Scientific experiments, simulations, and modern applications generate large amounts of
data. Analysing resources required to process such big datasets is essential to identify …

Finding a resource-efficient way of processing large application datasets having complex
analytical and transactional queries with minimal replication is vital in reducing application …

Processing large datasets requires significant hardware resources and energy. Researchers
have observed that most database management systems could not utilize available …

Scientific experiments and contemporary applications generate substantial volumes of data
daily, posing a challenge for traditional database management systems (DBMS) that expend …

Most websites and applications are hosted on a public or private cloud. In-house
deployments also require dealing with system resources. Researchers have started …

Scientific experiments, simulations, and modern applications generate large amounts of
data. Data is stored in raw format to avoid the high loading time of traditional database …

The use of Semantic Web applications is increasing day by day and so is the volume of
Resource Description Framework (RDF) data. To manage the huge volume of RDF data, Hot …

Las bases de datos multimedia almacenan datos de gran tamaño, provocando problemas
en la recuperación eficiente de la información, aumentando los costos de ejecución y …