There has been a growing interest in the graph-streaming setting where a continuous
stream of graph updates is mixed with graph queries. In principle, purely-functional trees are …

Temporal property graphs are graphs whose structure and properties change over time.
Temporal graph datasets tend to be large due to stored historical information, asking for …

The value of graph-based big data can be unlocked by exploring the topology and metrics of
the networks they represent, and the computational approaches to this exploration take on …

State-of-the-art streaming graph processing systems that provide Bulk Synchronous Parallel
(BSP) guarantees remain oblivious to the computation sparsity present in iterative graph …

The specific characteristics of graph workloads make it hard to design a one-size-fits-all
graph storage system. Systems that support transactional updates use data structures with …

Due to the growing need to process large graph and network datasets created by modern
applications, recent years have witnessed a surging interest in developing big graph …

With high computation power and memory bandwidth, graphics processing units (GPUs)
lend themselves to accelerate data-intensive analytics, especially when such applications fit …

Several emerging evolving graph application workloads demand support for efficient ad-hoc
analytics—the ability to perform ad-hoc queries on arbitrary time windows of the graph. We …

Graph processing has become an important part of various areas of computing, including
machine learning, medical applications, social network analysis, computational sciences …

ChronoGraph is a novel system enabling temporal graph traversals. Compared to snapshot-
oriented systems, this traversal-oriented system is suitable for analyzing information …