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

Institut für Technische Informatik

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.

Originalsprache	Englisch
Titel	2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems
Seitenumfang	3
Erscheinungsort	Hangzhou, China
Herausgeber (Verlag)	IEEE
Erscheinungsdatum	01.05.2012
Seiten	281-283
ISBN (Print)	978-1-4673-1693-4
ISBN (elektronisch)	978-0-7695-4707-7
DOIs	https://doi.org/10.1109/DCOSS.2012.49
Publikationsstatus	Veröffentlicht - 01.05.2012
Veranstaltung	8th IEEE International Conference on Distributed Computing in Sensor Systems - Hangzhou, China Dauer: 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",

month = may,

day = "1",

doi = "10.1109/DCOSS.2012.49",

language = "English",

isbn = "978-1-4673-1693-4",

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, S. 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

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AU - Romer, K.

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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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ER -

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

Abstract

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