Blockchain-Based Task Placement and Resource Management in Edge Computing: A Survey

As the metaverse progresses, it requires real-time, low-latency, and secure computing capabilities that conventional cloud-based systems cannot fully support. Multiaccess edge computing (MEC) addresses this demand by moving processing closer to the user; however, it also introduces new challenges in task placement, resource management, security, and trust. The blockchain is a promising enabler to address the limitations of trust, transparency, and centralized control in these systems. This survey systematically reviews 61 high-quality studies that explore blockchain-based solutions for task offloading and resource allocation in MEC. This work identifies the prevailing trends and research gaps using a structured method. The analysis reveals that over 60% of studies employ artificial intelligence-based techniques. Additionally, this work quantifies the adoption of various performance metrics from the literature and examines the case study distribution across application domains. Finally, this work outlines the technical challenges and opportunities for future research toward scalable, efficient, and trustworthy blockchain-enabled MEC frameworks.

Authors

Institutions

Publication Details

Journal
Electronics
Published
2025-08-26
DOI
https://doi.org/10.3390/electronics14173398
Citations
3
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
9.74

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Blockchain-Based Task Placement and Resource Management in Edge Computing: A Survey

Minsoo Hahn, Ibrahim Aliyu, Jinsul Kim, Abubakar Isah et al.
3 citations
Electronics
Blockchain Technology Applications and Security
9.74
article

Blockchain-Based Task Placement and Resource Management in Edge Computing: A Survey

Minsoo Hahn, Ibrahim Aliyu, Jinsul Kim, Abubakar Isah, Sulaiman Muhammad Rashid
article en
3 citations

Abstract

As the metaverse progresses, it requires real-time, low-latency, and secure computing capabilities that conventional cloud-based systems cannot fully support. Multiaccess edge computing (MEC) addresses this demand by moving processing closer to the user; however, it also introduces new challenges in task placement, resource management, security, and trust. The blockchain is a promising enabler to address the limitations of trust, transparency, and centralized control in these systems. This survey systematically reviews 61 high-quality studies that explore blockchain-based solutions for task offloading and resource allocation in MEC. This work identifies the prevailing trends and research gaps using a structured method. The analysis reveals that over 60% of studies employ artificial intelligence-based techniques. Additionally, this work quantifies the adoption of various performance metrics from the literature and examines the case study distribution across application domains. Finally, this work outlines the technical challenges and opportunities for future research toward scalable, efficient, and trustworthy blockchain-enabled MEC frameworks.

ElectronicsVol. 14(17)
Chonnam National University (KR), Astana Medical University (KZ)
Iran Telecommunication Research Center, Ministry of Science and ICT, South Korea, Institute for Information and Communications Technology Promotion
Openalex Percentile: Top 2%
Blockchain Technology Applications and Security
9.74
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Blockchain-Based Task Placement and Resource Management in Edge Computing: A Survey — Minsoo Hahn, Ibrahim Aliyu, et al. · Electronics (2025) | TGRS Research Map | TGRS