International Journal of Computational Intelligence Systems

Volume 10, Issue 1, 2017, Pages 521 - 539

Combination Replicas Placements Strategy for Data sets from Cost-effective View in the Cloud*

Authors
Received 25 July 2015, Accepted 13 December 2016, Available Online 1 January 2017.
DOI
10.2991/ijcis.10.1.521How to use a DOI?
Keywords
Cloud environment; Cost-effective; Replicas placements; Pseudo-replicas; Replicas
Abstract

In the cloud storage system, data sets replicas technology can efficiently enhance data availability and thereby increase the system reliability by replicating commonly used data sets in geographically different data centers. Most current approaches largely focus on system performance improvement by placing replicas for an independent data set, omitting the generation relationship among data sets. Furthermore, cost is an important element in deciding replicas number and their stored places, which can cause great financial burden for cloud clients because the cost for replicas storage and consistency maintenance may lead to high overhead with the number of new replicas increased in a pay-as-you-go paradigm. In this paper, we propose a combination strategy of real-replicas and pseudo-replicas (by computation from its provenance) from cost-effective view in order to achieve the minimum data set management cost, not only for the independent data sets but also for related data sets with generation relationships. We first define cost models that fit into the cloud computing paradigm, including data sets storage, computation and transfer costs, and then develop a new data set management cost model, helping to achieve a multi-criteria optimization of data set management. After that, a minimum cost benchmarking approach for the best trade-off between real-replicas and pseudo-replicas is proposed once decision to add a replica has been made. Then, a more practical and reasonable genetic algorithm as an alternative procedure for generating optimal or near-optimal solution is given in order to identify the suitable replicas storage places. Finally, we present simulations setups and results that provide a first validation of our strategy. Both the theoretical analysis and simulations conducted on general (random) data sets as well as specific real world applications have shown efficiency and effectiveness of the improved system brought by the proposed strategy in cloud computing environment.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
10 - 1
Pages
521 - 539
Publication Date
2017/01/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.10.1.521How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Xiuguo Wu
PY  - 2017
DA  - 2017/01/01
TI  - Combination Replicas Placements Strategy for Data sets from Cost-effective View in the Cloud*
JO  - International Journal of Computational Intelligence Systems
SP  - 521
EP  - 539
VL  - 10
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.10.1.521
DO  - 10.2991/ijcis.10.1.521
ID  - Wu2017
ER  -