminals and the data transmission rate of mobile networks. In addition, a new class of applications has also emerged, such as face recognition, mobile augmented reality, etc., which are sensitive to delay and require a lot of resources. However, the computing and storage resources of the mobile terminal are limited, especially the battery life is short, running such applications will bring high delay and increase the energy c...

AI Technical Summary

Problems solved by technology

However, in traditional mobile cloud computing, mobile terminals are connected to remote public clouds through mobile networks, such as Alibaba Cloud, Tencent Cloud, etc. Centrally deployed remote public clouds are far away from mobile terminals, and the remote public clouds are connected through mobile networks between the two. Data transmission often brings relatively high network delay. In order to solve the problem of high delay, a new computing mode--Mobile Edge Computing (MEC) was born, which deploys edge servers at the edge of the mobile terminal network , to extend the services provided by the remote cloud to a location closer to the mobile terminal, so that the mobile terminal can use the powerful resources of the edge server and transmit data with the edge server with low network delay

[0004] In the computing offloading methods of mobile edge computing, most methods have certain limitations in the multi-user computing offloading environment. When a large number of terminals submit offloading requests to the edge server, the edge server will make an offloading decision for the request and allocate a reasonable resources, but because the edge server is deployed at the edge of the network of the mobile terminal, resources such as computing and storage are limited, resources cannot always be allocated immediately for the request, and the offloading strategies between users will affect each other

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