Reliable Task Offloading for 6G-Based IoT Applications  

作　　者：Usman Mahmood Malik Muhammad Awais Javed Ahmad Naseem Alvi Mohammed Alkhathami 

机构地区：[1]Department of Computer Software Engineering,National University of Science and Technology(NUST),Islamabad,44000,Pakistan [2]Department of Electrical and Computer Engineering,COMSATS University Islamabad,Islamabad,45550,Pakistan [3]Information Systems Department,College of Computer and Information Sciences,Imam Mohammad Ibn Saud Islamic University(IMSIU),Riyadh,11432,Saudi Arabia

出　　处：《Computers, Materials & Continua》2025年第2期2255-2274,共20页计算机、材料和连续体(英文)

基　　金：supported and funded by theDeanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-RP23082).

摘　　要：Fog computing is a key enabling technology of 6G systems as it provides quick and reliable computing,and data storage services which are required for several 6G applications.Artificial Intelligence(AI)algorithms will be an integral part of 6G systems and efficient task offloading techniques using fog computing will improve their performance and reliability.In this paper,the focus is on the scenario of Partial Offloading of a Task to Multiple Helpers(POMH)in which larger tasks are divided into smaller subtasks and processed in parallel,hence expediting task completion.However,using POMH presents challenges such as breaking tasks into subtasks and scaling these subtasks based on many interdependent factors to ensure that all subtasks of a task finish simultaneously,preventing resource wastage.Additionally,applying matching theory to POMH scenarios results in dynamic preference profiles of helping devices due to changing subtask sizes,resulting in a difficult-to-solve,externalities problem.This paper introduces a novel many-to-one matching-based algorithm,designed to address the externalities problem and optimize resource allocation within POMH scenarios.Additionally,we propose a new time-efficient preference profiling technique that further enhances time optimization in POMH scenarios.The performance of the proposed technique is thoroughly evaluated in comparison to alternate baseline schemes,revealing many advantages of the proposed approach.The simulation findings indisputably show that the proposed matching-based offloading technique outperforms existing methodologies in the literature,yielding a remarkable 52 reduction in task latency,particularly under high workloads.

关 键 词：6G IOT task offloading fog computing 

分 类 号：TN929.5[电子电信—通信与信息系统]