Big data is typically characterized with 4V's: Volume, Velocity, Variety and Veracity. When it
comes to big graphs, these challenges become even more staggering. Each and every of …

Incremental algorithms are important to dynamic graph analyses, but are hard to write and
analyze. Few incremental graph algorithms are in place, and even fewer offer performance …

Real-world graphs are constantly evolving, which demands updates of the previous analysis
results to accommodate graph changes. By using the memoized previous computation state …

Computing single-source shortest paths (SSSP) is one of the fundamental problems in
graph theory. There are many applications of SSSP including finding routes in GPS systems …

Abstract In this Big Data era, many large-scale and complex graphs have been produced
with the rapid growth of novel Internet applications and the new experiment data collecting …

In this thesis we develop a package of generic methods for boosting the velocity of graph
computations, regarding partitioning and incrementalization. The former is to deal with the …

In dynamically evolving graphs, one may be interested in continuously observing certain
properties of the graph. One approach for continuous monitoring is to re‐execute the graph …

Big graphs such as social networks or the internet network, biological networks, knowledge
graphs appear in many domains. However, processing these graphs rely on the accessibility …

In many applications involving dynamic graph structures one may be interested in
continuously observing certain properties of interest. We present here the result of our …