Work in Progress: Resourse-Aware Fault Localization in Large Sensor Networks

R. Mietz; K. Romer

doi:10.1109/DCOSS.2012.49

Work in Progress: Resourse-Aware Fault Localization in Large Sensor Networks

R. Mietz, K. Romer

Institute of Computer Engineering

Abstract

Sensor networks are exposed to hostile environments that may cause failures of single nodes and communication links which affect the whole network. Localizing the cause of the problem in space and time requires to collect diagnostic data from the network. Due to resource and energy constraints, however, it is not possible to continuously collect detailed diagnostic data from all nodes. We therefore propose an incremental approach where first data is logged to flash memory and later the user can pose a sequence of diagnostic queries with decreasing scope and increasing level of detail to pinpoint the cause of the problem.

Original language	English
Title of host publication	2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems
Number of pages	3
Place of Publication	Hangzhou, China
Publisher	IEEE
Publication date	01.05.2012
Pages	281-283
ISBN (Print)	978-1-4673-1693-4
ISBN (Electronic)	978-0-7695-4707-7
DOIs	https://doi.org/10.1109/DCOSS.2012.49
Publication status	Published - 01.05.2012
Event	8th IEEE International Conference on Distributed Computing in Sensor Systems - Hangzhou, China Duration: 16.05.2012 → 18.05.2012

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title = "Work in Progress: Resourse-Aware Fault Localization in Large Sensor Networks",

abstract = "Sensor networks are exposed to hostile environments that may cause failures of single nodes and communication links which affect the whole network. Localizing the cause of the problem in space and time requires to collect diagnostic data from the network. Due to resource and energy constraints, however, it is not possible to continuously collect detailed diagnostic data from all nodes. We therefore propose an incremental approach where first data is logged to flash memory and later the user can pose a sequence of diagnostic queries with decreasing scope and increasing level of detail to pinpoint the cause of the problem.",

author = "R. Mietz and K. Romer",

year = "2012",

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doi = "10.1109/DCOSS.2012.49",

language = "English",

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series = "Distributed Computing in Sensor Systems",

publisher = "IEEE",

pages = "281--283",

booktitle = "2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems",

note = "8th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2012 ; Conference date: 16-05-2012 Through 18-05-2012",

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Mietz, R & Romer, K 2012, Work in Progress: Resourse-Aware Fault Localization in Large Sensor Networks. in 2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems. Distributed Computing in Sensor Systems, IEEE, Hangzhou, China, pp. 281-283, 8th IEEE International Conference on Distributed Computing in Sensor Systems, Hangzhou, China, 16.05.12. https://doi.org/10.1109/DCOSS.2012.49

Work in Progress: Resourse-Aware Fault Localization in Large Sensor Networks. / Mietz, R.; Romer, K.
2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems. Hangzhou, China: IEEE, 2012. p. 281-283 (Distributed Computing in Sensor Systems).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

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N2 - Sensor networks are exposed to hostile environments that may cause failures of single nodes and communication links which affect the whole network. Localizing the cause of the problem in space and time requires to collect diagnostic data from the network. Due to resource and energy constraints, however, it is not possible to continuously collect detailed diagnostic data from all nodes. We therefore propose an incremental approach where first data is logged to flash memory and later the user can pose a sequence of diagnostic queries with decreasing scope and increasing level of detail to pinpoint the cause of the problem.

AB - Sensor networks are exposed to hostile environments that may cause failures of single nodes and communication links which affect the whole network. Localizing the cause of the problem in space and time requires to collect diagnostic data from the network. Due to resource and energy constraints, however, it is not possible to continuously collect detailed diagnostic data from all nodes. We therefore propose an incremental approach where first data is logged to flash memory and later the user can pose a sequence of diagnostic queries with decreasing scope and increasing level of detail to pinpoint the cause of the problem.

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T2 - 8th IEEE International Conference on Distributed Computing in Sensor Systems

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Work in Progress: Resourse-Aware Fault Localization in Large Sensor Networks

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