Dusit Niyato

A stochastic programming approach for risk management in mobile cloud computing

2018

The development of mobile cloud computing has brought many benefits to mobile users as well as cloud service providers. However, mobile cloud computing is facing some challenges, especially security-related problems due to the growing number …

Federated Learning in Mobile Edge Networks: A Comprehensive Survey

2019 · arXiv (Cornell University)

In recent years, mobile devices are equipped with increasingly advanced sensing and computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up countless possibilities for meaningful applications. Traditional cloudbased Machine Learning (ML) approaches …

Toward an Automated Auction Framework for Wireless Federated Learning Services Market

2020 · IEEE Transactions on Mobile Computing

In traditional machine learning, the central server first collects the data owners' private data together and then trains the model. However, people's concerns about data privacy protection are dramatically increasing. The emerging paradigm of federated …

Dynamic Contract Design for Federated Learning in Smart Healthcare Applications

2020 · IEEE Internet of Things Journal

Currently, the data collected by the Internet of Healthcare Things, i.e., healthcare oriented Internet of Things (IoT), still rely on cloud-based centralized data aggregation and processing. To reduce the need for transmission of data to …

Reputation-aware Hedonic Coalition Formation for Efficient Serverless Hierarchical Federated Learning

2021 · IEEE Transactions on Parallel and Distributed Systems

Amid growing concerns on data privacy, Federated Learning (FL) has emerged as a promising privacy preserving distributed machine learning paradigm. Given that the FL network is expected to be implemented at scale, several studies have …

Applications of Multi-Agent Reinforcement Learning in Future Internet: A Comprehensive Survey

2022 · IEEE Communications Surveys & Tutorials

Future Internet involves several emerging technologies such as 5G and beyond 5G networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of Things (IoTs). Moreover, the future Internet becomes heterogeneous and decentralized with a …

Optimal Stochastic Resource Allocation for Distributed Quantum Computing

2022 · arXiv (Cornell University)

With the advent of interconnected quantum computers, i.e., distributed quantum computing (DQC), multiple quantum computers can now collaborate via quantum networks to perform massively complex computational tasks. However, DQC faces problems sharing quantum information because …

Blockchain for Decentralized Know Your Customer (KYC) and Customer Due Diligence (CDD) Pipelines in the Metaverse

2023

Transactions conducted in the Metaverse must be validated in an interoperable and decentralized manner in order to prevent money laundering risks. Some processes to ensure that transactions are legal include the Know Your Customer (KYC) …

From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks

2023 · arXiv (Cornell University)

Generative Artificial Intelligence (GAI) possesses the capabilities of generating realistic data and facilitating advanced decision-making. By integrating GAI into modern Internet of Things (IoT), Generative Internet of Things (GIoT) is emerging and holds immense potential …

Compressing Deep Reinforcement Learning Networks with a Dynamic Structured Pruning Method for Autonomous Driving

2024 · arXiv (Cornell University)

Deep reinforcement learning (DRL) has shown remarkable success in complex autonomous driving scenarios. However, DRL models inevitably bring high memory consumption and computation, which hinders their wide deployment in resource-limited autonomous driving devices. Structured Pruning …

Approximated Coded Computing: Towards Fast, Private and Secure Distributed Machine Learning

2025 · IEEE Transactions on Emerging Topics in Computing

In a large-scale distributed machine learning system, coded computing has attracted wide-spread attention since it can effectively alleviate the impact of stragglers. However, several emerging problems greatly limit the performance of coded distributed systems. Firstly, …

Low Complexity Wireless Interference Identification in Antagonistic Environments Based on Multi-Task Learning

2025 · IEEE Transactions on Vehicular Technology

As the fundamental premise of anti-interference communication, wireless interference identification (WII) has garnered extensive research and yielded substantial results, especially for deep learning (DL)-enabled WII. However, existing studies are conducted typically under the closed-set assumption, …

Task-Oriented Low-Label Semantic Communication With Self-Supervised Learning

2025 · IEEE Transactions on Wireless Communications

Task-oriented semantic communication enhances transmission efficiency by conveying semantic information rather than exact messages. Deep learning (DL)-based semantic communication can effectively cultivate the essential semantic knowledge for semantic extraction, transmission, and interpretation by leveraging massive …

Context-Aware Semantic Communication for the Wireless Networks

2025 · arXiv (Cornell University)

In next-generation wireless networks, supporting real-time applications such as augmented reality, autonomous driving, and immersive Metaverse services demands stringent constraints on bandwidth, latency, and reliability. Existing semantic communication (SemCom) approaches typically rely on static models, …