Storage Codes with Flexible Number of Nodes
Weiqi Li, Zhiying Wang, Taiting Lu, and Hamid Jafarkhani

TL;DR
This paper introduces flexible storage codes that enable data recovery from varying numbers of nodes, optimizing storage utilization and reducing latency in distributed systems.
Contribution
It proposes a new class of error-correcting codes with flexible node requirements, including constructions for LRC, PMDS, and MSR codes, and analyzes their performance.
Findings
Codes improve data access flexibility in distributed storage.
Simulation results demonstrate reduced latency and increased efficiency.
Theoretical constructions support practical implementation.
Abstract
This paper presents flexible storage codes, a class of error-correcting codes that can recover information from a flexible number of storage nodes. As a result, one can make a better use of the available storage nodes in the presence of unpredictable node failures and reduce the data access latency. Let us assume a storage system encodes information symbols over a finite field into nodes, each of size symbols. The code is parameterized by a set of tuples , satisfying and , such that the information symbols can be reconstructed from any nodes, each node accessing symbols. In other words, the code allows a flexible number of nodes for decoding to accommodate the variance in the data access time of the nodes. Code constructions are…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Data Storage Technologies · Caching and Content Delivery · Cryptography and Data Security
