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UID:submissions.pasc-conference.org_PASC24_sess156_pos149@linklings.com
SUMMARY:P04 - Advancing Fault Tolerance in Graph Processing Engines Based 
 on Total Order Multicast
DESCRIPTION:Poster\n\nEkkehard Steinmacher, Fernando Pedone, Olaf Schenk, 
 and Patrick Eugster (Università della Svizzera italiana)\n\nData for many 
 problem domains are naturally well represented as graphs, and graph analyt
 ics has thus become an important tool in many areas of business and scienc
 e alike. In order to support increasingly large data sets and thus graph w
 ith increasingly large sets of vertices and edges, scalable graph analytic
 s engines like neo4j partition and distribute graph vertices across comput
 e nodes, leveraging hardware parallelism by processing queries in a distri
 buted manner. In short, queries are then propagated across compute nodes f
 ollowing the query logic and edges between the respective vertices. Such s
 ystems are also capable of supporting concurrent queries on overlapping su
 bgraphs and thus sets of compute edges with some minimal synchronization. 
 This poster leverages novel advances on totally ordered fault-tolerant com
 munication for real-time processing on large graphs. Total order multicast
  distinguishes between messages with different sets of destination process
 es. More precisely, as opposed to total order broadcast where all messages
  are indifferently issued to an entire group of processes, total order mul
 ticast distinguishes between different subgroups of processes, that can be
  addressed individually by processes issuing messages.\n\nSession Chair: E
 rik W. Draeger (Lawrence Livermore National Laboratory)
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