Journal Article10.1007/s10515-021-00318-6
Efficient deep-reinforcement learning aware resource allocation in SDN-enabled fog paradigm
Abdullah Lakhan,Mazin Abed Mohammed,Omar Ibrahim Obaid,Chinmay Chakraborty,Karrar Hameed Abdulkareem,Seifedine Kadry +5 more
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About: This article is published in Automated software engineering. The article was published on 09 Jan 2022. The article focuses on the topics: Computer science & Reinforcement learning.
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Citations
Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism
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Offloading mechanisms based on reinforcement learning and deep learning algorithms in the fog computing environment: A comprehensive review
01 Jan 2023
TL;DR: In this article , a taxonomy of fog computing offloading mechanisms based on RL and DRL algorithms was divided into three major categories: value-based, policy-based and hybrid-based algorithms.
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ITS Based on Deep Graph Convolutional Fraud Detection Network Blockchain-Enabled Fog-Cloud
Abdullah Lakhan,Mazin Abed Mohammed,Dheyaa Ahmed Ibrahim,Seifedine Kadry,Karrar Hameed Abdulkareem +4 more
TL;DR: In this article , a serverless blockchain enable task scheduling (SBETS) system and algorithm framework is proposed to reduce processing and security blockchian costs for ITS applications in the system.
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A Novel CNN-TLSTM Approach for Dengue Disease Identification and Prevention using IoT-Fog Cloud Architecture
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References
Multi-Criteria Decision Making Methods
Evangelos Triantaphyllou
- 01 Jan 2000
TL;DR: With the continuing proliferation of decision methods and their variants, it is important to have an understanding of their comparative value and to choose the best decision-making method.
681
Tasks Scheduling and Resource Allocation in Fog Computing Based on Containers for Smart Manufacturing
Luxiu Yin,Juan Luo,Haibo Luo +2 more
TL;DR: The results showed that the proposed task-scheduling algorithm and reallocation scheme can effectively reduce task delays and improve the concurrency number of the tasks in fog nodes.
370
A Survey on Service Migration in Mobile Edge Computing
TL;DR: The cutting-edge research efforts on service migration in MEC are reviewed, a devisal of taxonomy based on various research directions for efficient service migration is presented, and a summary of three technologies for hosting services on edge servers, i.e., virtual machine, container, and agent are provided.
366
Spherical fuzzy Dombi aggregation operators and their application in group decision making problems
TL;DR: This paper defines some new operational laws by Dombi t-norm and t-conorm and develops an algorithm by using spherical fuzzy set information in decision-making matrix that is suitable and effective for decision process to evaluate their best alternative.
188
Multi-criteria decision-making method based on single-valued neutrosophic linguistic Maclaurin symmetric mean operators
Jian-qiang Wang,Yu Yang,Lin Li +2 more
TL;DR: This study centers on multi-criteria decision-making (MCDM) issues in which criteria are weighed differently and criteria values are expressed as single-valued neutrosophic linguistic numbers.
169