AI 中文总结
该研究提出基于SchedExt(SCX)的无服务器平台驱动CPU负载均衡框架，通过自定义Linux调度器优化任务放置，8域配置可降能耗15%、减延迟最高50%，兼顾能效与性能。
AI 中文摘要
无服务器平台维护函数调用和资源利用率的全局视图，但现有系统大多将CPU调度决策限制在操作系统调度器范围内。本文提出一种无服务器平台驱动的CPU负载均衡框架，该框架通过基于SchedExt(SCX)构建的自定义Linux调度器，使控制平面能够直接影响CPU调度。所提出的调度器引入了可配置的调度域和共享接口，允许控制平面根据函数的历史到达间隔时间将函数分配到不同域中。在每个域内，采用单队列负载均衡策略结合虚拟时间优先级策略，优化任务放置的同时减少忙轮询任务的干扰。实验结果表明，8个域的配置实现了最佳权衡，可将系统能耗降低约15%，仅使调用成本增加5%；在高负载工作负载下，与默认Linux完全公平调度器(CFS)相比，所提出的调度器还能将请求延迟降低多达50%。这些结果表明，将CPU调度决策开放给无服务器控制平面，可在保持调度灵活性的同时，提升能效和工作负载性能。
英文摘要
Serverless platforms maintain a global view of function invocations and resource utilization, yet existing systems largely restrict CPU scheduling decisions to the operating system scheduler. This paper presents a serverless platform-driven CPU load balancing framework that enables the control plane to directly influence CPU scheduling through a custom Linux scheduler built on SchedExt(SCX). The proposed scheduler introduces configurable scheduling domains and a shared interface that allows the control plane to assign functions to domains based on their historical inter-arrival times. Within each domain, a single-queue load-balancing strategy combined with a virtual-time prioritization policy improves task placement while reducing interference from busy-polling tasks. Results show that an eight-domain configuration achieves the best trade-off, reducing system energy consumption by approximately 15% while increasing invocation cost by only 5%. Under heavily loaded workloads, the proposed scheduler also reduces request latency by up to 50% compared to the default Linux Completely Fair Scheduler (CFS). These results demonstrate that exposing CPU scheduling decisions to the serverless control plane can improve both energy efficiency and workload performance while preserving scheduling flexibility.
