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Placement Strategies for Internet-Scale Data Stream Systems

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3 Author(s)
Lakshmanan, Geetika T. ; IBM T.J. Watson Res. Center, Yorktown heights, NY ; Ying Li ; Strom, R.

Optimally assigning streaming tasks to network machines is a key factor that influences a large data-stream-processing system's performance. Although researchers have prototyped and investigated various algorithms for task placement in data stream management systems, taxonomies and surveys of such algorithms are currently unavailable. To tackle this knowledge gap, the authors identify a set of core placement design characteristics and use them to compare eight placement algorithms. They also present a heuristic decision tree that can help designers judge how suitable a given placement solution might be to specific problems.

Published in:

Internet Computing, IEEE  (Volume:12 ,  Issue: 6 )