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cs.IT updates on arXiv.org

Theoretical Limits of Language Model Alignment $f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models When Can Voting Help, Hurt, or Change Course? Exact Structure of Binary Test-Time Aggregation When Semantic Communication Meets Queueing: Cross-Layer Latency and Task Fidelity Optimization Convexity in Disguise: A Theoretical Framework for Nonconvex Low-Rank Matrix Estimation Conditional Diffusion Under Linear Constraints: Langevin Mixing and Information-Theoretic Guarantees Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval Expert Routing for Communication-Efficient MoE via Finite Expert Banks Contextual Memory-Enhanced Source Coding for Low-SNR Communications Realizable Bayes-Consistency for General Metric Losses Leveraging Code Automorphisms for Improved Syndrome-Based Neural Decoding A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy Optimization of CV-QKD Under Practical Constraints Benchmarking Wireless Representations: High-Dimensional vs. Compressed Embeddings for Efficiency and Robustness Real-Time Text Transmission via LLM-Based Entropy Coding over Fixed-Rate Channels SwiftChannel: Algorithm-Hardware Co-Design for Deep Learning-Based 5G Channel Estimation Evolving Token Communication with Parametric Memory Network Remote Action Generation: Remote Control with Minimal Communication The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions Stabilizing Private LASSO under Heterogeneous Covariates via Anisotropic Objective Perturbation Linear-Readout Floors and Threshold Recovery in Computation in Superposition Soft Graph Diffusion Transformer for MIMO Detection Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design Exponential families from a single KL identity MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness Diffusion-OAMP for Joint Image Compression and Wireless Transmission Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
Minimum Storage Regenerating Codes For All Parameters
Sreechakra Goparaju, Arman Fazeli, Alexander Vardy · 2016-02-15 · via cs.IT updates on arXiv.org

Regenerating codes for distributed storage have attracted much research interest in the past decade. Such codes trade the bandwidth needed to repair a failed node with the overall amount of data stored in the network. Minimum storage regenerating (MSR) codes are an important class of optimal regenerating codes that minimize (first) the amount of data stored per node and (then) the repair bandwidth. Specifically, an $[n,k,d]$-$(α)$ MSR code $\mathbb{C}$ over $\mathbb{F}_q$ is defined as follows. Using such a code $\mathbb{C}$, a file $\cal{F}$ consisting of $αk$ symbols over $\mathbb{F}_q$ can be distributed among $n$ nodes, each storing $α$ symbols, in such a way that: The file $\cal{F}$ can be recovered by downloading the content of any $k$ of the $n$ nodes; and the content of any failed node can be reconstructed by accessing any $d$ of the remaining $n-1$ nodes and downloading $α/(d-k+1)$ symbols from each of these nodes. Unfortunately, explicit constructions of $[n,k,d]$ MSR codes are known only for certain special cases: either low rate, namely $k/n<0.5$, or high repair connectivity, namely $d = n-1$. Although setting $d = n-1$ minimizes the repair bandwidth, it may be impractical to connect to all the remaining nodes in order to repair a single failed node. Our main result in this paper is an explicit construction of systematic-repair $[n,k,d]$ MSR codes for all possible values of parameters $n,k,d$. In particular, we construct systematic-repair MSR codes of high rate $k/n>0.5$ and low repair connectivity $k< d<n-1$. Such codes were not previously known to exist. In order to construct these codes, we solve simultaneously several repair scenarios, each of which is expressible as an interference alignment problem. Extension of our results beyond systematic repair remains an open problem.