Distributed time-aware provenance

  • Authors:

  • Wenchao Zhou;Suyog Mapara;Yiqing Ren;Yang Li;Andreas Haeberlen;Zachary Ives;Boon Thau Loo;Micah Sherr

  • Affiliations:

  • Georgetown University, Washington, DC;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;Georgetown University, Washington, DC

  • Venue:
  • Proceedings of the VLDB Endowment
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

The ability to reason about changes in a distributed system's state enables network administrators to better diagnose protocol misconfigurations, detect intrusions, and pinpoint performance bottlenecks. We propose a novel provenance model called Distributed Time-aware Provenance (DTaP) that aids forensics and debugging in distributed systems by explicitly representing time, distributed state, and state changes. Using a distributed Datalog abstraction for modeling distributed protocols, we prove that the DTaP model provides a sound and complete representation that correctly captures dependencies among events in a distributed system. We additionally introduce DistTape, an implementation of the DTaP model that uses novel distributed storage structures, query processing, and cost-based optimization techniques to efficiently query time-aware provenance in a distributed setting. Using two example systems (declarative network routing and Hadoop MapReduce), we demonstrate that DistTape can efficiently maintain and query time-aware provenance at low communication and computation cost.