As someone who has spent the better part of two decades optimizing distributed systems—from early MapReduce clusters to ...

AI workloads are testing traditional centralized systems beyond their limits. Incentivizing distributed energy and data is the answer, says Greg Osuri, CEO of Akash Network.

The cost of underestimating security and compliance translates to catastrophic risks. Unfortunately, despite the growing complexity of modern distributed systems, many organizations still treat these ...

HAMBURG, Germany, June 12, 2025 – As the ISC 2025 main program comes to a close today, the conference organization announced that Rosa M. Badia, a prominent European scientist specializing in parallel ...

PySpark: deployed as the engine for distributed computing, optimizes computational efficiency in ETL processes by distributing data across multiple nodes for parallel processing, scaling to match ...

Parallel processing, an integral element of modern computing, allows for more efficiency in a wide range of applications. Here’s what you need to know.

Distributed computing frameworks such as MapReduce and Spark are often used to process large-scale data computing jobs. In wireless scenarios, exchanging data among distributed nodes would seriously ...

Distributed architecture is expected to be an effective solution for large-scale edge computing tasks in terminal devices. However, it remains a great challenge to resolve the conflict between ...

Keywords: data engineering, data science, high performance computing, distributed computing, dataframes Citation: Perera N, Sarker AK, Shan K, Fetea A, Kamburugamuve S, Kanewala TA, Widanage C, ...