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Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions

Many enterprise companies migrate their services and applications to the cloud to benefit from cloud computing advantages. Meanwhile, the rapidly increasing number of connected devices with the massive amount of generated data that use cloud services leads to high workload, congestion, and delay b...

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Main Authors: Akhlaqi, Mohammad Yahya, Mohd Hanapi, Zurina
Format: Article
Published: Elsevier 2023
Online Access:http://psasir.upm.edu.my/id/eprint/109067/
https://linkinghub.elsevier.com/retrieve/pii/S1084804522002090
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spelling my.upm.eprints.1090672024-10-14T03:59:44Z http://psasir.upm.edu.my/id/eprint/109067/ Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions Akhlaqi, Mohammad Yahya Mohd Hanapi, Zurina Many enterprise companies migrate their services and applications to the cloud to benefit from cloud computing advantages. Meanwhile, the rapidly increasing number of connected devices with the massive amount of generated data that use cloud services leads to high workload, congestion, and delay bottleneck in the centralized cloud architecture. Consequently, Mobile Edge Computing (MEC) is introduced as a new paradigm to expand cloud capabilities near the end devices. In addition, new technologies such as the Internet of Things (IoT), Autonomous Vehicles (AV), 5G, and Augmented Reality (AR) bring new demands and opportunities that MEC can make possible. Offloading delay-sensitive and computationally intensive tasks to nearby MEC nodes is an effective way that still is the most common open problem in MEC. The offloading problem in MEC has been widely studied in areas such as Vehicular Edge Computing (VEC), IoT, Radio Access Networks (RAN), and 5G but independently. Due to the high diversity of research areas, targeted issues, and adopted algorithms and techniques, finding the right research path in task offloading is highly demanding. To fill this gap, a comprehensive survey is conducted using the mixed-method systematic literature review involving qualitative and quantitative data from the studied papers. For each journal paper, the detailed information of the work area, targeted issue, formulation technique, optimization approach, adopted algorithms, evaluation techniques, performance matrices, dataset, utilized tools, and framework are extracted and analyzed using manual and automatic coding. Major offloading-related issues in MEC are investigated, and the taxonomy of journal papers based on adopted approaches is presented. For further future exploration, we suggest the potential areas of research, the contribution of the algorithms and technique, and the research direction in MEC. This review will give a quick and overall view of MEC’s latest issues and solutions. Elsevier 2023-03 Article PeerReviewed Akhlaqi, Mohammad Yahya and Mohd Hanapi, Zurina (2023) Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions. Journal of Network and Computer Applications, 212. art. no. 103568. pp. 1-47. ISSN 1084-8045; ESSN: 1095-8592 https://linkinghub.elsevier.com/retrieve/pii/S1084804522002090 10.1016/j.jnca.2022.103568
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Many enterprise companies migrate their services and applications to the cloud to benefit from cloud computing advantages. Meanwhile, the rapidly increasing number of connected devices with the massive amount of generated data that use cloud services leads to high workload, congestion, and delay bottleneck in the centralized cloud architecture. Consequently, Mobile Edge Computing (MEC) is introduced as a new paradigm to expand cloud capabilities near the end devices. In addition, new technologies such as the Internet of Things (IoT), Autonomous Vehicles (AV), 5G, and Augmented Reality (AR) bring new demands and opportunities that MEC can make possible. Offloading delay-sensitive and computationally intensive tasks to nearby MEC nodes is an effective way that still is the most common open problem in MEC. The offloading problem in MEC has been widely studied in areas such as Vehicular Edge Computing (VEC), IoT, Radio Access Networks (RAN), and 5G but independently. Due to the high diversity of research areas, targeted issues, and adopted algorithms and techniques, finding the right research path in task offloading is highly demanding. To fill this gap, a comprehensive survey is conducted using the mixed-method systematic literature review involving qualitative and quantitative data from the studied papers. For each journal paper, the detailed information of the work area, targeted issue, formulation technique, optimization approach, adopted algorithms, evaluation techniques, performance matrices, dataset, utilized tools, and framework are extracted and analyzed using manual and automatic coding. Major offloading-related issues in MEC are investigated, and the taxonomy of journal papers based on adopted approaches is presented. For further future exploration, we suggest the potential areas of research, the contribution of the algorithms and technique, and the research direction in MEC. This review will give a quick and overall view of MEC’s latest issues and solutions.
format Article
author Akhlaqi, Mohammad Yahya
Mohd Hanapi, Zurina
spellingShingle Akhlaqi, Mohammad Yahya
Mohd Hanapi, Zurina
Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions
author_facet Akhlaqi, Mohammad Yahya
Mohd Hanapi, Zurina
author_sort Akhlaqi, Mohammad Yahya
title Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions
title_short Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions
title_full Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions
title_fullStr Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions
title_full_unstemmed Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions
title_sort task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions
publisher Elsevier
publishDate 2023
url http://psasir.upm.edu.my/id/eprint/109067/
https://linkinghub.elsevier.com/retrieve/pii/S1084804522002090
_version_ 1814054688667992064
score 13.211869

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