Deployment optimization of multi-stage investment portfolio service and hybrid intelligent algorithm under edge computing.

ABSTRACT: The purposes are to improve the server deployment capability under Mobile Edge Computing (MEC), reduce the time delay and energy consumption of terminals during task execution, and improve user service quality. After the server deployment problems under traditional edge computing are analyzed and researched, a task resource allocation model based on multi-stage is proposed to solve the communication problem between different supporting devices. This model establishes a combined task resource allocation and task offloading method and optimizes server execution by utilizing the time delay and energy consumption required for task execution and comprehensively considering the restriction processes of task offloading, partition, and transmission. For the MEC process that supports dense networks

SUBMITTER: Zhang X 

PROVIDER: S-EPMC8177502 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature