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RS-Pooling: an adaptive data distribution strategy for fault-tolerant and large-scale storage systems

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Abstract

Storage pooling is a virtualization technique used in data centers to build upgradeable storage pools and to face up the explosive growth of information. In this technique, a randomized data distribution strategy (DDS) ensures the load balancing when adding new devices to the pool by using reallocation mechanisms. However, when applying fault-tolerant schemes to the storage pools, the system produces r redundant objects from a common data source and DDS must allocate them in different devices, which increases the complexity of the reallocation operations performed during the upgrade procedures. This paper presents RS-Pooling: an adaptive DDS for fault-tolerant and large-scale storage systems. RS-Pooling builds storage pools by grouping devices into disjointed sub-pools and ensures the effectiveness of fault-tolerant schemes by performing the allocation of redundant objects from a common data source in different sub-pools. In RS-Pooling, the first redundant object is allocated in random manner whereas the rest of them are allocated by using a cyclic list of sub-pools, this procedure minimizes the amount of reallocation operations, and fosters load balancing. We performed an emulation-based evaluation of RS-Pooling and a traditional DDS for storage pooling called RUSHp. The evaluation reveals that RS-Pooling improves the time efficiency of look up operations compared to that obtained from RUSHp. The evaluation also shows that, in upgrade procedures and regardless of the initial settlement, RS-Pooling requires significantly less reallocation operations than that of RUSHp for load balancing of fault-tolerant storage pools.

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Acknowledgments

This work has been funded by scholarship from CONACYT and UAM (Mexico). Authors express their gratitude to the anonymous referees that helped to improve the quality of this paper with their invaluable comments and suggestions.

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Authors and Affiliations

  1. Department of Electrical Engineering, UAM-Iztapalapa, México, D.F., Mexico

    Moisés Quezada-Naquid & Ricardo Marcelín-Jiménez

  2. LTI-CINVESTAV, Cd. Victoria, Tamaulipas, Mexico

    J. L. Gonzalez-Compeán

  3. ARCOS, Computer Science Department, Carlos III University, Madrid, Spain

    Jesus Carretero Perez

Authors
  1. Moisés Quezada-Naquid
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  2. Ricardo Marcelín-Jiménez
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  3. J. L. Gonzalez-Compeán
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  4. Jesus Carretero Perez
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Corresponding author

Correspondence to J. L. Gonzalez-Compeán.

Additional information

R. Marcelín-Jiménez also collaborates with the research team at the “Centro de Investigación en Tecnologías de la Información y Comunicación: INFOTEC”.

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Quezada-Naquid, M., Marcelín-Jiménez, R., Gonzalez-Compeán, J.L. et al. RS-Pooling: an adaptive data distribution strategy for fault-tolerant and large-scale storage systems. J Supercomput 72, 417–437 (2016). https://doi.org/10.1007/s11227-015-1569-7

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  • DOI: https://doi.org/10.1007/s11227-015-1569-7

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