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Title:Scaling Data-Plane Logging in Large Scale Networks
Author(s):Arefin, Md Ahsan; Khurshid, Ahmed; Caesar, Matthew; Nahrstedt, Klara
Subject(s):Network Management
Traffic Engineering
Measurement and Analysis
Network Monitoring
Data-plane Logging
Abstract:Understanding and troubleshooting wide area networks (such as military backbone networks and ISP networks) are challenging tasks due to their large, distributed, and highly dynamic nature. Building a system that can record and replay fine-grained behaviors of such networks would simplify this problem by allowing operators to recreate the sequence and precise ordering of events (e.g., packet-level forwarding decisions, route changes, failures) taking place in their networks. However, doing this at large scales seems intractable due to the vast amount of information that would need to be logged. In this paper, we propose a scalable and reliable framework to monitor fine-grained data-plane behavior within a large network. We give a feasible architecture for a distributed logging facility, a tree-based data structure for log compression and show how this logged information helps network operators to detect and debug anomalous behavior of the network. Experimental results obtained through trace-driven simulations and Click software router experiments show that our design is lightweight in terms of processing time, memory requirement and control overhead, yet still achieves over 99%precision in capturing network events.
Issue Date:2011-08-11
Citation Info:IEEE MILCOM 2011
Genre:Technical Report
Publication Status:published or submitted for publication
Peer Reviewed:is peer reviewed
Sponsor:NSF CNS 1053781
NSF NeTSE 1012194
NSF NeTS 0964081
NSF CSR 0834480
NSF CSR 0720702
International Fulbright S&T Award
Date Available in IDEALS:2011-08-11

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