公开(公告)号：US10736032B2

公开(公告)日：2020-08-04

申请号：US16193805

申请日：2018-11-16

Applicant: Huazhong University of Science and Technology

Inventor： Feng Lu ,  Ziqian Shi ,  Ruoxue Liu ,  Song Wu ,  Hai Jin

IPC: G06F9/46 ,  H04W52/02 ,  H04L29/08 ,  H04W88/02

Abstract: The present invention relates to a method for cloudlet-based optimization of energy consumption, comprises: building a cloudlet system that comprises: at least two cloudlets and a mobile device wirelessly connected to the cloudlets, so that the cloudlets provide the mobile device wirelessly connected thereto with cloud computing services; acquiring system data related to the mobile device from the cloudlet system for analyzing a data volume to be handled by the mobile device locally and setting an initial operating frequency FLinitial for a first processor of the mobile device according to the data volume; and based on a tolerable latency range T of a task queue, dynamically deciding a scheduling strategy for individual task of the task queue using a Markov Decision Process, and setting a present operating frequency FL for the first processor of the mobile device corresponding to the scheduling strategy, so as to enable the mobile device to complete the tasks within the tolerable latency range T with minimal energy consumption.

公开(公告)号：US20190208467A1

公开(公告)日：2019-07-04

申请号：US16193805

申请日：2018-11-16

Applicant: Huazhong University of Science and Technology

Inventor： Feng Lu ,  Ziqian Shi ,  Ruoxue Liu ,  Song Wu ,  Hai Jin

IPC: H04W52/02 ,  H04L29/08

Abstract: The present invention relates to a method for cloudlet-based optimization of energy consumption, comprises: building a cloudlet system that comprises: at least two cloudlets and a mobile device wirelessly connected to the cloudlets, so that the cloudlets provide the mobile device wirelessly connected thereto with cloud computing services; acquiring system data related to the mobile device from the cloudlet system for analyzing a data volume to be handled by the mobile device locally and setting an initial operating frequency FLinitial for a first processor of the mobile device according to the data volume; and based on a tolerable latency range T of a task queue, dynamically deciding a scheduling strategy for individual task of the task queue using a Markov Decision Process, and setting a present operating frequency FL for the first processor of the mobile device corresponding to the scheduling strategy, so as to enable the mobile device to complete the tasks within the tolerable latency range T with minimal energy consumption.