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新论文 · v1arXiv:2610.36636

Agar: What-If Analysis for Microservice Applications

Saarth Deshpande, Neeraja J. Yadwadkar, Venkat Arun

原文摘要

Microservice operators must reason about how applications would behave under changes that have not yet occurred: different workloads, resource allocations, or SLO targets. Evaluating every alternative experimentally is expensive, but predicting such counterfactuals is difficult because microservices contain many interacting components. End-to-end models must learn behavior over a combinatorial space of conditions, but composing per-component predictors causes prediction errors to accumulate. We address this challenge by changing what each component model must predict. Rather than predicting exact values, we learn simple, interpretable bounds that contain every observed behavior while remaining tight enough to support useful end-to-end conclusions. We build AGAR, a counterfactual performance analysis tool that composes these models to answer end-to-end SLO-feasibility questions. This allows us to formulate autoscaling as a counterfactual query: what is the smallest resource allocation under which an SLO is met? Our evaluation demonstrates that across three microservice applications, AGAR's bounds are actionable: its derived autoscaler reduces CPU allocation by up to 36.8% over state-of-the-art horizontal autoscalers while satisfying application SLOs. Further, AGAR is able to predict operational cost given workload traces, provide guidance on which service's startup time to optimize and localize performance bugs within each application.

cs.DC · cs.OS · cs.PF

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arXiv ↗PDF ↗
新论文 · v1arXiv:2610.36436

USB Differentiated Service for Networked Cyber-Physical Systems

Anton Njavro, Rafiuddin Syed, Shriram Raja, Zhiyuan Ruan, Richard West

原文摘要

Cyber-physical systems are increasingly complex, requiring high throughput, low-latency data processing across multiple cores and compute devices. Additional functional safety challenges dictate the need for high system availability in the presence of failures. Together, these requirements are addressed using a network of compute nodes across which data processing, control and functional safety tasks are distributed. A key challenge is how to address the service requirements of independent data flows, spanning a set of hosts and I/O devices. In this paper, we show how to develop connectivity between hosts using a custom xDCI gadget driver that uses USB interrupters to differentiate the processing of separate data flows. Our solution is the first to handle both isochronous and bulk communication at USB 3.0 transfer rates, with predictable bus latencies down to the granularity of a 125 microsecond microframe, which is sufficient for many CPS control operations. We present an end-to-end solution that couples the predictable execution of user-level tasks with interrupt processing and data communication, so that multiple virtual connections are able to share a common bus. This work is not only applicable to host networking but also device I/O, which makes it arguably desirable for CPS scenarios requiring short-range communication, such as in vehicle control area networks or robotics.

cs.OS

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arXiv ↗PDF ↗
新论文 · v1arXiv:2610.36347

Callosal: Rethinking the Kernel Page Cache for Disaggregated Storage and Memory

James McMahon, Amit Samanta, Seung-seob Lee, Ryan Stutsman, Anurag Khandelwal

原文摘要

Classic distributed filesystems like NFS centralize filesystem operations on a server and use custom, filesystem-specific approaches for managing cache consistency across client nodes. This limits scalability, and it leads to weak consistency, ruling out applications that concurrently access and mutate shared files. Our key insight is that these legacy designs are now too storage-centric; with today's large memories, OS page caches do most of the "heavy lifting" in accessing data, not the filesystem and block storage layers. In response to this, we present Callosal, a page cache for a cluster of machines that is centered on shared disaggregated memory. Rather than serializing operations through a filesystem server and using ad hoc caching like NFS, Callosal is built around the existing Linux page cache paths and is accelerated by RDMA and programmable switches. Callosal delivers the strong consistency that programs expect with local filesystems (like in ext4 and tmpfs) while avoiding the additional network access delays and bottlenecks that host-based solutions incur. We compare Callosal against NFS, CephFS, and local filesystems; often Callosal can provide caching performance similar to local filesystems while also scaling across nodes. For mixed read/write workloads, on average Callosal has 4.6x higher throughput than NFS when contention is not extreme, and it offers strong consistency guarantees like CephFS, while outperforming it. For a file-backed key-value store with 1% writes and uniform access, Callosal scales 1.7x across 4 nodes, while CephFS collapses across nodes.

cs.OS

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arXiv ↗PDF ↗
新论文 · v1arXiv:2610.35999

safeL4: Rethinking Safe-Language-Based Single Address Space Microkernels

Zheyuan Xu, Xiaobei Zhang, Zihan Li, Zekai Nie, Guangtao Zhu, Zhuang Lu, Qianying Zhang, Shijun Zhao 等 10 位作者

原文摘要

Microkernels provide good features such as high security, safety, and flexibility, but their reliance on hardware-based isolation leads to heavy performance overhead, limiting their widespread adoption. Although constructing single-address-space microkernels based on safe language-based isolation is a promising approach to addressing the performance issue, this approach still faces challenges in maintaining the principle of minimality and enforcing capability-based, fine-grained access control over system resources. We propose safeL4, an approach to constructing microkernels based on safe languages. It guarantees minimality through low-level abstractions for unsafe operations, and implements a capability system based on the safe language's object capabilities to achieve fine-grained access control over all operations on system resources. We implement a prototype system in Rust, and our evaluation results show that the primitives provided by safeL4 are, on average, 1.9$\times$ faster than those of seL4.

cs.OS · cs.CR · cs.PL

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arXiv ↗PDF ↗
版本更新 · v3arXiv:2510.08479

No Provenance Left Behind: Revisiting Reference Monitor Guarantees with Learned Kernel Scheduling

Jinsong Mao, Benjamin E. Ujcich, Shiqing Ma

原文摘要

Provenance plays a critical role in maintaining traceability of a system's actions for root cause analysis of security threats and impacts. Provenance collection is often incorporated into the reference monitor of systems to ensure that an audit trail exists of all events, that events are completely captured, and that logging of such events cannot be bypassed. However, recent research has questioned whether existing state-of-the-art provenance collection systems fail to ensure the security guarantees of a true reference monitor due to the 'super producer threat' in which provenance generation can overload a system to force the system to drop security-relevant events and allow an attacker to hide their actions. One approach towards solving this threat is to enforce resource isolation, but that does not fully solve the problems resulting from hardware dependencies and performance limitations. In this paper, we show how an operating system's kernel scheduler can mitigate this threat, and we introduce Aegis, a learned scheduler for Linux specifically designed for provenance. Unlike conventional schedulers that ignore provenance completeness requirements, Aegis leverages reinforcement learning to learn provenance task behavior and to dynamically optimize resource allocation. We evaluate Aegis's efficacy and show that Aegis significantly improves both the completeness and efficiency of provenance collection systems compared to traditional scheduling, while maintaining reasonable overheads and even improving overall runtime in certain cases compared to the default Linux scheduler.

cs.CR · cs.OS

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arXiv ↗PDF ↗