Rake: Semantics assisted network-based tracing framework

Yao Zhao, Yinzhi Cao, Yan Chen, Ming Zhang, Anup Goyal

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


The ability to trace request execution paths is critical for diagnosing performance faults in large-scale distributed systems. Previous black-box and white-box approaches are either inaccurate or invasive. We present a novel semantics-assisted gray-box tracing approach, called Rake, which can accurately trace individual request by observing network traffic. Rake infers the causality between messages by identifying polymorphic IDs in messages according to application semantics. To make Rake universally applicable, we design a Rake language so that users can easily describe necessary semantics of their applications while reusing the core Rake component. We evaluate Rake using a few popular distributed applications, including web search, distributed computing cluster, content provider network, and online chatting. Our results demonstrate Rake is much more accurate than the black-box approaches while requiring no modification to OS/applications. In the CoralCDN (a content distributed network) experiments, Rake links messages with much higher accuracy than WAP5, a state-of-the-art blackbox approach. In the Hadoop (a distributed computing cluster platform) experiments, Rake helps reveal several previously unknown issues that may lead to performance degradation, including a RPC (Remote Procedure Call) abusing problem.

Original languageEnglish (US)
Article number6313581
Pages (from-to)3-14
Number of pages12
JournalIEEE Transactions on Network and Service Management
Issue number1
StatePublished - Mar 2013


  • Rake
  • Tracing framework

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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