4.8 Article

Communication-Efficient Semihierarchical Federated Analytics in IoT Networks

Related references

Note: Only part of the references are listed.
Article Automation & Control Systems

Adaptive Multivariate Data Compression in Smart Metering Internet of Things

Mayukh Roy Chowdhury et al.

Summary: The study proposes a novel multivariate data compression scheme for smart metering IoT, utilizing the cross correlation between different variables sensed by smart meters to reduce data dimension. Results indicate that the technique achieves impressive bandwidth savings while ensuring faithful reconstruction of data.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2021)

Article Engineering, Electrical & Electronic

Energy Efficient Federated Learning Over Wireless Communication Networks

Zhaohui Yang et al.

Summary: This paper investigates the problem of energy-efficient transmission and computation resource allocation for federated learning over wireless communication networks. An iterative algorithm is proposed to minimize energy consumption and numerical results show a reduction of up to 59.5% compared to conventional methods.

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (2021)

Proceedings Paper Computer Science, Hardware & Architecture

Non-orthogonal Multiple Access assisted Federated Learning for UAV Swarms: An Approach of Latency Minimization

Yuxiao Song et al.

Summary: In this study, a federated learning framework combined with non-orthogonal multiple access technology is proposed for a UAV swarm composed of a leader-UAV and follower-UAVs. The joint optimization of transmission durations, broadcasting duration, and computation rates aims to minimize latency in executing FL iterations until reaching a specified accuracy. Numerical results demonstrate the effectiveness of the proposed algorithm over baseline strategies.

IWCMC 2021: 2021 17TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE (IWCMC) (2021)

Article Computer Science, Information Systems

Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges

Latif U. Khan et al.

Summary: The Internet of Things will benefit from novel machine learning algorithms for network and application management. Federated learning presents a promising solution for on-device machine learning without data migration to the central cloud. While offering better privacy preservation, federated learning still raises privacy concerns.

IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2021)

Article Computer Science, Software Engineering

Regularized nonlinear acceleration

Damien Scieur et al.

MATHEMATICAL PROGRAMMING (2020)

Article Engineering, Electrical & Electronic

Federated Learning: Challenges, Methods, and Future Directions

Tian Li et al.

IEEE SIGNAL PROCESSING MAGAZINE (2020)

Article Computer Science, Information Systems

Federated Learning With Cooperating Devices: A Consensus Approach for Massive IoT Networks

Stefano Savazzi et al.

IEEE INTERNET OF THINGS JOURNAL (2020)

Article Computer Science, Theory & Methods

Accelerating Federated Learning via Momentum Gradient Descent

Wei Liu et al.

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS (2020)

Article Computer Science, Information Systems

A Flexible and Pervasive IoT-Based Healthcare Platform for Physiological and Environmental Parameters Monitoring

Mostafa Haghi et al.

IEEE INTERNET OF THINGS JOURNAL (2020)

Article Computer Science, Information Systems

Communication-Efficient Federated Learning for Wireless Edge Intelligence in IoT

Jed Mills et al.

IEEE INTERNET OF THINGS JOURNAL (2020)

Article Engineering, Civil

Parallel Transportation Systems: Toward IoT-Enabled Smart Urban Traffic Control and Management

Fenghua Zhu et al.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2020)

Article Computer Science, Information Systems

Convergence of Edge Computing and Deep Learning: A Comprehensive Survey

Xiaofei Wang et al.

IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2020)

Article Engineering, Electrical & Electronic

Computation Offloading Toward Edge Computing

Li Lin et al.

PROCEEDINGS OF THE IEEE (2019)

Article Computer Science, Information Systems

Toward Computation Offloading in Edge Computing: A Survey

Congfeng Jiang et al.

IEEE ACCESS (2019)

Article Automation & Control Systems

A Novel Mobile and Hierarchical Data Transmission Architecture for Smart Factories

Yun Luo et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2018)

Article Computer Science, Information Systems

A Fundamental Tradeoff Between Computation and Communication in Distributed Computing

Songze Li et al.

IEEE TRANSACTIONS ON INFORMATION THEORY (2018)

Article Computer Science, Information Systems

A Survey on Network Methodologies for Real-Time Analytics of Massive IoT Data and Open Research Issues

Shikhar Verma et al.

IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2017)

Article Engineering, Biomedical

A Hybrid Data Compression Scheme for Power Reduction in Wireless Sensors for IoT

Chacko John Deepu et al.

IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS (2017)

Review Computer Science, Hardware & Architecture

Device-to-Device Communication in Cellular Networks: A Survey

Pimmy Gandotra et al.

JOURNAL OF NETWORK AND COMPUTER APPLICATIONS (2016)

Article Mathematics, Applied

AIR Tools - A MATLAB package of algebraic iterative reconstruction methods

Per Christian Hansen et al.

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS (2012)

Article Automation & Control Systems

Asynchronous Broadcast-Based Convex Optimization Over a Network

Angelia Nedic

IEEE TRANSACTIONS ON AUTOMATIC CONTROL (2011)

Article Computer Science, Information Systems

Randomized gossip algorithms

Stephen Boyd et al.

IEEE TRANSACTIONS ON INFORMATION THEORY (2006)