点击次数：
影响因子：9.2
DOI码：10.1109/TCC.2026.3714912
所属单位：中国矿业大学
教研室：计算机系
发表刊物：IEEE Transactions on Cloud Computing
刊物所在地：美国
关键字：Serverless computing, resource configuration,reinforcement learning, performance optimization, cloud computing
摘要：Serverless resource control must react to workload pressure without ignoring what the function actually computes. Existing profiling and telemetry-driven optimizers mainly observe runtime symptoms, which makes them slow to transfer across functions whose CPU, memory, and I/O behavior differ. CALO is a code-aware and load-aware controller that caches offline code embeddings, combines them with live telemetry in a 79-dimensional state, and selects memory, architecture, and timeout from a 48-action provider catalog. CALO is trained with a measurement-grounded batch-window simulator built from OpenWhisk warm, cold-start, burst, and idle-gap profiles, which supports simulator-based policy comparison while keeping the execution model tied to measured behavior. Across three seeds, five benchmarks, and four workload families under dual x64/ARM64 calibration, CALO improves mean raw reward from 0.513 to 0.569 over online Bayesian optimization and raises the 10% Conditional Value at Risk (CVaR10) from 0.163 to 0.351. A matched Load-Only CALO ablation indicates a modest, workload-dependent code contribution: the largest mean gains occur on thumbnailer and image-recognition, while effects are mixed or small when runtime telemetry already explains the workload well. OpenWhisk validation covers 120 x64 fixedconfiguration targets, yields 112 deployable configurations with 13.9% median warm-path error, and gives positive transfer evidence across eight focused adaptive-stress replay cases. Together, the simulator and OpenWhisk evidence indicate that code semantics can provide a complementary control signal within the tested settings, while online action selection remains lightweight at 0.124 ms median and 0.132 ms p95 on the local CPU used in this study. Code is available at https://github.com/MuQY1818/calo-experiments
第一作者：徐东红
合写作者：卜炜珏,叶周亮,武世龙
论文类型：期刊论文
学科门类：工学
一级学科：计算机科学与技术
文献类型：J
页面范围：1 - 14
字数：12000
ISSN号：2168-7161
是否译文：否
发表时间：2026-07-20
收录刊物：SCI