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Enabling Large- Scale Storage in Sensor Networks with the Coffee File System
2009 (English)In: Proceedings of the 8th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2009), San Francisco, USA, April 2009, 2009Conference paper (Refereed)
Place, publisher, year, edition, pages
URN: urn:nbn:se:uu:diva-142686OAI: oai:DiVA.org:uu-142686DiVA: diva2:387790
8th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2009), San Francisco, USA, April 2009
Available from: 2011-01-14 Created: 2011-01-14 Last updated: 2016-02-12
In thesis
1. Storage-Centric System Architectures for Networked, Resource-Constrained Devices
Open this publication in new window or tab >>Storage-Centric System Architectures for Networked, Resource-Constrained Devices
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The emergence of the Internet of Things (IoT) has increased the demand for networked, resource-constrained devices tremendously. Many of the devices used for IoT applications are designed to be resource-constrained, as they typically must be small, inexpensive, and powered by batteries. In this dissertation, we consider a number of challenges pertaining to these constraints: system support for energy efficiency; flash-based storage systems; programming, testing, and debugging; and safe and secure application execution. The contributions of this dissertation are made through five research papers addressing these challenges.

Firstly, to enhance the system support for energy-efficient storage in resource-constrained devices, we present the design, implementation, and evaluation of the Coffee file system and the Antelope DBMS. Coffee provides a sequential write throughput that is over 92% of the attainable flash driver throughput, and has a constant memory footprint for open files. Antelope is the first full-fledged relational DBMS for sensor networks, and it provides two novel indexing algorithms to enable fast and energy-efficient database queries.

Secondly, we contribute a framework that extends the functionality and increases the performance of sensornet checkpointing, a debugging and testing technique. Furthermore, we evaluate how different data compression algorithms can be used to decrease the energy consumption and data dissemination time when reprogramming sensor networks.

Lastly, we present Velox, a virtual machine for IoT applications. Velox can enforce application-specific resource policies. Through its policy framework and its support for high-level programming languages, Velox helps to secure IoT applications. Our experiments show that Velox monitors applications' resource usage and enforces policies with an energy overhead below 3%.

The experimental systems research conducted in this dissertation has had a substantial impact both in the academic community and the open-source software community. Several of the produced software systems and components are included in Contiki, one of the premier open-source operating systems for the IoT and sensor networks, and they are being used both in research projects and commercial products.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2016. 60 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1331
, SICS Dissertation Series, ISSN 1101-1335 ; 74
Internet of Things, wireless sensor networks, resource-constrained devices, file system, database management system, virtual machine, data compression, reprogramming, checkpointing
National Category
Computer Science
Research subject
Computer Science
urn:nbn:se:uu:diva-267628 (URN)978-91-554-9441-4 (ISBN)
Public defence
2016-02-18, ITC/2446, Lägerhyddsvägen 2, Uppsala, 13:15 (English)
Available from: 2016-01-22 Created: 2015-11-25 Last updated: 2016-02-12

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