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The Capacity of Private Information Retrieval from Heterogeneous Uncoded Caching Databases
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abstract
We consider private information retrieval (PIR) of a single file out of $K$ files from $N$ non-colluding databases with heterogeneous storage constraints $\mathbf{m}=(m_1, \cdots, m_N)$. The aim of this work is to jointly design the content placement phase and the information retrieval phase in order to minimize the download cost in the PIR phase. We characterize the optimal PIR download cost as a linear program. By analyzing the structure of the optimal solution of this linear program, we show that, surprisingly, the optimal download cost in our heterogeneous case matches its homogeneous counterpart where all databases have the same average storage constraint $\mu=\frac{1}{N} \sum_{n=1}^{N} m_n$. Thus, we show that there is no loss in the PIR capacity due to heterogeneity of storage spaces of the databases. We provide the optimum content placement explicitly for $N=3$.
Forward citations
Cited by 2 Pith papers
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Improved Storage for Efficient Private Information Retrieval
A hybrid of MDS coding and uncoded partial replication achieves the known PIR storage-download curve at more points, but the general claim is only demonstrated by a single example.
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Breaking the MDS-PIR Capacity Barrier via Joint Storage Coding
Joint encoding of messages in MDS-coded storage can strictly increase private information retrieval rates beyond the separate-coding capacity for two parametric families of systems.
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