delayed write buffering

This work addresses the vulnerability in trusted execution environment (TEE)-based smart contract networks where encrypted transaction data still leaks sender–receiver linkability through storage access patterns. To mitigate this, the authors propose two novel structures: a Delayed Write Buffer and a Bitwise-Trie of Bucketed Entries. Leveraging the asymmetric update semantics and delay tolerance inherent in token transfers, these mechanisms decouple transaction execution from the receiver’s storage access. Combined with constant-size queries, randomized settlement, and privacy-preserving push notifications, the approach constructs a receiver anonymity set while maintaining high performance. The resulting system effectively resists both storage access pattern leakage and flooding attacks, achieving real-time private token transfers with probabilistic anonymity guarantees.

In DDR5 DRAM, write operations significantly increase read latency and limit bank-level parallelism, primarily due to on-die ECC-induced write latency variability (1–24×), which conventional cache replacement policies fail to model. Method: This work introduces the first bank-aware cache replacement paradigm—BARD—comprising three policies: BARD-E, BARD-C, and hybrid BARD-H. Without requiring low-level DRAM timing knowledge, BARD dynamically schedules write requests to improve bank concurrency via LLC dirty-line bank-location–aware replacement, lightweight 8-byte/slice SRAM-based metadata tracking, and coordinated writeback and proactive cleaning. Contribution/Results: Evaluated across SPEC2017, LIGRA, STREAM, and Google workloads, BARD achieves 4.3% average speedup (up to 8.5%) with negligible hardware overhead.

This work investigates how synchronization mechanisms affect state freshness under coupled position and application updates in shared memory. To address read–write contention in the Forwarding Information Base (FIB), we propose the first stochastic hybrid system (SHS) model featuring coupled dual age metrics, enabling quantitative comparison of Read-Copy-Update (RCU) and reader–writer locks (RWL) in terms of update timeliness. Theoretical analysis and numerical evaluation reveal a fundamental trade-off: RWL significantly improves application-update freshness under high position-update rates, whereas RCU ensures more timely application delivery and lower packet loss due to stale addresses under low update rates. This study is the first to formally characterize the timeliness–synchronization–frequency trade-off, establishing a quantifiable foundation for designing network state synchronization mechanisms.

This work identifies and systematically constructs Write+Sync, a novel pure-software write-based covert channel exploiting timing discrepancies between OS memory-disk synchronization mechanisms and software write buffering—operating without hardware dependencies and evading existing defenses. It introduces the first high-speed write channel explicitly designed for software caches, proposing single- and multi-file page collaborative modulation strategies alongside multi-granularity channel encoding. A system-level implementation is realized on Linux and macOS. Experiments demonstrate an average throughput of 2.036 Kb/s (peak: 14.762 Kb/s) on Linux with 0% bit error rate (BER), and 10.211 Kb/s (peak: 253.022 Kb/s) on macOS with only 0.004% BER. The channel enables practical attacks, including website fingerprinting and performance degradation, thereby validating its real-world exploitability and threat impact.

To address concurrency control challenges under mixed long/short transaction workloads in manufacturing systems, this paper proposes a decentralized graph-based protocol that guarantees zero aborts for long update transactions, improves short-transaction throughput, and fully exploits multicore parallelism. Our key contributions are: (1) the first decentralized scheduling mechanism based on a full-precision multiversion serialization graph (MVSG), enabling lock-free concurrency and distributed graph maintenance; and (2) BoMB—the first OLTP benchmark tailored to Bill-of-Materials (BOM) scenarios—accurately modeling heterogeneous transaction conflict patterns. Experimental evaluation on BoMB demonstrates 100% commit rate for long transactions, short-transaction throughput of 1.7 Mtpm, and near-linear scalability—substantially outperforming state-of-the-art approaches.

This work addresses the problem of frontrunning and value extraction caused by Maximal Extractable Value (MEV) in distributed ledgers by proposing a defense mechanism based on Verifiable Delay Functions (VDFs). The approach introduces a mandatory time delay at the transaction generation stage, preventing block producers from instantaneously exploiting MEV opportunities without compromising system liveness. To the best of our knowledge, this is the first application of VDFs to MEV mitigation. The scheme is rigorously proven effective under both Byzantine and rational actor models, while its theoretical limitations are explicitly characterized. Empirical analysis demonstrates that the mechanism successfully blocks the majority of existing MEV attacks, offering a solution that is both theoretically sound and practically feasible.

This work addresses the vulnerability of encrypted mempools to economically lagging and security risks arising from self-authorized state manipulation—such as perpetual contract funding rate manipulation—due to their inability to inject corrective transactions into already committed batches, despite offering protection against victim-dependent MEV attacks. The paper proposes a micro-correction mechanism grounded in executable arbitrage, modeling how correctors optimally choose order sizes balancing price impact and inventory costs, while evaluating exploitable opportunities through the lens of protocol disclosure timing. It introduces a novel local security index incorporating attacker blind spots, correction shielding, and capitalization shielding, revealing how private transactions suppress predictive capitalization of funding rates and induce dual amplification effects. By integrating game theory, market mechanism design, and encrypted mempool architecture, the study establishes a dynamic security framework driven by information scheduling and response factors, proving that closed-phase correction rates fall below adaptive correction rates and quantifying both state distortion and its responsive amplification.

Shared state profoundly influences the performance and fault tolerance of stream processing, service-oriented, and continual learning systems, yet existing approaches often treat access control, hardware-aware execution, memory management, and long-term evolution in isolation. This work reframes state management as a runtime control problem and introduces a contract-driven blueprint centered on state objects, control planes, coupling paths, evaluation boundaries, and pending contracts. Building upon this foundation, we develop a unified analytical framework encompassing state-access scheduling, state-aware execution, and state evolution reuse. Through systematic scheduling, runtime control, and cross-layer coupling analysis, our approach identifies critical anti-patterns and advances a perturbation-aware evaluation paradigm, thereby establishing both theoretical foundations and practical design guidelines for state control in distributed systems.

This work addresses the performance limitations of the Sui blockchain, which stem from workload contention. Conventional read-write conflict graph approaches overestimate actual serialization dependencies. To remedy this, the authors propose a write-only (W-only) analysis model that introduces the W-only conflict graph as a lower bound on contention. By integrating write-set analysis, union-find-based object clustering, and empirical mainnet data, the study precisely characterizes genuine write serialization events. Findings reveal that excluding read-only dependencies eliminates the hub-and-spoke topology commonly assumed, indicating that parallelism potential has been overestimated by 30–40%. Moreover, 10–50% of transaction value flows through serial paths, exposing significant ordering risk. The results demonstrate that Sui’s contention topology is highly assortative and dominated by dense clusters, fundamentally revising prior understanding of its parallel execution capacity.