Deep reinforcement learning approach for computation offloading in blockchain-enabled communications systems

Tanweer Alam; Arif Ullah; Mohamed Benaida

doi:10.1007/s12652-021-03663-2

ScienceGate Book Chapters

JOURNAL ARTICLE

Deep reinforcement learning approach for computation offloading in blockchain-enabled communications systems

Tanweer Alam Arif Ullah Mohamed Benaida

Year: 2022 Journal: Journal of Ambient Intelligence and Humanized Computing Vol: 14 (8)Pages: 9959-9972 Publisher: Springer Science+Business Media

DOI: 10.1007/s12652-021-03663-2

Get Full-Text PDF Get Analytical Report

Keywords:

Blockchain Computer science Scalability Reinforcement learning Distributed computing Database transaction Information exchange Computer security Computer network Telecommunications Artificial intelligence

Metrics

Cited By

18.24

FWCI (Field Weighted Citation Impact)

Refs

0.99

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Blockchain Technology Applications and Security

Physical Sciences → Computer Science → Information Systems

IoT and Edge/Fog Computing

Physical Sciences → Computer Science → Computer Networks and Communications

EEG and Brain-Computer Interfaces

Life Sciences → Neuroscience → Cognitive Neuroscience

Deep reinforcement learning approach for computation offloading in blockchain-enabled communications systems

Metrics

Citation History

Topics

Related Documents

Computation offloading in blockchain-enabled MCS systems: A scalable deep reinforcement learning approach

Scalable Blockchain-empowered Distributed Computation Offloading: A Deep Reinforcement Learning Approach

Cooperative Computation Offloading and Resource Allocation for Blockchain-Enabled Mobile-Edge Computing: A Deep Reinforcement Learning Approach

Deep Reinforcement Learning-Based Contract Incentive and Computation Offloading for Mobile Edge Computing-Enabled Blockchain

Blockchain enabled trusted task offloading scheme for fog computing: A deep reinforcement learning approach