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Lewis Tseng

Researcher at Boston College

Publications -  94
Citations -  1155

Lewis Tseng is an academic researcher from Boston College. The author has contributed to research in topics: Computer science & Consensus. The author has an hindex of 14, co-authored 81 publications receiving 795 citations. Previous affiliations of Lewis Tseng include Toyota & University of Illinois at Urbana–Champaign.

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Proceedings ArticleDOI

Iterative approximate byzantine consensus in arbitrary directed graphs

TL;DR: This paper proves a necessary and sufficient condition for the existence of iterative, algorithms that achieve approximate Byzantine consensus in arbitrary directed graphs, where each directed edge represents a communication channel between a pair of nodes, in synchronous arbitrary point-to-point networks.
Journal ArticleDOI

Federated Learning in Vehicular Networks: Opportunities and Solutions

TL;DR: In this paper, a federated vehicular network (FVN) is proposed to support distributed machine learning and federated learning in vehicular networks with centralized components and utilizes both DSRC and mmWave communication to achieve scalable and stable performance.
Journal ArticleDOI

Blockchain for Managing Heterogeneous Internet of Things: A Perspective Architecture

TL;DR: A preliminary study on an architecture that implements blockchain in managing heterogeneous IoT systems and the difficulties of integrating IoT and blockchain is presented to stimulate further effort and cross-disciplinary collaboration.
Journal ArticleDOI

Blockchain-based database in an IoT environment: challenges, opportunities, and analysis

TL;DR: This paper presents initial studies on the challenges and opportunities of using Blockchain as a database for Internet-of-Things (IoT) applications, and explores several reasonable consistency models for BBP-based database, and shows that such a database does not satisfy many consistency models under certain typical IoT environments.
Journal ArticleDOI

Blockchain and Fog Computing for Cyberphysical Systems: The Case of Smart Industry

TL;DR: In this article, the knowledge of blockchain and fog computing required to improve cyberphysical systems is presented, and emerging challenges and issues are also discussed, as well as their potential support for software and a wide spectrum of critical applications.