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Table 4 Comparative summary of existing data placement algorithms

From: A survey on data storage and placement methodologies for Cloud-Big Data ecosystem

Approach Fixed DS Constraint satisfaction Granul. Interm. DS Mult. appl. Data size Repl. Opt. criteria Add. info.
BDAP [85] Yes Meta-heuristic Fine Yes No No No Comm. cost No
Xu [92] No Meta-heuristic Coarse No No No No Data transf. number No
Yuan [78] Yes Recursive binary part. Coarse Yes Yes Yes No Data transf. number No
Kaya [100] No Hypergraph part. Coarse No No No No Data transf. number No
Zhao [87] Yes Hierarchical part. clust. + PSO Fine Yes No No No Data transf. number No
Wang [83] No Recursive clust. + ODPA Fine No No No No Data transf. number Yes
Yu [72] No Hypergraph part. Fine No No No No Cut weight Yes
Zhang [90] No Lagrance MIP relaxation Coarse No No No No Data access cost No
Hsu [91] No Fine No No No No Profiling-related metric Yes
LeBeane [97] No Hypergraph part. Fine No No No No Skew factor Yes
Lan [89] No Clustering-based PSO search Fine No No No No Volatility AMA, hurst distance Yes
BitDew [94] No   Fine Yes Yes No Yes Data dep. repl., fault tol. Yes
Kayoor [99] No Hypergraph part. Coarse No No No Yes Avg. query span Yes
Kosar [81] Yes   Fine Yes Yes No Yes   Yes
Scalia [86] No Multi-dimensional Knapsack problem Fine No Yes Yes No Storage cost Yes
SWORD [98] Yes Graph partition Fine   No   Yes Conflicting transactions Yes