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Mon 19 Jun 2017 15:00 - 15:20 at Vertex WS219 - Doctoral Symposium

Dynamically changing graphs are a powerful abstraction used to represent temporal relationships and connections occurring between data entities in various real-world organizations, such as social and telecommunication networks. The increasing volume, variety and velocity of graph-structured data in many application domains have led to a development of large-scale graph processing systems. However, current state-of-the-art graph processing systems do not provide efficient support for streaming graph scenarios. In this report, we describe and discuss stream graph processing, which narrows the problem of traditional graph processing by focusing on near real-time analysis of dynamic graph data constructed and maintained from stream sources, as opposed to processing of historical graph datasets loaded from a disk storage. We provide an outline of challenges in stream graph processing and present our preliminary approach to designing a stream graph processing system done as a part of early PhD work.

Mon 19 Jun

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

14:00 - 15:30
14:00
20m
Talk
Consistent Stream Processing
DEBS Doctoral Symposium
Lorenzo Affetti Politecnico di Milano
14:20
20m
Talk
A New Application Benchmark for Data Stream Processing Architectures in an Enterprise Context
DEBS Doctoral Symposium
Guenter Hesse Hasso Plattner Institute, Christoph Matthies Hasso Plattner Institute, Benjamin Reissaus Hasso Plattner Institute
14:40
20m
Talk
Raphtory: Decentralised Streaming for Temporal Graphs
DEBS Doctoral Symposium
Benjamin Steer Queen Mary University London, Félix Cuadrado Queen Mary University of London, Richard Clegg Queen Mary University London
15:00
20m
Talk
Large-Scale Stream Graph Processing
DEBS Doctoral Symposium
Domagoj Margan Imperial College London