Dynamic Scaling for Parallel Graph Computations
Summary: Dynamic scaling for vertex-partitioned graphs; balancing load, replication, and migration when scaling by k is intractable even for constant k. Proposes two parallel solutions: (i) extended consistent-hashing approximations with provable replication/migration bounds; (ii) a generic adaptive scaling scheme with VP-relative guarantees. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Wenfei Fan
- 2. Chunming Hu
- 3. Muyang Liu
- 4. Ping Lu
- 5. Qiang Yin
- 6. Jingren Zhou
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 444 | Parallelizing Sequential Graph Computations | 2017 | SIGMOD | 0.00022987918 |
| 664 | Relational Cloud: A Database-as-a-Service for the Cloud | 2011 | CIDR | 0.00018465843 |
| 2,595 | LEOPARD: Lightweight Edge-Oriented Partitioning and Replication for Dynamic Graphs | 2016 | VLDB | 8.4735292e-05 |
| 3,180 | Energy Management for MapReduce Clusters | 2010 | VLDB | 7.4302009e-05 |
| 3,573 | A Scalable Distributed Graph Partitioner | 2015 | VLDB | 6.954939e-05 |
| 4,473 | LogGP: A Log-based Dynamic Graph Partitioning Method | 2014 | VLDB | 6.1542362e-05 |
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