Causality Tracking
Causality Tracking is a methodological framework in distributed systems that captures and enforces the partial ordering of events based on their causal dependencies, distinguishing it from mere timestamp-based synchronization by explicitly representing precedence relationships induced by message passing and shared state.
23
Publications
904
Citations
86
Authors
46
Institutions
Publications per year
2017–2026
5
23
Towards a Timely Causality Analysis for Enterprise Security
Yushan Liu, Mu Zhang, Li Ding et al. · 2018 · 177 citations · Full text
Jiaqing Du, Sameh Elnikety, Amitabha Roy et al. · 2013 · 120 citations · Full text
The potential dangers of causal consistency and an explicit solution
Peter Bailis, Alan Fekete, Ali Ghodsi et al. · 2012 · 80 citations
1–5 of 23
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Institut de Recherche en Informatique et Systèmes Aléatoires, France
2 publications · 28 citations
2
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2
h-index
1–5 of 86
46
NEC (United States)
Irving, United States
2 h-index
9 publications
1K citations
University of Utah
Salt Lake City, United States
2 h-index
7 publications
127 citations
Princeton University
Princeton, United States
2 h-index
3 publications
379 citations

Universidade Nova de Lisboa
Lisbon, Portugal
2 h-index
4 publications
44 citations
Institut de Recherche en Informatique et Systèmes Aléatoires
Rennes, France
1 h-index
2 publications
24 citations

Lawrence Livermore National Laboratory
Livermore, United States
1 h-index
5 publications
95 citations

University of Bologna
Bologna, Italy
1 h-index
2 publications
56 citations
The University of Texas at Austin
Austin, United States
1 h-index
1 publications
22 citations
1–8 of 46
Conference · 1 publications · 32 citations
1
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ESPR · 1 publications · 161 citations
1
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Repository · 1 publications · 16 citations
1
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Repository · 1 publications · 18 citations
1
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1 publications · 37 citations
1
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1–5