SummaryStore is an approximate time-series store, designed for analytics, capable of
storing large volumes of time-series data (~ 1 petabyte) on a single node; it preserves high …

With the proliferation of attribute-rich machine-generated data, emerging real-time
monitoring, diagnosis, and visualization tools ingest and analyze such data across multiple …

The growth of High Performance Computer (HPC) systems increases the complexity with
respect to understanding resource utilization, system management, and performance issues …

Time-series databases are becoming an indispensable component in today's data centers.
In order to manage the rapidly growing time-series data, we need an effective and efficient …

Nowadays, massive data appears in the form of high-speed data streams. It is an important
and challenging problem to perform various mining tasks on data streams, such as finding …

The key to successful deployment of big data solutions lies in the timely distillation of
meaningful information. This is made difficult by the mismatch between volume and velocity …

Purpose The purpose of this paper is to propose a data prediction framework for scenarios
which require forecasting demand for large-scale data sources, eg, sensor networks …

Approximate stream processing algorithms, such as Count-Min sketch, Space-Saving,
support numerous applications across multiple areas such as databases, storage systems …

Modern data centers are the backbone of today's Internet-based services and applications.
With the explosive growth of the Internet data and a wider range of data-intensive …

Obtaining item frequencies in data streams with limited space is a well-recognized and
challenging problem in a wide range of applications. Sketch-based solutions have been …