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Published June 2016 | Published + Submitted
Book Section - Chapter Open

Joint Data Purchasing and Data Placement in a Geo-Distributed Data Market


This paper studies design challenges faced by a geo-distributed cloud data market: which data to purchase (data purchasing) and where to place/replicate the data (data placement). We show that the joint problem of data purchasing and data placement within a cloud data market is NP-hard in general. However, we give a provably optimal algorithm for the case of a data market made up of a single data center, and then generalize the structure from the single data center setting and propose Datum, a near-optimal, polynomial-time algorithm for a geo-distributed data market.

Additional Information

© 2016 Copyright held by the owner/author(s). This work is partially supported by NSF grants CNS-1254169, CNS-1319820, NETS-1518941, and BSF grant 2012348.

Attached Files

Submitted - 1604.02533.pdf

Published - p383-ren.pdf


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August 20, 2023
August 20, 2023