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Data-Centric Serverless Computing with LAMBDASTORE

Publié
Serveur de preprints
Preprints.org
DOI
10.20944/preprints202512.0965.v1

LAMBDASTORE is a new serverless platform with an integrated storage engine tailored for stateful serverless workloads. Its compute-storage co-design colocates serverless functions with their associated data, yielding significant performance gains. It also leverages the transaction interface of its storage engine to provide serializable workflows and exactly-once semantics. This paper presents the design of LAMBDASTORE and introduces three key contributions. First, it adopts an object-oriented model in which functions are bundled with their associated data, enabling function execution to be scheduled directly at the data’s location. Second, the storage layer provides efficient transaction processing by dynamically adjusting lock granularity and employing a customized optimistic concurrency control protocol. Third, to enable colocation without sacrificing elasticity, the system supports data migration and lightweight replication at the granularity of individual objects. Experiments show that LAMBDASTOREoutperformsconventional serverless platforms, especially in read-heavy workloads. In such settings, LAMBDASTORE achieves throughput orders of magnitude higher than existing systems, while maintaining average end-to-end latencies below 20 ms.

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