Rapid moving in the technology and the need to respond to the massive changes in the big
data create another challenge for the government to make the deal with a huge amount of …

Debugging data processing logic in Data-Intensive Scalable Computing (DISC) systems is a
difficult and time consuming effort. Today's DISC systems offer very little tooling for …

Increasing transaction volumes have led to a resurgence of interest in distributed transaction
processing. In particular, partitioning data across several servers can improve throughput by …

Workload consolidation is a widely-used technique to maximize server resource utilization in
cloud and datacenter computing. Recent commodity CPUs support last-level cache (LLC) …

Data centers are experiencing an exponential increase in the amount of network traffic that
they have to sustain due to cloud computing and several emerging web applications. To …

In edge computing scenarios, the distribution of data and collaboration of workloads on
different layers are serious concerns for performance, privacy, and security issues. So for …

Abstract Virtual Operations Support Teams (VOSTs) are a novel form of organized
intelligence-gathering effort that has recently appeared in the emergency management and …

In this paper we introduce LDBC Graphalytics, a new industrial-grade benchmark for graph
analysis platforms. It consists of six deterministic algorithms, standard datasets, synthetic …

In-memory cluster computing platforms have gained momentum in the last years, due to their
ability to analyse big amounts of data in parallel. These platforms are complex and difficult-to …

Systems enabling the continuous processing of large data streams have recently attracted
the attention of the scientific community and industrial stakeholders. Data Stream Processing …