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Sympathy for the Sensor Network Debugger
Nithya Ramanathan
Kevin Chang
Rahul Kapur
Lewis Girod
Eddie Kohler
D Estrin
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SenSys’05, November 2–4, 2005, San Diego, California, USA.
Copyright 2005 ACM 1-59593-054-X/05/0011 . . . $5.00.
Third ACM Conference on Embedded Networked Sensor System (SenSys)
ABSTRACT: Being embedded in the physical world, sensor networks present a
wide range of bugs and misbehavior qualitatively different from
those in most distributed systems. Unfortunately, due to resource
constraints, programmers must investigate these bugs with only
limited visibility into the application. This paper presents the design
and evaluation of Sympathy, a tool for detecting and debugging
failures in sensor networks. Sympathy has selected metrics
that enable efficient failure detection, and includes an algorithm
that root-causes failures and localizes their sources in order to reduce
overall failure notifications and point the user to a small number
of probable causes. We describe Sympathy and evaluate its performance
through fault injection and by debugging an active application,
ESS, in simulation and deployment. We show that for a
broad class of data gathering applications, it is possible to detect
and diagnose failures by collecting and analyzing a minimal set of
metrics at a centralized sink. We have found that there is a tradeoff
between notification latency and detection accuracy; that additional
metrics traffic does not always improve notification latency;
and that Sympathy’s process of failure localization reduces primary
failure notifications by at least 50% in most cases.
SUGGESTED CITATION: Nithya Ramanathan, Kevin Chang, Rahul Kapur, Lewis Girod, Eddie Kohler, and D Estrin,
"Sympathy for the Sensor Network Debugger"
(May 5, 2005).
Center for Embedded Network Sensing.
Papers.
Paper 121.
http://repositories.cdlib.org/cens/wps/121
POST-PRINT: Nithya Ramanathan, Kevin Chang, Rahul Kapur, Lewis Girod, Eddie Kohler, and D Estrin,
"Sympathy for the Sensor Network Debugger"
(2005).
Center for Embedded Network Sensing.
Artice 1019.
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