Search Results for author: Aruna Seneviratne

Found 12 papers, 2 papers with code

Federated Learning for Smart Healthcare: A Survey

no code implementations16 Nov 2021 Dinh C. Nguyen, Quoc-Viet Pham, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne, Zihuai Lin, Octavia A. Dobre, Won-Joo Hwang

Recent advances in communication technologies and Internet-of-Medical-Things have transformed smart healthcare enabled by artificial intelligence (AI).

Federated Learning Management

Cooperative Task Offloading and Block Mining in Blockchain-based Edge Computing with Multi-agent Deep Reinforcement Learning

no code implementations29 Sep 2021 Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, H. Vincent Poor

The convergence of mobile edge computing (MEC) and blockchain is transforming the current computing services in mobile networks, by offering task offloading solutions with security enhancement empowered by blockchain mining.

Edge-computing

BEdgeHealth: A Decentralized Architecture for Edge-based IoMT Networks Using Blockchain

no code implementations29 Sep 2021 Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne

The healthcare industry has witnessed significant transformations in e-health services by using mobile edge computing (MEC) and blockchain to facilitate healthcare operations.

Edge-computing

6G Internet of Things: A Comprehensive Survey

no code implementations11 Aug 2021 Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, Dusit Niyato, Octavia Dobre, H. Vincent Poor

The sixth generation (6G) wireless communication networks are envisioned to revolutionize customer services and applications via the Internet of Things (IoT) towards a future of fully intelligent and autonomous systems.

Autonomous Driving

Federated Learning for Industrial Internet of Things in Future Industries

no code implementations31 May 2021 Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, Dusit Niyato, H. Vincent Poor

The Industrial Internet of Things (IIoT) offers promising opportunities to transform the operation of industrial systems and becomes a key enabler for future industries.

Federated Learning

Federated Learning for Internet of Things: A Comprehensive Survey

no code implementations16 Apr 2021 Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, H. Vincent Poor

The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of intelligent services and applications empowered by artificial intelligence (AI).

Federated Learning

Conservative Plane Releasing for Spatial Privacy Protection in Mixed Reality

1 code implementation17 Apr 2020 Jaybie A. de Guzman, Kanchana Thilakarathna, Aruna Seneviratne

Aside from objects being detected, spatial information also reveals the location of the user with high specificity, e. g. in which part of the house the user is.

Mixed Reality

Secure Computation Offloading in Blockchain based IoT Networks with Deep Reinforcement Learning

no code implementations15 Aug 2019 Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne

How to implement offloading to alleviate computation burdens at MDs while guaranteeing high security in mobile edge cloud is a challenging problem.

Management reinforcement-learning

Privacy-Preserved Task Offloading in Mobile Blockchain with Deep Reinforcement Learning

no code implementations15 Aug 2019 Dinh C. Nguyen, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne

Blockchain technology with its secure, transparent and decentralized nature has been recently employed in many mobile applications.

Edge-computing reinforcement-learning

BreathRNNet: Breathing Based Authentication on Resource-Constrained IoT Devices using RNNs

no code implementations22 Sep 2017 Jagmohan Chauhan, Suranga Seneviratne, Yining Hu, Archan Misra, Aruna Seneviratne, Youngki Lee

Increasing popularity of IoT devices makes a strong case for implementing RNN based inferences for applications such as acoustics based authentication, voice commands, and edge analytics for smart homes.

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