跳到正文
研踪PaperTrail

YOUR RESEARCH, IN SIGHT

让下一篇重要论文,不再错过。

覆盖计算机全学科,以 AI 为快捷入口。关注方向、作者和关键词,把发现变成持续的研究积累。

部分采集异常
正在读取账号与研究记录…

全站更新概况

+1163新增论文
+868其中 AI 相关
+88已有论文修订
+100新增 AI 导读

arXiv 最近完成扫描:2026-11-06 07:02 · 全站最近入库:2026-11-05 12:13各信源进度 →

统计口径与数据新鲜度

统计 2026-11-05 09:57 — 2026-11-06 09:57(北京时间) · 点击数字查看对应简报;AI 相关包含在新增论文内。

最近完成检查:2026-11-06 07:02最近发现新增版本:2026-11-05 12:13库内论文最新更新时间:2026-11-05 02:59

每分钟刷新已保存的数据。空检查不代表采集异常;新收录可能包含历史论文。AI 导读按新增版本计数。

15,949 已收录论文13,765 AI 相关3,571 有修订112 HF 社区发现

浏览论文库

时间范围跟随排序:版本更新、本站收录或首次发表。最新收录可能包含历史论文。部分信源异常,查看状态 →

找到 1 篇论文 · 按版本更新时间排序上轮扫描起点 2026-11-06 07:00(北京时间)
新论文 · v1arXiv:2610.38004

Opportunistic Optical Link Scheduling in the Scalable Matching Model

Marcos T. Henriques, Olga Goussevskaia

The Scalable Matching Model (SMM) is a useful abstraction for reconfigurable datacenter networks. In SMM, a set of $n$ (Top-of-Rack) electrical packet switches is connected via a set of optical circuit switches (OCS), each realizing a $p \times p$ matching, where $p$ is the number of ports per switch. In the case when $p \ll n$, bounded-degree networks utilize only a small portion of the OCS infrastructure at each point in time, especially when traffic patterns are skewed and bursty. In this work, we propose the Opportunistic Optical Link Scheduling (OOLS), a set of lightweight OCS link scheduling routines, designed to augment bounded-degree reconfigurable network topologies by leveraging idle OCS resources. We evaluate the performance of OOLS in the SMM through simulations, using synthetic and real-world data-center workloads. Our simulation results show that OOLS substantially improves performance, lowering communication costs and boosting throughput.

尚无 AI 解读,展示原文摘要

cs.NI
arXiv ↗PDF ↗