A Deep Deterministic Policy Gradient-Based Method for Enforcing Service Fault-Tolerance in MEC  

作　　者：Tingyan LONG Peng CHEN Yunni XIA Yong MA Xiaoning SUN Jiale ZHAO Yifei LYU 

机构地区：[1]College of Computer Science,Chongqing University,Chongqing 400044,China [2]School of Computer and Software Engineering,Xihua University,Chengdu 610039,China [3]School of Computer and Information Engineering,Jiangxi Normal University,Nanchang 330022,China [4]School of Computer and Information Science,Chongqing Normal University,Chongqing 401331,China

出　　处：《Chinese Journal of Electronics》2024年第4期899-909,共11页电子学报（英文版）

基　　金：National Key R&D Program of China (Grant No. 2018YFB1403602);Chongqing Technological Innovation Foundations (Grant Nos. cstc2019jscx-msxm0652 and cstc2019jscx-fxyd0385);Chongqing Key RD Project (Grant No. cstc2018jszxcyzd X0081);Jiangxi Key RD Project (Grant No. 2018 1ACE50029);Postgraduate Research and Innovation Project of Chongqing (Grant No. CYB22064);Graduate Research and Innovation Foundation of Chongging (Grant. No. CYS22112);Technological Program Organized by SGCC (Grant No. 52094020000U);Technology Innovation and Application Development Foundation of Chongqing (Grant No. cstc2020jscx-gksb X0010)。

摘　　要：Mobile edge computing(MEC) provides edge services to users in a distributed and on-demand way.Due to the heterogeneity of edge applications, deploying latency and resource-intensive applications on resourceconstrained devices is a key challenge for service providers. This is especially true when underlying edge infrastructures are fault and error-prone. In this paper, we propose a fault tolerance approach named DFGP, for enforcing mobile service fault-tolerance in MEC. It synthesizes a generative optimization network(GON) model for predicting resource failure and a deep deterministic policy gradient(DDPG) model for yielding preemptive migration decisions.We show through extensive simulation experiments that DFGP is more effective in fault detection and guaranteeing quality of service, in terms of fault detection accuracy, migration efficiency, task migration time, task scheduling time,and energy consumption than other existing methods.

关 键 词：Mobile edge computing SERVICE Generative optimization network Fault tolerance Deep deterministic policy gradient 

分 类 号：TN929.5[电子电信—通信与信息系统]