Hierarchical Coding for Cloud Storage: Topology-Adaptivity, Scalability, and Flexibility

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2022-06-01

Author

Yang, Siyi
Hareedy, Ahmed
Calderbank, Robert
Dolecek, Lara

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In order to accommodate the ever-growing data from various, possibly independent, sources and the dynamic nature of data usage rates in practical applications, modern cloud data storage systems are required to be scalable, flexible, and heterogeneous. The recent rise of the blockchain technology is also moving various information systems towards decentralization to achieve high privacy at low costs. While codes with hierarchical locality have been intensively studied in the context of centralized cloud storage due to their effectiveness in reducing the average reading time, those for decentralized storage networks (DSNs) have not yet been discussed. In this paper, we propose a joint coding scheme where each node receives extra protection through the cooperation with nodes in its neighborhood in a heterogeneous DSN with any given topology. This work extends and subsumes our prior work on coding for centralized cloud storage. In particular, our proposed construction not only preserves desirable properties such as scalability and flexibility, which are critical in dynamic networks, but also adapts to arbitrary topologies, a property that is essential in DSNs but has been overlooked in existing works.

Subject Keywords

cooperative data protection, decentralized storage networks, flexibility, Joint hierarchical coding, scalability

URI

https://hdl.handle.net/11511/97706

Journal

IEEE Transactions on Information Theory

DOI

https://doi.org/10.1109/tit.2022.3149454

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

S. Yang, A. Hareedy, R. Calderbank, and L. Dolecek, “Hierarchical Coding for Cloud Storage: Topology-Adaptivity, Scalability, and Flexibility,” IEEE Transactions on Information Theory, vol. 68, no. 6, pp. 3657–3680, 2022, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/97706.