☆ 4.6 Article

Harris Hawks optimization based hybrid deep learning model for efficient network slicing in 5G network

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2023)

Related references

Note: Only part of the references are listed.

Article Computer Science, Information Systems

5G network traffic control: a temporal analysis and forecasting of cumulative network activity using machine learning and deep learning technologies

Ramraj Dangi et al.

Summary: To provide better service to users, traffic forecasting is an important research area in 5G. A hybrid model called ARIMA-CNN-LSTM is proposed to overcome the inability of traditional deep learning models in accurately predicting network load during sudden changes in traffic conditions, by combining ARIMA, CNN, and LSTM. Comparative analysis shows that the proposed model outperforms other deep learning models in predicting output in both normal and unusual traffic conditions.

INTERNATIONAL JOURNAL OF AD HOC AND UBIQUITOUS COMPUTING (2023)

Add to Collection

Article Computer Science, Information Systems

Highly Accurate and Reliable Wireless Network Slicing in 5th Generation Networks: A Hybrid Deep Learning Approach

Sulaiman Khan et al.

Summary: This paper proposes a hybrid deep learning model for reconfigurable slicing and network management in 5G and 6G networks. The model utilizes convolutional neural networks and long short term memory networks for resource allocation, network reconfiguration, and slice selection, as well as optimizing network slices through statistical information. Experimental results demonstrate the applicability and accuracy of the proposed model.

JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT (2022)

Add to Collection

Review Chemistry, Analytical

Study and Investigation on 5G Technology: A Systematic Review

Ramraj Dangi et al.

Summary: This paper presents the characteristics and advantages of 5G technology as the latest generation of mobile networks, highlighting how businesses can utilize the opportunities brought by 5G.

SENSORS (2022)

Add to Collection

Article Medicine, General & Internal

An Improved Machine-Learning Approach for COVID-19 Prediction Using Harris Hawks Optimization and Feature Analysis Using SHAP

Kumar Debjit et al.

Summary: This paper proposes an improved machine learning model for early detection of COVID-19 and conducts experiments on publicly available COVID-19 data, achieving high prediction accuracy. The proposed method outperforms traditional algorithms and other machine learning methods in terms of performance and feature analysis capabilities, and discusses a graphical user interface as a potential tool.

DIAGNOSTICS (2022)

Add to Collection

Review Computer Science, Information Systems

ML-Based 5G Network Slicing Security: A Comprehensive Survey

Ramraj Dangi et al.

Summary: This paper introduces the concept and architecture of 5G network slicing, and discusses the use of machine learning and deep learning algorithms to address security issues in network slicing. By partitioning and customizing slices, 5G networks are able to provide different services while ensuring reliability and meeting user demands.

FUTURE INTERNET (2022)

Add to Collection

Article Computer Science, Hardware & Architecture

Optimal 5G network slicing using machine learning and deep learning concepts

Mustufa Haider Abidi et al.

Summary: Network slicing aims to support diverse applications with enhanced performance and flexibility by splitting the physical network into logical networks. The proposed model in this study utilizes a hybrid learning algorithm to optimize network slicing performance and accuracy.

COMPUTER STANDARDS & INTERFACES (2021)

Add to Collection

Article Computer Science, Hardware & Architecture

Dynamic-Adaptive AI Solutions for Network Slicing Management in Satellite-Integrated B5G Systems

Lei Lei et al.

Summary: The integrated terrestrial and non-terrestrial networks in 5G and beyond are envisioned to support dynamic, seamless, and differentiated services for emerging use cases. However, the increasing service heterogeneity and network complexity pose challenges in network management and resource orchestration. Network slicing and artificial intelligence (AI) are key in addressing these challenges, with dynamic-adaptive AI solutions playing a crucial role in dealing with concept drift.

IEEE NETWORK (2021)

Add to Collection

Article Communication

Importance of Internet Exchange Point (IXP) infrastructure for 5G: Estimating the impact of 5G use cases

Thomas Hoeschele et al.

Summary: While the Internet is widely spread, the shift from wired to wireless network access technology is ongoing. The impact of 5G on the Internet's core, specifically on interdomain traffic, is significant. Estimating and ranking 5G use cases is crucial for interdomain infrastructure providers and policymakers.

TELECOMMUNICATIONS POLICY (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

Fast density peak clustering for large scale data based on kNN

Yewang Chen et al.

KNOWLEDGE-BASED SYSTEMS (2020)

Add to Collection

Article Engineering, Electrical & Electronic

Artificial Intelligence for 5G and Beyond 5G: Implementations, Algorithms, and Optimizations

Chuan Zhang et al.

IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS (2020)

Add to Collection

Article Telecommunications

The LSTM-Based Advantage Actor-Critic Learning for Resource Management in Network Slicing With User Mobility

Rongpeng Li et al.

IEEE COMMUNICATIONS LETTERS (2020)

Add to Collection

Proceedings Paper Computer Science, Theory & Methods

Secure5G: A Deep Learning Framework Towards a Secure Network Slicing in 5G and Beyond

Anurag Thantharate et al.

2020 10TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE (CCWC) (2020)

Add to Collection

Article Computer Science, Information Systems

Flexible Resource Block Allocation to Multiple Slices for Radio Access Network Slicing Using Deep Reinforcement Learning

Yu Abiko et al.

IEEE ACCESS (2020)

Add to Collection

Article Computer Science, Hardware & Architecture

Deer Hunting Optimization Algorithm: A New Nature-Inspired Meta-heuristic Paradigm

G Brammya et al.

COMPUTER JOURNAL (2019)

Add to Collection

Article Engineering, Electrical & Electronic

Intelligent Resource Scheduling for 5G Radio Access Network Slicing

Mu Yan et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2019)

Add to Collection

Proceedings Paper Engineering, Electrical & Electronic

Real-Time Network Slicing with Uncertain Demand: A Deep Learning Approach

Nguyen Van Huynh et al.

ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC) (2019)

Add to Collection

Article Engineering, Electrical & Electronic

Toward In-Network Deep Machine Learning for Identifying Mobile Applications and Enabling Application Specific Network Slicing

Akihiro Nakao et al.

IEICE TRANSACTIONS ON COMMUNICATIONS (2018)

Add to Collection

Article Engineering, Electrical & Electronic

Toward In-Network Deep Machine Learning for Identifying Mobile Applications and Enabling Application Specific Network Slicing

Akihiro Nakao et al.

IEICE TRANSACTIONS ON COMMUNICATIONS (2018)

Add to Collection

Article Acoustics

LUMBAR ULTRASOUND IMAGE FEATURE EXTRACTION AND CLASSIFICATION WITH SUPPORT VECTOR MACHINE

Shuang Yu et al.

ULTRASOUND IN MEDICINE AND BIOLOGY (2015)

Add to Collection

Article Computer Science, Interdisciplinary Applications

Grey Wolf Optimizer

Seyedali Mirjalili et al.

ADVANCES IN ENGINEERING SOFTWARE (2014)

Add to Collection

Article Mathematics, Applied

A Glowworm Swarm Optimization Algorithm Based Tribes

Yongquan Zhou et al.

APPLIED MATHEMATICS & INFORMATION SCIENCES (2013)

Add to Collection

Article Computer Science, Artificial Intelligence

Simplifying Particle Swarm Optimization

M. E. H. Pedersen et al.

APPLIED SOFT COMPUTING (2010)

Add to Collection

© Peeref 2019-2024. All rights reserved.