Function-as-a-Service (FaaS) platforms provide scalable and cost-efficient execution but suffer from increased latency and resource overheads in complex applications comprising multiple functions, particularly due to double billing when functions call each other. This paper presents Provuse, a transparent, platform-side optimization that automatically performs function fusion at runtime for independently deployed functions, thereby eliminating redundant function instances. This approach reduces both cost and latency without requiring users to change any code. Provusetargets provider-managed FaaS platforms that retain control over function entry points and deployment artifacts, enabling transparent, runtime execution consolidation without developer intervention. We provide two implementations for this approach using the tinyFaaS platform as well as Kubernetes, demonstrating compatibility with container orchestration frameworks. An evaluation shows consistent improvements, achieving an average end-to-end latency reduction of 26.33% and a mean RAM usage reduction of 53.57%. These results indicate that automatic function fusion is an effective platform-side strategy for reducing latency and RAM consumption in composed FaaS applications, highlighting the potential of transparent infrastructure-level optimizations in serverless systems.

翻译：函数即服务（FaaS）平台提供了可扩展且经济高效的执行环境，但在由多个函数构成的复杂应用中，其延迟和资源开销显著增加，尤其是在函数相互调用时因重复计费问题而加剧。本文提出Provuse，一种透明的平台侧优化技术，可在运行时对独立部署的函数自动执行函数融合，从而消除冗余的函数实例。该方法无需用户修改任何代码即可同时降低成本和延迟。Provuse面向由提供商管理、保留函数入口点和部署工件控制权的FaaS平台，能够在无需开发者干预的情况下实现透明的运行时执行整合。我们基于tinyFaaS平台和Kubernetes提供了该方法的两种实现，证明了其与容器编排框架的兼容性。评估结果显示该方法能持续带来改进，平均端到端延迟降低26.33%，平均内存使用量减少53.57%。这些结果表明，自动函数融合是降低组合式FaaS应用延迟与内存消耗的有效平台侧策略，凸显了无服务器系统中透明基础设施级优化的潜力。