Parallel Offloading of Terminal Multitasking in Edge Computing

As emerging technologies like autonomous driving continue to develop, they bring a plethora of latency-sensitive tasks to mobile terminals. Traditional single-terminal, single-task offloading models result in considerable waiting latency for subsequent offloading tasks. This paper introduces MIMO (Multiple Input Multiple Output) technology and proposes a single-terminal multi-task parallel offloading algorithm. The algorithm enables the simultaneous transmission of multiple tasks within a single timeslot, achieving rapid offloading of computational tasks. It also considers the issue of transmission power allocation for offloaded tasks, thereby reducing the latency introduced by data transfer. Simulation analysis indicates that the proposed method performs better than other algorithms in reducing average task latency.

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Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/spic62469.2024.10691445
Citations
1
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.35

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article

Parallel Offloading of Terminal Multitasking in Edge Computing

Weinan Zhao, Lincong Zhang, Yongjun Li
1 citations
IoT and Edge/Fog Computing
0.35
article

Parallel Offloading of Terminal Multitasking in Edge Computing

Weinan Zhao, Lincong Zhang, Yongjun Li
article en
1 citations

Abstract

As emerging technologies like autonomous driving continue to develop, they bring a plethora of latency-sensitive tasks to mobile terminals. Traditional single-terminal, single-task offloading models result in considerable waiting latency for subsequent offloading tasks. This paper introduces MIMO (Multiple Input Multiple Output) technology and proposes a single-terminal multi-task parallel offloading algorithm. The algorithm enables the simultaneous transmission of multiple tasks within a single timeslot, achieving rapid offloading of computational tasks. It also considers the issue of transmission power allocation for offloaded tasks, thereby reducing the latency introduced by data transfer. Simulation analysis indicates that the proposed method performs better than other algorithms in reducing average task latency.

Shenyang Ligong University (CN), Anyang Institute of Technology (CN)
Shenyang Ligong University
Openalex Percentile: Top 38%
IoT and Edge/Fog Computing
0.35
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