research-article

Covering space for in-network sensor data storage

Authors:

Xianfeng David GuAuthors Info & Claims

IPSN '10: Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks

Pages 232 - 243

https://doi.org/10.1145/1791212.1791240

Published: 12 April 2010 Publication History

Abstract

For in-network storage schemes, one maps data, indexed in a logical space, to the distributed sensor locations. When the physical sensor network has an irregular shape and possibly holes, the mapping of data to sensors often creates unbalanced storage load with high data concentration on nodes near network boundaries. In this paper we propose to map data to a covering space, which is a tiling of the plane with copies of the sensor network, such that the sensors receive uniform storage load and traffic. We propose distributed algorithms to construct the covering space with Ricci flow and Möbius transforms. The use of the covering space improves the performance of many in-network storage and retrieval schemes such as geographical hash tables (GHTs) or the double rulings (quorum based schemes), and provides better load balanced routing.

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Cited By

(2018)Sensor data distribution and knowledge inference framework for a cognitive-based distributed storage sink environmentInternational Journal of Sensor Networks10.1504/IJSNET.2018.08838726:1(26-42)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1504/IJSNET.2018.088387
Wei ZSong MYin GSong HWang HMa XCheng A(2017)Data Access Based on a Guide Map of the Underwater Wireless Sensor NetworkSensors10.3390/s1710237417:10(2374)Online publication date: 17-Oct-2017
https://doi.org/10.3390/s17102374
Saucan E(2017)Metric Curvatures Revisited: A Brief OverviewModern Approaches to Discrete Curvature10.1007/978-3-319-58002-9_2(63-114)Online publication date: 5-Oct-2017
https://doi.org/10.1007/978-3-319-58002-9_2
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Index Terms

Covering space for in-network sensor data storage
1. Networks
  1. Network protocols
    1. Network layer protocols
      1. Routing protocols
2. Theory of computation
  1. Randomness, geometry and discrete structures
    1. Computational geometry

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cover image ACM Conferences

IPSN '10: Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks

April 2010

460 pages

ISBN:9781605589886

DOI:10.1145/1791212

Conference Chairs:
Tarek Abdelzaher
UIUC
,
Thiemo Voigt
SICS
,
Adam Wolisz
TU Berlin

Copyright © 2010 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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IEEE-SPS: Signal Processing Society
SIGBED: ACM Special Interest Group on Embedded Systems

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 April 2010

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IPSN '10

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IEEE-SPS
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IPSN '10: The 9th International Conference on Information Processing in Sensor Networks

April 12 - 16, 2010

Stockholm, Sweden

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Overall Acceptance Rate 143 of 593 submissions, 24%

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Citations

Cited By

(2018)Sensor data distribution and knowledge inference framework for a cognitive-based distributed storage sink environmentInternational Journal of Sensor Networks10.1504/IJSNET.2018.08838726:1(26-42)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1504/IJSNET.2018.088387
Wei ZSong MYin GSong HWang HMa XCheng A(2017)Data Access Based on a Guide Map of the Underwater Wireless Sensor NetworkSensors10.3390/s1710237417:10(2374)Online publication date: 17-Oct-2017
https://doi.org/10.3390/s17102374
Saucan E(2017)Metric Curvatures Revisited: A Brief OverviewModern Approaches to Discrete Curvature10.1007/978-3-319-58002-9_2(63-114)Online publication date: 5-Oct-2017
https://doi.org/10.1007/978-3-319-58002-9_2
Liu WDeng TYang Jiang HLiao XLiu JLi BJiang G(2016)Towards Robust Surface Skeleton Extraction and Its Applications in 3D Wireless Sensor NetworksIEEE/ACM Transactions on Networking10.1109/TNET.2016.251634324:6(3300-3313)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1109/TNET.2016.2516343
Gao JDavid Gu XLuo F(2016)Discrete Ricci Flow for Geometric RoutingEncyclopedia of Algorithms10.1007/978-1-4939-2864-4_602(556-563)Online publication date: 22-Apr-2016
https://doi.org/10.1007/978-1-4939-2864-4_602
Yang YJin MZhao YWu H(2015)Distributed information storage and retrieval in 3-d sensor networks with general topologiesIEEE/ACM Transactions on Networking10.1109/TNET.2014.231780923:4(1149-1162)Online publication date: 1-Aug-2015
https://dl.acm.org/doi/10.1109/TNET.2014.2317809
Albano MChessa S(2015)Replication vs erasure coding in data centric storage for wireless sensor networksComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2014.11.01877:C(42-55)Online publication date: 11-Feb-2015
https://dl.acm.org/doi/10.1016/j.comnet.2014.11.018
Zhu DTao QXing JWang YLiu WDeng TLin HWang CJiang H(2015)Boundary-free skeleton extraction and its evaluation in sensor networksWireless Networks10.1007/s11276-014-0742-x21:1(269-280)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1007/s11276-014-0742-x
Gao JGoswami M(2015)Medial Axis Based Routing Has Constant Load Balancing FactorAlgorithms - ESA 201510.1007/978-3-662-48350-3_47(557-569)Online publication date: 12-Nov-2015
https://doi.org/10.1007/978-3-662-48350-3_47
Gao JGu XLuo F(2015)Discrete Ricci Flow for Geometric RoutingEncyclopedia of Algorithms10.1007/978-3-642-27848-8_602-1(1-8)Online publication date: 5-May-2015
https://doi.org/10.1007/978-3-642-27848-8_602-1
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