Derandomized Construction of Combinatorial Batch Codes
Srimanta Bhattacharya

TL;DR
This paper presents an explicit derandomized construction of combinatorial batch codes that significantly improves data item capacity while maintaining near-regular server load, advancing the design of efficient data distribution schemes.
Contribution
The work introduces a new explicit construction of c-uniform CBCs with high data capacity and near-regular server load, using improved analysis and derandomization of previous randomized methods.
Findings
Constructed c-uniform CBCs with m^{c-1+1/k} data items.
Servers are shown to be almost regular in data distribution.
Derandomization extends explicit constructions to a wider parameter range.
Abstract
Combinatorial Batch Codes (CBCs), replication-based variant of Batch Codes introduced by Ishai et al. in STOC 2004, abstracts the following data distribution problem: data items are to be replicated among servers in such a way that any of the data items can be retrieved by reading at most one item from each server with the total amount of storage over servers restricted to . Given parameters and , where and are constants, one of the challenging problems is to construct -uniform CBCs (CBCs where each data item is replicated among exactly servers) which maximizes the value of . In this work, we present explicit construction of -uniform CBCs with data items. The construction has the property that the servers are almost regular, i.e., number of data items stored in each server is in the range $[{nc \over…
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