Context: Big Data systems are a class of software systems that ingest, store, process and serve massive amounts of heterogeneous data, from multiple sources. Despite their undisputed impact in current society, their ...

The massive amount of tourists, citizens and traffic in big cities usually collapse busy areas causing transport inefficiency, unbalanced economic growth, crime, and nuisance among citizens and visitors. Therefore, the ...

Predictive models are an important element in dam safety analysis. They provide an estimate of the dam response faced with a given load combination, which can be compared with the actual measurements to draw conclusions ...

Traditional data centers are designed with a rigid architecture of fit-for-purpose servers that provision resources beyond the average workload in order to deal with occasional peaks of data. Heterogeneous data centers are ...

Data from utility meters (gas, electricity, water) is a rich source of information for distribution companies, beyond billing. In this paper we present a supervised technique, which primarily but not only feeds on meter ...

Histogramming is a tool commonly used in data analysis. Although its serial version is simple to implement, providing an efficient and scalable way to parallelize it can be challenging. This especially holds in case of ...

Motivated by the increasing popularity of hosting in-memory big-data analytics in cloud, we present a profiling methodology that can understand how different memory subsystems, i.e., cache and memory bandwidth, are susceptible ...

The amount of data that human activities generate poses a challenge to current computer systems. Big data processing techniques are evolving to address this challenge, with analysis increasingly being performed using ...