Search Results for author: Madhusanka Liyanage

Found 8 papers, 1 papers with code

Need of 6G for the Metaverse Realization

no code implementations28 Dec 2022 Bartlomiej Siniarski, Chamitha De Alwis, Gokul Yenduri, Thien Huynh-The, GÜrkan GÜr, Thippa Reddy Gadekallu, Madhusanka Liyanage

The concept of the Metaverse aims to bring a fully-fledged extended reality environment to provide next generation applications and services.

Edge-computing

A Survey on XAI for 5G and Beyond Security: Technical Aspects, Challenges and Research Directions

no code implementations27 Apr 2022 Thulitha Senevirathna, Vinh Hoa La, Samuel Marchal, Bartlomiej Siniarski, Madhusanka Liyanage, Shen Wang

The goal of using XAI in the security domain of 5G and beyond is to allow the decision-making processes of ML-based security systems to be transparent and comprehensible to 5G and beyond stakeholders, making the systems accountable for automated actions.

Decision Making Edge-computing +2

Roadmap for Edge AI: A Dagstuhl Perspective

no code implementations27 Nov 2021 Aaron Yi Ding, Ella Peltonen, Tobias Meuser, Atakan Aral, Christian Becker, Schahram Dustdar, Thomas Hiessl, Dieter Kranzlmuller, Madhusanka Liyanage, Setareh Magshudi, Nitinder Mohan, Joerg Ott, Jan S. Rellermeyer, Stefan Schulte, Henning Schulzrinne, Gurkan Solmaz, Sasu Tarkoma, Blesson Varghese, Lars Wolf

Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI.

Edge-computing

Federated Learning for Big Data: A Survey on Opportunities, Applications, and Future Directions

no code implementations8 Oct 2021 Thippa Reddy Gadekallu, Quoc-Viet Pham, Thien Huynh-The, Sweta Bhattacharya, Praveen Kumar Reddy Maddikunta, Madhusanka Liyanage

In this article, we present a survey on the use of FL for big data services and applications, aiming to provide general readers with an overview of FL, big data, and the motivations behind the use of FL for big data.

Federated Learning

Cannot find the paper you are looking for? You can Submit a new open access paper.