Recent advances in the Internet of Things (IoT) and pervasive and ubiquitous computing
provide a glimpse into the future of our planet and reveal exciting visions of many smart …

Streams of data can be continuously generated by sensors in various real-life applications
such as environment surveillance. Partially due to the inherited limitation of the sensors …

Inspired by the emerging Big Data challenge, in this paper we provide the description of
OLAP*, a Cloud based framework for supporting effective and efficient OLAP in Big Data …

Aggregate queries are useful tools in the context of sensor network‐based systems as they
retrieve knowledge from huge amounts of summarized readings to be exploited for …

Imminent massive-scale IoT deployments require a Cloud-Sensor architecture to facilitate an
ecosystem of friction-free integration and programmability. In addition to these two functional …

Genetic algorithms (GAs) are efficient non-gradient stochastic search methods. Parallel GAs
are proposed to overcome the deficiencies of sequential GAs, such as low speed and …

Nowadays, a leading instance of big data is represented by Web data that lead to the
definition of so-called big Web data. Indeed, extending beyond to a large number of critical …

Due to the high maintenance cost of traditional online auction system, poor load balance
ability and down problems occurring in the peak value of system access, this paper aims to …

Big data (eg,[1–3]) has become one of the most challenging research topics in current years.
Big data is everywhere, from social networks to web advertisements, from sensor and stream …

The problem of managing multidimensional stream cubes (ie, data cubes originated from
data streams) over Computational Grids still plays a critical role in Database and Data …