This tutorial serves as a comprehensive guide for understanding graph databases, focusing
on the fundamentals of graph theory while showcasing practical applications across various …

The challenge of executing extensive graph analyses in-memory intensifies with growing
graph sizes. This has given rise to disk-based external graph analytics systems that prioritize …

Graph processing plays a pivotal role in numerous large-scale applications, including social
and transportation networks. One of the primary challenges in handling large-scale graph …

The advent of online applications such as social networks has led to an unprecedented
scale of data and complex relationships among data. Hypergraphs are introduced to …

Recent studies showed that single-machine graph processing systems can be as highly
competitive as clusterbased approaches on large-scale problems. While several out-of-core …

Recent studies showed that single-machine graph processing systems can be as highly
competitive as cluster-based approaches on large-scale problems. While several out-of-core …

Focusing on the main research context represented by the issue of supporting big data
analytics over big graph data, this paper introduces and experimentally assesses the …

Smartphone applications are becoming increasingly popular. However, these applications
can suffer limited power budgets or malfunctioned sensing issues from their host devices …

Abstract Remote Direct Memory Access, or RDMA, is a technology that allows one computer
server to direct access the memory of another server without involving its CPU. Compared …

Processing large-scale graphs has increasingly become a critical component in a variety of
fields, from scientific computing to social analytics. The size of graphs of interest are …