PLATON · Platform-aware LArge-scale Time-Series prOcessiNg

Platform-aware LArge-scale Time-Series prOcessiNg

PLATON brought together a highly-experienced researcher in the field of the theory of concurrent and distributed computing with a hosting group which has world-leading expertise on data series management, indexing, and analysis to harness the difficulties of large-scale data series processing by realizing the data series processing performance and scalability goals. PLATON built a powerful index for large-scale data series processing, which facilitates processing of datasets that are orders of magnitude larger than the current datasets tested by state-of-the-art such indexes. This holistic data series indexing solution is a novel distributed data-series processing framework that efficiently addresses the critical challenges of exhibiting good speedup and ensuring high scalability in data series processing by taking advantage of the full computational capacity of modern clusters comprised of multi-core servers. PLATON provided also fault-tolerant solutions by developing the first non-blocking index, which by avoiding the use of locks, it allows to all threads to make progress independently of other threads’ speeds or failures. Through a wide range of configurations and using several real and synthetic datasets, the experimental analysis performed in PLATON demonstrates that the designed software achieves all its challenging goals. This software has been used to process large-scale collections of real data series, which has several important applications across many domains, such as in seismology, astrophysics, neuroscience, and other scientific fields.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз