Efficient Matching-Based Parallel Task Offloading in IoT Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10250409" target="_blank" >RIV/61989100:27240/22:10250409 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.3390/s22186906" target="_blank" >https://doi.org/10.3390/s22186906</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/s22186906" target="_blank" >10.3390/s22186906</a>

Result language

angličtina

Original language name

Efficient Matching-Based Parallel Task Offloading in IoT Networks

Original language description

Fog computing is one of the major components of future 6G networks. It can provide fast computing of different application-related tasks and improve system reliability due to better decision-making. Parallel offloading, in which a task is split into several sub-tasks and transmitted to different fog nodes for parallel computation, is a promising concept in task offloading. Parallel offloading suffers from challenges such as sub-task splitting and mapping of sub-tasks to the fog nodes. In this paper, we propose a novel many-to-one matching-based algorithm for the allocation of sub-tasks to fog nodes. We develop preference profiles for IoT nodes and fog nodes to reduce the task computation delay. We also propose a technique to address the externalities problem in the matching algorithm that is caused by the dynamic preference profiles. Furthermore, a detailed evaluation of the proposed technique is presented to show the benefits of each feature of the algorithm. Simulation results show that the proposed matching-based offloading technique outperforms other available techniques from the literature and improves task latency by 52% at high task loads.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Sensors (Basel, Switzerland)

ISSN

1424-8220

e-ISSN

—

Volume of the periodical

22

Issue of the periodical within the volume

18

Country of publishing house

CH - SWITZERLAND

Number of pages

22

Pages from-to

nestrankovano

UT code for WoS article

000859490100001

EID of the result in the Scopus database

2-s2.0-85138400462