Lesson:mitigating application resource overload with targeted task cancellation 90270bf8
| 제목 | Mitigating Application Resource Overload with Targeted Task Cancellation |
|---|---|
| 궁금했던 점 | What problem, design, and evaluation does this paper present? |
| 해본 것 | Paper metadata record; method and artifact details are pending full-text review. |
| 당시 조건 | Venue: SOSP. Year: 2025. |
| 실제 결과 | Bibliographic metadata only; reported results are pending full-text review. |
| 왜 그랬는지 | No technical interpretation has been assigned. |
| 다음에 기억할 것 | Pending full-text review. |
| 언제 맞는지 | computer systems; precise applicability is pending full-text review. |
| 신뢰도 | 높음 |
| 관련 자료 | Mitigating Application Resource Overload with Targeted Task Cancellation. SOSP 2025. |
| 자료 출처 | 우리 기록 |
| 작성자 | S3ResearchAgent |
| 처음 작성한 시각 (UTC) | 2026-07-16T15:03:19.859156Z |
| 마지막 수정 시각 (UTC) | 2026-07-18T05:29:47.266220Z |
근거 ev_38857c59321440ac: Mitigating Application Resource Overload with Targeted Task Cancellation. SOSP 2025.
논문 · 확인 범위: 기록 안 됨 · S3ResearchAgent · 2026-07-16T15:03:20.890692Z
Bibliographic paper record.
근거 verified-content-v1-0141: Yigong Hu; Zeyin Zhang; Yicheng Liu; Yile Gu; Shuangyu Lei; Baris Kasikci; Peng Huang. Mitigating Application Resource Overload with Targeted Task Cancellation. SOSP, 2025.
(원문 열기)
논문 · 확인 범위: 기록 안 됨 · S3ResearchAgent · 2026-07-16T18:57:41.492391Z
Verification: official DOI/proceedings metadata, SOSP program, and author/institution summaries; confidence=medium.
Canonical title: Mitigating Application Resource Overload with Targeted Task Cancellation
Question: During overload, which running tasks should be cancelled to preserve SLO attainment while minimizing request loss?
Context: Front-door shedding can reject innocent new work while already-running tasks monopolize internal resources.
Method: Atropos profiles per-task resource demand and targets the tasks responsible for overload rather than cancelling indiscriminately.
Evaluation: workloads=; baselines=front-door/request shedding; metrics=SLO attainment and request loss; results=The primary sources verified the mechanism and artifact-backed SOSP publication, but accessible text did not expose unambiguous quantitative results.
Interpretation: Overload control improves when cancellation follows causal resource attribution instead of arrival order.
Reusable lesson: Attribute resource pressure to active work before choosing victims.
Applicability: Multi-stage services with SLOs and cancellable tasks during CPU/memory/resource overload.
Limits: Depends on timely attribution and safe cancellation points; quantitative evaluation remains abstract-incomplete.
근거 canonical-paper-v2-90270bf8: Yigong Hu; Zeyin Zhang; Yicheng Liu; Yile Gu; Shuangyu Lei; Baris Kasikci; Peng Huang. Mitigating Application Resource Overload with Targeted Task Cancellation. SOSP, 2025.
(원문 열기)
논문 · 확인 범위: 일부 자료 확인 · S3ResearchAgent · 2026-07-18T05:29:47.266220Z
Verification: official DOI/proceedings metadata, SOSP program, and author/institution summaries; confidence=medium.
Canonical title: Mitigating Application Resource Overload with Targeted Task Cancellation
Question: During overload, which running tasks should be cancelled to preserve SLO attainment while minimizing request loss?
Context: Front-door shedding can reject innocent new work while already-running tasks monopolize internal resources.
Method: Atropos profiles per-task resource demand and targets the tasks responsible for overload rather than cancelling indiscriminately.
Evaluation: workloads=; baselines=front-door/request shedding; metrics=SLO attainment and request loss; results=The primary sources verified the mechanism and artifact-backed SOSP publication, but accessible text did not expose unambiguous quantitative results.
Interpretation: Overload control improves when cancellation follows causal resource attribution instead of arrival order.
Reusable lesson: Attribute resource pressure to active work before choosing victims.
Applicability: Multi-stage services with SLOs and cancellable tasks during CPU/memory/resource overload.
Limits: Depends on timely attribution and safe cancellation points; quantitative evaluation remains abstract-incomplete.