摘要：With the growing popularity of Internet of Things (IoT), Mobile Edge Computing (MEC) has emerged for reducing the heavy workload at the multi-cloud core network by deploying computing and storage resources at the edge of network close to users. In IoT, services are data-intensive and event-driven, resulting in extensive dependencies among services. Traditional task offloading schemes face significant challenges in the IoT scenario with service dependencies. To this end, this paper proposes an intelligent approach for minimizing latency and energy consumption which jointly considers the task scheduling and resource allocation for dependent IoT services in MEC. Specifically, we establish the system model, communication model as well as computing model for performance evaluation by fully considering the dependent relationships among services, and an optimization problem is proposed for minimizing the delay and energy consumption simultaneously. Then, we design a layered scheme to deal with the service dependencies, and present detailed algorithms to intelligently obtain optimal task scheduling and resource allocation policies. Finally, simulation experiments are carried out to validate the effectiveness of the proposed scheme. ? 2023, The Author(s).

ISSN号：2192-113X

卷、期、页：卷12期1

发表日期：2023-07-18

影响因子：0.000000

期刊分区（SCI为中科院分区）：三区

收录情况：SCI（科学引文索引印刷版）,EI（工程索引）,SCIE（科学引文索引网络版）

发表期刊名称：Journal of Cloud Computing

通讯作者：陈杰,冷亚静

第一作者：黄霁崴

论文类型：期刊论文

论文概要：陈杰,冷亚静,黄霁崴，An intelligent approach of task offloading for dependent services in Mobile Edge Computing，Journal of Cloud Computing，2023，卷12期1

论文题目：An intelligent approach of task offloading for dependent services in Mobile Edge Computing