research-article

TL-Tree: flash-optimized storage for time-series sensing data on sensor platforms

Authors:

Krithi RamamrithamAuthors Info & Claims

SAC '12: Proceedings of the 27th Annual ACM Symposium on Applied Computing

Pages 1565 - 1572

https://doi.org/10.1145/2245276.2232028

Published: 26 March 2012 Publication History

Abstract

Extending NAND flash to off-the-shelf sensor platforms has great potential for improving in-network processing for sensor networks. However, due to the specific read/write characteristics of NAND, the strict resource constraints of sensor devices, e.g., main memory and energy, and the time-series sensing property of sensor applications, designing an efficient resource-aware flash storage system on sensor platforms is a challenging work. In this paper, we propose Time-Log Tree (TL-Tree), a novel indexing structure that is designed to consider time-series as a primary characteristic for optimizing both memory and energy constraints. TL-Tree is an unbalanced tree tailored to temporal sensor data. It realizes the flash utilization bound problem and builds a cascaded structure wherein only the root tree and the most recently updated subtree are stored in the main memory. We prove that TL-Tree minimizes the memory cost and also maximizes the effective usage of flash capacity. Compared to other schemes, simulation results show that the TL-Tree achieves much better access and energy savings for MicaZ platforms. We developed a hardware board that includes a raw 128MB NAND flash chip on MicaZ mote, and also implemented a flash driver and the TL-Tree to demonstrate the practical use of this idea.

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Cited By

Yang MChang YTsao CHuang PChang YKuo T(2014)Garbage collection and wear leveling for flash memory: Past and future2014 International Conference on Smart Computing10.1109/SMARTCOMP.2014.7043841(66-73)Online publication date: Nov-2014
https://doi.org/10.1109/SMARTCOMP.2014.7043841
Huang ZLuo HSkoda DZhu TGu Y(2014)E-Sketch: Gathering large-scale energy consumption data based on consumption patterns2014 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2014.7004289(656-665)Online publication date: Oct-2014
https://doi.org/10.1109/BigData.2014.7004289
Lam KZhu CChang YHsieh JHuang PPoon CWang J(2014)Garbage collection of multi-version indexed data on flash memoryJournal of Systems Architecture: the EUROMICRO Journal10.1016/j.sysarc.2014.06.00460:8(630-643)Online publication date: 1-Nov-2014
https://dl.acm.org/doi/10.1016/j.sysarc.2014.06.004
Show More Cited By

Index Terms

TL-Tree: flash-optimized storage for time-series sensing data on sensor platforms
1. Computer systems organization
  1. Embedded and cyber-physical systems
  2. Real-time systems
2. Software and its engineering
  1. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        Memory management
        Secondary storage

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cover image ACM Conferences

SAC '12: Proceedings of the 27th Annual ACM Symposium on Applied Computing

March 2012

2179 pages

ISBN:9781450308571

DOI:10.1145/2245276

Conference Chairs:
Sascha Ossowski
University Rey Juan Carlos, Spain
,
Paola Lecca
The Microsoft Research - University of Trento COSBI, Italy

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGAPP: ACM Special Interest Group on Applied Computing

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 March 2012

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National Natural Science Foundation of China

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SAC 2012

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SIGAPP

SAC 2012: ACM Symposium on Applied Computing

March 26 - 30, 2012

Trento, Italy

Acceptance Rates

SAC '12 Paper Acceptance Rate 270 of 1,056 submissions, 26%;

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

Yang MChang YTsao CHuang PChang YKuo T(2014)Garbage collection and wear leveling for flash memory: Past and future2014 International Conference on Smart Computing10.1109/SMARTCOMP.2014.7043841(66-73)Online publication date: Nov-2014
https://doi.org/10.1109/SMARTCOMP.2014.7043841
Huang ZLuo HSkoda DZhu TGu Y(2014)E-Sketch: Gathering large-scale energy consumption data based on consumption patterns2014 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2014.7004289(656-665)Online publication date: Oct-2014
https://doi.org/10.1109/BigData.2014.7004289
Lam KZhu CChang YHsieh JHuang PPoon CWang J(2014)Garbage collection of multi-version indexed data on flash memoryJournal of Systems Architecture: the EUROMICRO Journal10.1016/j.sysarc.2014.06.00460:8(630-643)Online publication date: 1-Nov-2014
https://dl.acm.org/doi/10.1016/j.sysarc.2014.06.004
Wang BBaras J(2013)HybridStoreProceedings of the 10th European conference on Wireless Sensor Networks10.1007/978-3-642-36672-7_4(50-66)Online publication date: 13-Feb-2013
https://dl.acm.org/doi/10.1007/978-3-642-36672-7_4

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