A cloud-edge-device collaborative offloading scheme with heterogeneous tasks and its performance evaluation  

作　　者：Xiaojun BAI Yang ZHANG Haixing WU Yuting WANG Shunfu JIN 

机构地区：[1]School of Information Science and Engineering,Yanshan University,Qinhuangdao 066004,China [2]Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province,Yanshan University,Qinhuangdao 066004,China

出　　处：《Frontiers of Information Technology & Electronic Engineering》2024年第5期664-684,共21页信息与电子工程前沿（英文版）

基　　金：supported by the National Natural Science Foundation of China(Nos.62273292,62276226,and 61973261)。

摘　　要：How to collaboratively offload tasks between user devices,edge networks(ENs),and cloud data centers is an interesting and challenging research topic.In this paper,we investigate the offoading decision,analytical modeling,and system parameter optimization problem in a collaborative cloud-edge device environment,aiming to trade off different performance measures.According to the differentiated delay requirements of tasks,we classify the tasks into delay-sensitive and delay-tolerant tasks.To meet the delay requirements of delay-sensitive tasks and process as many delay-tolerant tasks as possible,we propose a cloud-edge device collaborative task offoading scheme,in which delay-sensitive and delay-tolerant tasks follow the access threshold policy and the loss policy,respectively.We establish a four-dimensional continuous-time Markov chain as the system model.By using the Gauss-Seidel method,we derive the stationary probability distribution of the system model.Accordingly,we present the blocking rate of delay-sensitive tasks and the average delay of these two types of tasks.Numerical experiments are conducted and analyzed to evaluate the system performance,and numerical simulations are presented to evaluate and validate the effectiveness of the proposed task offloading scheme.Finally,we optimize the access threshold in the EN buffer to obtain the minimum system cost with different proportions of delay-sensitive tasks.

关 键 词：Edge computing Ofloading scheme Cloud-edge device collaboration Markov chain Cost function 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]