arXiv subjects

Mohammad Sadoghi

Publications and source records attributed to Mohammad Sadoghi.

At least 19 recordsLinked to original sources

arXiv2026

Hermes: Low Tail-Latency Via Prefix Consensus

Leader-based BFT protocols finalize through their leaders: a view whose leader is crashed or slow finalizes nothing, and the timeout that ends it admits no good setting. A conservative timeout turns every crashed leader into a long stall; an aggressive one voids the views of leaders that are merely slow. Either way the expired view is wasted, and this trade-off, not the good case, governs tail latency. Hermes makes expired views finalize. Hermes is a two-round rotating-leader protocol for $n=5f+1$ processes under partial synchrony built on prefix consensus: votes carry values ordered by a prefix relation, and quorums require comparability rather than equality. Every process broadcasts a justified proposal at view start and casts a single vote, for the leader's proposal upon delivery or for a fallback proposal at the timeout; there are no nullify votes. A timely honest leader finalizes its full proposal in $2\delta$. Otherwise, any $n-f$ votes, which need not match, finalize the heaviest common prefix. We instantiate Hermes as a finality gadget over an available chain and over Autobahn-style multi-lane dissemination, where parent-relative delta tipcuts with explicit skips keep independent proposals comparable and sender-indexed erasure-coded amplification keeps complexity at $O(n^2\hat{m}+\lambda n^3)$ bits and $O(n^2)$ messages per view, where $\hat{m}$ is the number of concurrent dissemination lanes in Autobahn and $\lambda$ the security parameter.

cs.DC↗

arXiv2026

Cassandra: Consensus with Partial Progress via Robust Partitionable View Synchronization

Replicated databases and permissioned blockchain systems rely on Byzantine Fault-Tolerant (BFT) consensus to maintain a globally consistent order of transactions across distributed replicas. These protocols preserve safety even under asynchrony, as they commit a transaction only after agreement among a strong quorum of replicas. During network partitions, however, when no strong quorum is reachable, they lose liveness and cannot make useful progress. In this paper, we present Cassandra, a consensus protocol that enables partial progress without sacrificing safety. Cassandra achieves this through a two-tier certification framework that decouples availability from commitment, allowing each partition to extend its own chain and reconcile these chains once the network is restored. To support this, Cassandra introduces a pacemaker that advances views without requiring a strong quorum and calibrates each replica's timeout off the critical path. Our evaluation results show that Cassandra remains competitive with state-of-the-art BFT protocols under stable conditions, sustaining 900K TPS at 16 replicas and 480K TPS at 104 replicas, with latency ranging from 0.31s at 16 replicas to 0.75s at 104 replicas. Under severe partitions, Cassandra maintains non-zero speculative throughput through PoA-backed progress, preserving work that can be reconciled once connectivity is restored.

cs.DC↗

arXiv2026

SafarDB: FPGA-Accelerated Distributed Transactions via Replicated Data Types

Data replication is critical to data center design, ensuring high availability, scalability, and fault tolerance. However, replicas must be coordinated to maintain convergence and database integrity constraints under transactional workloads. Commutative Replicated Data Types (RDTs) provide convergence for conflict-free objects using relaxed consistency, and Well-coordinated Replicated Data Types (WRDTs) provide convergence and integrity for general objects using a hybrid model, relaxed when possible and strong when necessary. While state-of-the-art RDT hardware acceleration uses Remote Direct Memory Access (RDMA), recent data center architectures increasingly leverage FPGAs as application accelerators to achieve lower latency and higher throughput. In contrast to deploying an FPGA-based SmartNIC, this paper connects an FPGA accelerator card directly to the network, allowing a complete redesign of the NIC to match the needs of the FPGA-hosted application. We co-design a network-attached FPGA replication engine with an FPGA-resident network interface, enabling near-network execution of replicated transactions and direct invocation of FPGA-resident operators. We introduce SafarDB, an FPGA-accelerated system for Conflict-Free Replicated Data Types (CRDTs) and WRDTs. SafarDB accelerates relaxed and strongly ordered replication paths; when strong ordering is required, SafarDB accelerates the underlying consensus control path. In FPGA-only CRDT and WRDT experiments where the complete application state fits in FPGA-resident memory, SafarDB provides lower average response time and higher average throughput than a state-of-the-art RDMA-based implementation. Further, experiments demonstrate that SafarDB is more resilient to crash failures than existing CPU/RDMA-based CRDT and WRDT implementations, and SafarDB can detect leader failures and elect new leaders much faster than previously possible.

cs.DC↗

arXiv2025

HYDRA: Breaking the Global Ordering Barrier in Multi-BFT Consensus

Multi-Byzantine Fault Tolerant (Multi-BFT) consensus, which runs multiple BFT instances in parallel, has recently emerged as a promising approach to overcome the leader bottleneck in classical BFT protocols. However, existing designs rely on a global ordering layer to serialize blocks across instances, an intuitive yet costly mechanism that constrains scalability, amplifies failure propagation, and complicates deployment. In this paper, we challenge this conventional wisdom. We present HYDRA, the first Multi-BFT consensus framework that eliminates global ordering altogether. HYDRA introduces an object-centric execution model that partitions transactions by their accessed objects, enabling concurrent yet deterministic execution across instances. To ensure consistency, HYDRA combines lightweight lock-based coordination with a deadlock resolution mechanism, achieving both scalability and correctness. We implement HYDRA and evaluate it on up to 128 replicas in both LAN and WAN environments. Experimental results show HYDRA outperforms several state-of-the-art Multi-BFT protocols in the presence of a straggler. These results demonstrate strong consistency and high performance by removing global ordering, opening a new direction toward scalable Multi-BFT consensus design.

cs.DC↗

arXiv2025

Carry the Tail in Consensus Protocols

We present Carry-the-Tail, the first deterministic atomic broadcast protocol in partial synchrony that, after GST, guarantees a constant fraction of commits by non-faulty leaders against tail-forking attacks, and maintains optimal, worst-case quadratic communication under a cascade of faulty leaders. The solution also guarantees linear amortized communication, i.e., the steady-state is linear. Prior atomic broadcast solutions achieve quadratic word communication complexity in the worst case. However, they face a significant degradation in throughput under tail-forking attack. Existing solutions to tail-forking attacks require either quadratic communication steps or computationally-prohibitive SNARK generation. The key technical contribution is Carry, a practical drop-in mechanism for streamlined protocols in the HotStuff family. Carry guarantees good performance against tail-forking and removes most leader-induced stalls, while retaining linear traffic and protocol simplicity.

cs.DB↗

arXiv2025

Meaningful Data Erasure in the Presence of Dependencies

Data regulations like GDPR require systems to support data erasure but leave the definition of "erasure" open to interpretation. This ambiguity makes compliance challenging, especially in databases where data dependencies can lead to erased data being inferred from remaining data. We formally define a precise notion of data erasure that ensures any inference about deleted data, through dependencies, remains bounded to what could have been inferred before its insertion. We design erasure mechanisms that enforce this guarantee at minimal cost. Additionally, we explore strategies to balance cost and throughput, batch multiple erasures, and proactively compute data retention times when possible. We demonstrate the practicality and scalability of our algorithms using both real and synthetic datasets.

cs.DB↗

arXiv2025

FairDAG: Consensus Fairness over Multi-Proposer Causal Design

The rise of cryptocurrencies like Bitcoin and Ethereum has driven interest in blockchain database technology, with smart contracts enabling the growth of decentralized finance (DeFi). However, research has shown that adversaries exploit transaction ordering to extract profits through attacks like front-running, sandwich attacks, and liquidation manipulation. This issue affects blockchains where block proposers have full control over transaction ordering. To address this, a more fair transaction ordering mechanism is essential. Existing fairness protocols, such as Pompe and Themis, operate on leader-based consensus protocols, which not only suffer from low throughput caused by the single-leader bottleneck, but also allow adversarial block proposers to manipulate transaction ordering. To address these limitations, we propose a new framework, FairDAG, that runs fairness protocols on top of DAG-based consensus protocols. FairDAG improves protocol performance in both throughput and fairness quality by leveraging the multi-proposer design and validity property of DAG-based consensus protocols. We conducted a comprehensive analytical and experimental evaluation of two FairDAG variants - FairDAG-AB and FairDAG-RL. Our results demonstrate that FairDAG outperforms prior fairness protocols in both throughput and fairness quality.

cs.DB↗

arXiv2025

Fides: Secure and Scalable Asynchronous DAG Consensus via Trusted Components

DAG-based BFT consensus has attracted growing interest in distributed data management systems for consistent replication in untrusted settings due to its high throughput and resilience to asynchrony. However, existing protocols still suffer from high communication overhead and long commit latency. In parallel, introducing minimal hardware trust has proven effective in reducing the complexity of BFT consensus. Inspired by these works, we present Fides, an asynchronous DAG-based BFT consensus protocol that, to our knowledge, is among the first to leverage TEEs to enhance both scalability and efficiency. Fides tolerates a minority of Byzantine replicas and achieves $O(\kappa n^2 + n^3)$ metadata communication complexity through a customized TEE-assisted Reliable Broadcast (T-RBC) primitive with linear communication complexity in one-step broadcast. Building on T-RBC, Fides redefines the DAG construction rules by reducing the reference requirement from $2f+1$ to $f+1$ between consecutive vertices. This new structure weakens DAG connectivity and invalidates traditional commit rules, so we formally abstract the problem and derive new theoretical bounds of liveness. We further propose a four-round commit rule that achieves the theoretically minimal commit latency. Besides, we design two additional primitives, T-RoundCert and T-Coin, to efficiently certify DAG references and replace the costly cryptographic common coin used in prior protocols. Comprehensive evaluations on geo-distributed and local testbeds show that Fides substantially outperforms state-of-the-art protocols, including Tusk, Bullshark, Mysticeti, RCC, Damysus, Achilles and HybridSet, achieving lower latency and higher throughput while preserving strong safety and liveness guarantees.

cs.DC↗

arXiv2024

Did we miss P In CAP? Partial Progress Conjecture under Asynchrony

Each application developer desires to provide its users with consistent results and an always-available system despite failures. Boldly, the CALM theorem disagrees. It states that it is hard to design a system that is both consistent and available under network partitions; select at most two out of these three properties. One possible solution is to design coordination-free monotonic applications. However, a majority of real-world applications require coordination. We resolve this dilemma by conjecturing that partial progress is possible under network partitions. This partial progress ensures the system appears responsive to a subset of clients and achieves non-zero throughput during failures. To this extent, we present the design of our CASSANDRA consensus protocol that allows partitioned replicas to order client requests.

cs.DC↗

arXiv2024

Orthrus: Accelerating Multi-BFT Consensus through Concurrent Partial Ordering of Transactions (Extended Version)

Multi-Byzantine Fault Tolerant (Multi-BFT) consensus allows multiple consensus instances to run in parallel, resolving the leader bottleneck problem inherent in classic BFT consensus. However, the global ordering of Multi-BFT consensus enforces a strict serialized sequence of transactions, imposing additional confirmation latency and also limiting concurrency. In this paper, we introduce Orthrus, a Multi-BFT protocol that accelerates transaction confirmation through partial ordering while reserving global ordering for transactions requiring stricter sequencing. To this end, Orthrus strategically partitions transactions to maximize concurrency and ensure consistency. Additionally, it incorporates an escrow mechanism to manage interactions between partially and globally ordered transactions. We evaluated Orthrus through extensive experiments in realistic settings, deploying 128 replicas in WAN and LAN environments. Our findings demonstrate latency reductions of up to 87% in WAN compared to existing Multi-BFT protocols.

cs.DC↗

arXiv2024

Hamava: Fault-tolerant Reconfigurable Geo-Replication on Heterogeneous Clusters

Fault-tolerant replicated database systems consume less energy than the compute-intensive proof-of-work blockchain. Thus, they are promising technologies for the building blocks that assemble global financial infrastructure. To facilitate global scaling, clustered replication protocols are essential in orchestrating nodes into clusters based on proximity. However, the existing approaches often assume a homogeneous and fixed model in which the number of nodes across clusters is the same and fixed, and often limited to a fail-stop fault model. This paper presents heterogeneous and reconfigurable clustered replication for the general environment with arbitrary failures. In particular, we present AVA, a fault-tolerant reconfigurable geo-replication that allows dynamic membership: replicas are allowed to join and leave clusters. We formally state and prove the safety and liveness properties of the protocol. Furthermore, our replication protocol is consensus-agnostic, meaning each cluster can utilize any local replication mechanism. In our comprehensive evaluation, we instantiate our replication with both HotStuff and BFT-SMaRt. Experiments on geo-distributed deployments on Google Cloud demonstrates that members of clusters can be reconfigured without considerably affecting transaction processing, and that heterogeneity of clusters may significantly improve throughput.

cs.DC↗

arXiv2024

HotStuff-1: Linear Consensus with One-Phase Speculation

This paper introduces HotStuff-1, a BFT consensus protocol that improves the latency of HotStuff-2 by two network hops while maintaining linear communication complexity against faults. Furthermore, HotStuff-1 incorporates an incentive-compatible leader rotation design that motivates leaders to propose transactions promptly. HotStuff-1 achieves a reduction of two network hops by speculatively sending clients early confirmations, after one phase of the protocol. Introducing speculation into streamlined protocols is challenging because, unlike stable-leader protocols, these protocols cannot stop the consensus and recover from failures. Thus, we identify prefix speculation dilemma in the context of streamlined protocols; HotStuff-1 is the first streamlined protocol to resolve it. HotStuff-1 embodies an additional mechanism, slotting, that thwarts delays caused by (1) rationally-incentivized leaders and (2) malicious leaders inclined to sabotage other's progress. The slotting mechanism allows leaders to dynamically drive as many decisions as allowed by network transmission delays before view timers expire, thus mitigating both threats.

cs.DB↗

arXiv2024

Thunderbolt: Concurrent Smart Contract Execution with Non-blocking Reconfiguration for Sharded DAGs

Sharding has emerged as a critical technique for enhancing blockchain system scalability. However, existing sharding approaches face unique challenges when applied to Directed Acyclic Graph (DAG)-based protocols that integrate expressive smart contract processing. Current solutions predominantly rely on coordination mechanisms like 2PC and require transaction read/write sets to optimize parallel execution. These requirements introduce two fundamental limitations: 1) additional coordination phases incur latency overhead, and 2) pre-declaration of read/write sets proves impractical for Turing-complete smart contracts with dynamic access patterns. This paper presents Thunderbolt, a novel sharding architecture for both single-shard transactions (Single-shard TXs) and cross-shard transactions (Cross-shard TXs) and enables nonblocking reconfiguration to ensure system liveness. Our design introduces 4 key innovations: 1) each replica serves dual roles as a full-shard representative and transaction proposer, employing the Execution-Order-Validation (EOV) model for Single-shard TXs and Order-Execution (OE) model for Cross-shard TXs. 2) we develop a DAG-based coordination protocol that establishes deterministic ordering between two transaction types while preserving concurrent execution capabilities. 3) we implement a dynamic concurrency controller that schedules Single-shard TXs without requiring prior knowledge of read/write sets, enabling runtime dependency resolution. 4) Thunderbolt introduces a nonblocking shard reconfiguration mechanism to address censorship attacks by featuring frequent shard re-assignment without impeding the construction of DAG nor blocking consensus. Thunderbolt achieves a 50x throughput improvement with 64 replicas compared to serial execution in the Tusk framework.

cs.DB↗

arXiv2023

Data-CASE: Grounding Data Regulations for Compliant Data Processing Systems

Data regulations, such as GDPR, are increasingly being adopted globally to protect against unsafe data management practices. Such regulations are, often ambiguous (with multiple valid interpretations) when it comes to defining the expected dynamic behavior of data processing systems. This paper argues that it is possible to represent regulations such as GDPR formally as invariants using a (small set of) data processing concepts that capture system behavior. When such concepts are grounded, i.e., they are provided with a single unambiguous interpretation, systems can achieve compliance by demonstrating that the system-actions they implement maintain the invariants (representing the regulations). To illustrate our vision, we propose Data-CASE, a simple yet powerful model that (a) captures key data processing concepts (b) a set of invariants that describe regulations in terms of these concepts. We further illustrate the concept of grounding using "deletion" as an example and highlight several ways in which end-users, companies, and software designers/engineers can use Data-CASE.

cs.DB↗

arXiv2023

Diba: A Re-configurable Stream Processor

Stream processing acceleration is driven by the continuously increasing volume and velocity of data generated on the Web and the limitations of storage, computation, and power consumption. Hardware solutions provide better performance and power consumption, but they are hindered by the high research and development costs and the long time to market. In this work, we propose our re-configurable stream processor (Diba), a complete rethinking of a previously proposed customized and flexible query processor that targets real-time stream processing. Diba uses a unidirectional dataflow not dedicated to any specific type of query (operator) on streams, allowing a straightforward placement of processing components on a general data path that facilitates query mapping. In Diba, the concepts of the distribution network and processing components are implemented as two separate entities connected using generic interfaces. This approach allows the adoption of a versatile architecture for a family of queries rather than forcing a rigid chain of processing components to implement such queries. Our experimental evaluations of representative queries from TPC-H yielded processing times of 300, 1220, and 3520 milliseconds for data streams with scale factor sizes of one, four, and ten gigabytes, respectively.

cs.DB↗

arXiv2023

Comparative Evaluation of Data Decoupling Techniques for Federated Machine Learning with Database as a Service

Federated Learning (FL) is a machine learning approach that allows multiple clients to collaboratively learn a shared model without sharing raw data. However, current FL systems provide an all-in-one solution, which can hinder the wide adoption of FL in certain domains such as scientific applications. To overcome this limitation, this paper proposes a decoupling approach that enables clients to customize FL applications with specific data subsystems. To evaluate this approach, the authors develop a framework called Data-Decoupling Federated Learning (DDFL) and compare it with state-of-the-art FL systems that tightly couple data management and computation. Extensive experiments on various datasets and data management subsystems show that DDFL achieves comparable or better performance in terms of training time, inference accuracy, and database query time. Moreover, DDFL provides clients with more options to tune their FL applications regarding data-related metrics. The authors also provide a detailed qualitative analysis of DDFL when integrated with mainstream database systems.

cs.DB↗

arXiv2023

Securing Consensus from Long-Range Attacks through Collaboration

Decentralized systems built around blockchain technology promise clients an immutable ledger. They add a transaction to the ledger after it undergoes consensus among the replicas that run a Proof-of-Stake (PoS) or Byzantine Fault-Tolerant (BFT) consensus protocol. Unfortunately, these protocols face a long-range attack where an adversary having access to the private keys of the replicas can rewrite the ledger. One solution is forcing each committed block from these protocols to undergo another consensus, Proof-of-Work(PoW) consensus; PoW protocol leads to wastage of computational resources as miners compete to solve complex puzzles. In this paper, we present the design of our Power-of-Collaboration (PoC) protocol, which guards existing PoS/BFT blockchains against long-range attacks and requires miners to collaborate rather than compete. PoC guarantees fairness and accountability and only marginally degrades the throughput of the underlying system.

cs.CR↗

arXiv2023

SpotLess: Concurrent Rotational Consensus Made Practical through Rapid View Synchronization

The emergence of blockchain technology has renewed the interest in consensus-based data management systems that are resilient to failures. To maximize the throughput of these systems, we have recently seen several prototype consensus solutions that optimize for throughput at the expense of overall implementation complexity, high costs, and reliability. Due to this, it remains unclear how these prototypes will perform in real-world environments. In this paper, we present SPOTLESS, a novel concurrent rotational consensus protocol made practical. Central to SPOTLESS is the combination of (1) a chained rotational consensus design for replicating requests with a reduced message cost and low-cost failure recovery that eliminates the traditional complex, error-prone view-change protocol; (2) the novel Rapid View Synchronization protocol that enables SPOTLESS to work in more general network assumptions, without a need for a Global Synchronization Time to synchronize view, and recover valid earlier views with the aid of non-faulty replicas without the need to rely on the primary; (3) a high-performance concurrent consensus architecture in which independent instances of the chained consensus operate concurrently to process requests with high throughput, thereby avoiding the bottlenecks seen in other rotational protocols. Due to the concurrent consensus architecture, SPOTLESS greatly outperforms traditional primary-backup consensus protocols such as PBFT (by up to 430%), NARWHAL-HS (by up to 137%), and HOTSTUFF (by up to 3803%). Due to its reduced message cost, SPOTLESS is even able to outperform RCC, a state-of-the-art high-throughput concurrent consensus protocol, by up to 23%. Furthermore, SPOTLESS is able to maintain a stable and low latency and consistently high throughput even during failures.

cs.DB↗