Efficient anomaly detection and diagnosis in multivariate time-series data is of great
importance for modern industrial applications. However, building a system that is able to …

In the context of big data, if the task of multivariate time series data anomaly detection cannot
be performed efficiently and accurately, it will bring great security risks to industrial systems …

Numerous industrial environments and IoT systems in the real world contain a range of
sensor devices. These devices, when in operation, produce a large amount of multivariate …

Byzantine fault-tolerant algorithms promise agreement on a correct value, even if a subset of
processes can deviate from the algorithm arbitrarily. While these algorithms provide strong …

Blockchain is a decentralized distributed system on which a large number of financial
applications have been deployed. The consensus process in it plays an important role …

Retry---the re-execution of a task on failure---is a common mechanism to enable resilient
software systems. Yet, despite its commonality and long history, retry remains difficult to …

Modern databases embrace weak isolation levels to cater for highly available transactions.
However, weak isolation bugs have recently manifested in many production databases. This …

Transactions are used to maintain the data integrity of databases, and have become an
indispensable feature in modern Database Management Systems (DBMSs). Despite …

The Linked Data Benchmark Council's Social Network Benchmark (LDBC SNB) is an effort
intended to test various functionalities of systems used for graph-like data management. For …

Today's cloud databases offer strong properties, including serializability, sometimes called
the gold standard database correctness property. But cloud databases are complicated …