arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2602.20924cs.NIcs.AIcs.SE
收藏

Airavat:一种用于互联网测量的代理框架

Airavat: An Agentic Framework for Internet Measurement

University of California, Irvine(加州大学尔湾分校)

Alagappan Ramanathan, Eunju Kang, Dongsu Han, Sangeetha Abdu Jyothi

AI总结:

Airavat通过代理框架实现互联网测量工作流的自动化生成与验证,解决了复杂分析中工具协调和方法学验证的难题。

摘要:

互联网测量面临双重挑战:复杂的分析需要专家级别的工具协调,但即使语法正确的实现也可能存在方法学缺陷且难以验证。因此,普及测量能力需要同时自动化工作流生成和对通过数十年研究建立的方法学标准的验证。我们介绍了Airavat,这是首个用于互联网测量工作流生成的代理框架,具有系统性的验证和验证。Airavat协调一组代理,模拟专家推理:三个代理分别处理问题分解、解决方案设计和代码实现,并借助现有工具的注册表提供帮助。两个专用引擎确保方法学正确性:验证引擎将工作流与编码了五十年测量研究知识图谱的图谱进行比对,而验证引擎识别适当的验证技术,这些技术基于已确立的方法论。通过四个互联网测量案例研究,我们证明Airavat(i)生成的工作流与专家级解决方案匹配,(ii)做出合理的架构决策,(iii)解决没有真实数据的新问题,(iv)识别出标准执行测试所遗漏的方法学缺陷。

英文摘要:

Internet measurement faces twin challenges: complex analyses require expert-level orchestration of tools, yet even syntactically correct implementations can have methodological flaws and can be difficult to verify. Democratizing measurement capabilities thus demands automating both workflow generation and verification against methodological standards established through decades of research. We present Airavat, the first agentic framework for Internet measurement workflow generation with systematic verification and validation. Airavat coordinates a set of agents mirroring expert reasoning: three agents handle problem decomposition, solution design, and code implementation, with assistance from a registry of existing tools. Two specialized engines ensure methodological correctness: a Verification Engine evaluates workflows against a knowledge graph encoding five decades of measurement research, while a Validation Engine identifies appropriate validation techniques grounded in established methodologies. Through four Internet measurement case studies, we demonstrate that Airavat (i) generates workflows matching expert-level solutions, (ii) makes sound architectural decisions, (iii) addresses novel problems without ground truth, and (iv) identifies methodological flaws missed by standard execution-based testing.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑