arXiv subjects

Rithwik Kerur

Publications and source records attributed to Rithwik Kerur.

3 recordsLinked to original sources

arXiv2026

eAVID: Asynchronous Verifiable Information Dispersal with Post-Dissemination Pruning

Asynchronous verifiable information dispersal (AVID) lets a sender spread a message across $N=3F+1$ nodes such that it remains recoverable despite up to $F$ Byzantine failures. Because dispersal must complete on $N-F$ responses, standard AVID protocols fix a $(F{+}1,\, N)$ erasure code and pay a $3\times$ storage blowup, whereas a synchronous system achieves the optimal $3/2\times$. This cost is paid permanently: the per-node footprint is fixed at dispersal time and does not adapt when the network turns out to be healthy and all $N$ nodes respond. We present eAVID, an AVID protocol that decouples the storage a node retains from the fragments it was sent. eAVID encodes the message with a single $(2F{+}1,\, 2N)$ Reed-Solomon code, commits to all $2N$ fragments under one Merkle root, and sends each node two distinct fragments. This approach uses the same dispersal bandwidth as the standard scheme. Dispersal completes on $N-F$ responses, as in the original AVID. Our divergence comes post-commit: nodes continue to collect responses asynchronously, and once a node has heard a Done over its adopted root from all $N$ nodes, it can safely discard one of its two fragments unilaterally. Because fragments are disjoint across nodes, at least $2F{+}1$ verified fragments survive. Pruning requires no certificate, no coordination among storage nodes, and no re-encoding. Reconstruction is unchanged as any $2F{+}1$ verified fragments decode the message regardless of how fragments are distributed. eAVID halves steady-state per-node storage relative to the $(F{+}1,\, N)$ baseline when the network is healthy, and degrades gracefully to the baseline footprint when it is not.

cs.DC↗

arXiv2026

Finding Nemo-Nemo: CFT DAG-based Consensus in the WAN

This paper introduces Nemo-Nemo, a practical crash-fault tolerant (CFT) consensus protocol designed to outperform existing protocols in wide-area networks by bridging design principles from the CFT and Byzantine-fault tolerant (BFT) worlds. By structuring command propagation through a causally ordered DAG, Nemo-Nemo allows all consensus replicas to propose commands with a naturally self-regulating communication regime. By exploiting multi-leader architecture, Nemo-Nemo avoids the performance bottleneck inherent to single-leader protocols. By separating command dissemination from consensus logic, Nemo-Nemo handles challenging network conditions even when consensus commits are stalled. Moreover, leader proposals that miss a deadline are never dropped, but deterministically deferred and executed later, preserving throughput under transient network delays. And by enabling Nemo-Nemo to commit on a DAG in just two network hops, it matches the latency of existing CFT systems, while achieving significantly higher throughput. The result is a robust, deployable system: the first DAG-based CFT consensus protocol proven to exceed state-of-the-art wide-area network performance in both speed and resilience.

cs.DC↗

arXiv2026

eAID: Elastic Asynchronous Information Dispersal with Post-Dissemination Pruning

Spreading and storing erasure-coded data effectively in distributed systems is challenging in practical settings. The dissemination of erasure-coded information is typically designed to complete only after receiving messages from $(N-F)$ nodes, thereby preparing for the worst-case, but rare, scenario of $F$ failures. In steady state, the remaining $F$ nodes may in fact be healthy, but their resources are not counted. This leads to over-provisioning of storage for encoded data. This paper introduces eAID, a novel elastic information dispersal algorithm that addresses this conundrum through a two-stage approach. First, the core protocol estimates the actual number $f$ of faulty nodes, rather than assuming the worst-case bound $F$. Dissemination completes quickly when messages are received from $(N-f)$ nodes, and more gradually when fewer nodes respond. Second, after initial dissemination completes, eAID continues monitoring for additional responses. As responses arrive from up to $N$ nodes, the system prunes the information stored at responding nodes accordingly. A key technique enabling this seamless elasticity is an agile encoding scheme that varies the number of disseminated fragments while keeping both fragment size and the recovery threshold $(F+1)$ fixed. Not only does this enable varying the number of disseminated fragments on the fly, it also allows nodes to discard encoded fragments autonomously. Crucially, this is achieved without maintaining complex metadata, without requiring nodes to reconstruct or re-encode information, and without global coordination for storage decisions. We demonstrate the practicality of eAID by integrating it with a replicated key-value store, and evaluating it in network environments with unpredictable latencies. The results show that eAID improves overall performance while significantly reducing long-term storage consumption.

cs.DC↗