This paper presents AdaChain, a learning-based blockchain framework that adaptively
chooses the best permissioned blockchain architecture in order to optimize effective …

Disaggregated database systems achieve unprecedented excellence in elasticity and
resource utilization at the cloud scale and have gained great momentum from both industry …

Directed Acyclic Graph (DAG)-based blockchain represents a paradigm shift from
conventional blockchains, which has the potential to drastically improve throughput …

This paper articulates our vision for a learning-based untrustworthy distributed database. We
focus on permissioned blockchain systems as an emerging instance of untrustworthy …

This paper introduces a novel file system, ScaleDFS, designed to accelerate decentralized
file sharing for a private network, leveraging the potential of scaling file management based …

Federated Learning (FL) is a novel distributed, privacy-preserving machine learning
paradigm. Conventional FL suffers from drawbacks such as single point of failure and client …

Disaggregated memory systems achieve resource utilization efficiency and system
scalability by distributing computation and memory resources into distinct pools of nodes …

Consortium blockchain has been widely used in finance, e-government due to the
characteristics of controllability, supervision, and operability. However, traditional consortium …

Byzantine Fault-Tolerant (BFT) protocols have recently been extensively used by distributed
and decentralized data management systems with non-trustworthy infrastructures to …

Blockchain technology inherently necessitates redundant computation to achieve
consensus among untrusted parties because of its fundamental threat model. This …