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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