Burak Ocalan | Searcharxiv

arXiv2026

HEAL: Online Incremental Recovery for Leaderless Distributed Systems Across Persistency Models

Ensuring resilience in distributed systems has become an acute concern. In today's environment, it is crucial to develop light-weight mechanisms that recover a distributed system from faults quickly and with only a small impact on the live-system throughput. To address this need, this paper proposes a new low-overhead, general recovery scheme for modern non-transactional leaderless distributed systems. We call our scheme HEAL. On a node failure, HEAL performs an optimized online incremental recovery. This paper presents HEAL's algorithms for settings with Linearizable consistency and different memory persistency models. We implement HEAL on a 6-node Intel cluster. Our experiments running TAOBench workloads show that HEAL is very effective. HEAL recovers the cluster in 120 milliseconds on average, while reducing the throughput of the running workload by an average of 8.7%. In contrast, a conventional recovery scheme for leaderless systems needs 360 seconds to recover, reducing the throughput of the system by 16.2%. Finally, compared to an incremental recovery scheme for a state-of-the-art leader-based system, HEAL reduces the average recovery latency by 20.7x and the throughput degradation by 62.4%.

cs.DC↗

arXiv2026

Towards CXL Resilience to CPU Failures

Compute Express Link (CXL) 3.0 and beyond allows the compute nodes of a cluster to share data with hardware cache coherence and at the granularity of a cache line. This enables shared-memory semantics for distributed computing, but introduces new resilience challenges: a node failure leads to the loss of the dirty data in its caches, corrupting application state. Unfortunately, the CXL specification does not consider processor failures. Moreover, when a component fails, the specification tries to isolate it and continue application execution; there is no attempt to bring the application to a consistent state. To address these limitations, this paper extends the CXL specification to be resilient to node failures, and to correctly recover the application after node failures. We call the system ReCXL. To handle the failure of nodes, ReCXL augments the coherence transaction of a write with messages that propagate the update to a small set of other nodes (i.e., Replicas). Replicas save the update in a hardware Logging Unit. Such replication ensures resilience to node failures. Then, at regular intervals, the Logging Units dump the updates to memory. Recovery involves using the logs in the Logging Units to bring the directory and memory to a correct state. Our evaluation shows that ReCXL enables fault-tolerant execution with only a 30% slowdown over the same platform with no fault-tolerance support.

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