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Blockchain and distributed ledger technologies are currently receiving tremendous attention in various disciplines. Our focus is enabling scalable, low-latency and reliable blockchain by means of mathematical modeling, analysis and algorithms.
Use cases are boundless. These include spectrum sharing, distributed computing, distributed machine learning, etc.
Publications
Publications
- H. Seo, J. Park, M. Bennis, W. Choi, "Communication and Consensus Co-Design for Low-Latency and Reliable Industrial IoT Systems," submitted to JSAC
- H-S. Kim, et, al, "Blockchained On-Device Federated Learning," to appear at IEEE communications letter, 2019.
- H. Seo, J. Park, M. Bennis, W. Choi, "Consensus-Before-Talk: Distributed Dynamic Spectrum Access via Distributed Spectrum Ledger Technology," IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), 2018.
- G. Lee, J. Park, W. Saad, and M. Bennis, "Performance Analysis of Blockchain systems with wireless mobile miners," submitted to IEEE Communications Letter 2019
Blockchained On-Device Federated Learning:
Blockchained On-Device Federated Learning:
- How to enable on-device machine learning without any centralized training data or coordination by utilizing a consensus mechanism in blockchain?
- What is the optimal block generation rate by considering communication, computation, and consensus delay?
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