Cloud storage systems are now mature enough to handle a massive volume of
heterogeneous and rapidly changing data, which is known as Big Data. However, failures …

Big data applications are currently used in many application domains, ranging from
statistical applications to prediction systems and smart cities. However, the quality of these …

The application of frequent patterns in classification has demonstrated its power in recent
studies. It often adopts a two-step approach: frequent pattern (or classification rule) mining …

The state-of-the-art approaches for tracking data provenance on high-performance
computing (HPC) systems are either supported by file systems or relational databases …

With the rapid advance of big data and cloud computing, building high quality big data
systems in different application fields has gradually became a popular research topic in …

Provenance describes detailed information about the history of a piece of data, containing
the relationships among elements such as users, processes, jobs, and workflows that …

Blockchain is an enabler of many emerging decentralized applications in areas of
cryptocurrency, Internet of Things, smart healthcare, among many others. Although various …

Methods and apparatus are provided for analytical processing of provenance data for High
Performance Computing workflow optimization. Prediction models for a workflow composed …

Data replication is a key technique to achieve high data availability, reliability, and optimized
performance in distributed storage systems. In recent years, with emerged new storage …

Object-based parallel file systems have emerged as promising storage solutions for high-
performance computing (HPC) systems. Despite the fact that object storage provides a …