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

Ren, Xiaoqi and London, Palma and Ziani, Juba and Wierman, Adam (2016) Joint Data Purchasing and Data Placement in a Geo-Distributed Data Market. In: SIGMETRICS '16 Proceedings of the 2016 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Science. ACM , New York, NY, pp. 383-384. ISBN 978-1-4503-4266-7. http://resolver.caltech.edu/CaltechAUTHORS:20170110-152309919

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Abstract

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.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1145/2896377.2901486DOIArticle
https://arxiv.org/abs/1604.02533arXivDiscussion Paper
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.
Funders:
Funding AgencyGrant Number
NSFCNS-1254169
NSFCNS-1319820
NSFNETS-1518941
Binational Science Foundation (USA-Israel)2012348
Record Number:CaltechAUTHORS:20170110-152309919
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170110-152309919
Official Citation:Xiaoqi Ren, Palma London, Juba Ziani, and Adam Wierman. 2016. Joint Data Purchasing and Data Placement in a Geo-Distributed Data Market. In Proceedings of the 2016 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Science (SIGMETRICS '16). ACM, New York, NY, USA, 383-384. DOI: http://dx.doi.org/10.1145/2896377.2901486
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:73397
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:10 Jan 2017 23:33
Last Modified:27 Jun 2019 20:03

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