Generalized decision aggregation in distributed sensing systems

Lu Su, Qi Li, Shaohan Hu, Shiguang Wang, Jing Gao, Hengchang Liu, Tarek F. Abdelzaher, Jiawei Han, Xue Liu, Yan Gao, Lance Kaplan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present GDA, a generalized decision aggregation framework that integrates information from distributed sensor nodes for decision making in a resource efficient manner. Traditional approaches that target similar problems only take as input the discrete label information from individual sensors that observe the same events. Different from them, our proposed GDA framework is able to take advantage of the confidence information of each sensor about its decision, and thus achieves higher decision accuracy. Targeting generalized problem domains, our framework can naturally handle the scenarios where different sensor nodes observe different sets of events whose numbers of possible classes may also be different. GDA also makes no assumption about the availability level of ground truth label information, while being able to take advantage of any if present. For these reasons, our approach can be applied to a much broader spectrum of sensing scenarios. The advantages of our proposed framework are demonstrated through both theoretic analysis and extensive experiments.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 35th Real-Time Systems Symposium, RTSS 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-10
Number of pages10
EditionJanuary
ISBN (Electronic)9781479972876
DOIs
StatePublished - Jan 14 2015
Event35th IEEE Real-Time Systems Symposium, RTSS 2014 - Rome, Italy
Duration: Dec 2 2014Dec 5 2014

Publication series

NameProceedings - Real-Time Systems Symposium
NumberJanuary
Volume2015-January
ISSN (Print)1052-8725

Other

Other35th IEEE Real-Time Systems Symposium, RTSS 2014
CountryItaly
CityRome
Period12/2/1412/5/14

Fingerprint

Sensor nodes
Labels
Agglomeration
Sensors
Decision making
Availability
Experiments

Keywords

  • Crowd Sensing
  • Decision Aggregation
  • Distributed Sensing System
  • Participatory Sensing
  • Social Sensing

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

Cite this

Su, L., Li, Q., Hu, S., Wang, S., Gao, J., Liu, H., ... Kaplan, L. (2015). Generalized decision aggregation in distributed sensing systems. In Proceedings - IEEE 35th Real-Time Systems Symposium, RTSS 2014 (January ed., pp. 1-10). [7010369] (Proceedings - Real-Time Systems Symposium; Vol. 2015-January, No. January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RTSS.2014.40

Generalized decision aggregation in distributed sensing systems. / Su, Lu; Li, Qi; Hu, Shaohan; Wang, Shiguang; Gao, Jing; Liu, Hengchang; Abdelzaher, Tarek F.; Han, Jiawei; Liu, Xue; Gao, Yan; Kaplan, Lance.

Proceedings - IEEE 35th Real-Time Systems Symposium, RTSS 2014. January. ed. Institute of Electrical and Electronics Engineers Inc., 2015. p. 1-10 7010369 (Proceedings - Real-Time Systems Symposium; Vol. 2015-January, No. January).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Su, L, Li, Q, Hu, S, Wang, S, Gao, J, Liu, H, Abdelzaher, TF, Han, J, Liu, X, Gao, Y & Kaplan, L 2015, Generalized decision aggregation in distributed sensing systems. in Proceedings - IEEE 35th Real-Time Systems Symposium, RTSS 2014. January edn, 7010369, Proceedings - Real-Time Systems Symposium, no. January, vol. 2015-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-10, 35th IEEE Real-Time Systems Symposium, RTSS 2014, Rome, Italy, 12/2/14. https://doi.org/10.1109/RTSS.2014.40
Su L, Li Q, Hu S, Wang S, Gao J, Liu H et al. Generalized decision aggregation in distributed sensing systems. In Proceedings - IEEE 35th Real-Time Systems Symposium, RTSS 2014. January ed. Institute of Electrical and Electronics Engineers Inc. 2015. p. 1-10. 7010369. (Proceedings - Real-Time Systems Symposium; January). https://doi.org/10.1109/RTSS.2014.40
Su, Lu ; Li, Qi ; Hu, Shaohan ; Wang, Shiguang ; Gao, Jing ; Liu, Hengchang ; Abdelzaher, Tarek F. ; Han, Jiawei ; Liu, Xue ; Gao, Yan ; Kaplan, Lance. / Generalized decision aggregation in distributed sensing systems. Proceedings - IEEE 35th Real-Time Systems Symposium, RTSS 2014. January. ed. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 1-10 (Proceedings - Real-Time Systems Symposium; January).
@inproceedings{6a03abc98d1b4f4ab2029f45bc1582ce,
title = "Generalized decision aggregation in distributed sensing systems",
abstract = "In this paper, we present GDA, a generalized decision aggregation framework that integrates information from distributed sensor nodes for decision making in a resource efficient manner. Traditional approaches that target similar problems only take as input the discrete label information from individual sensors that observe the same events. Different from them, our proposed GDA framework is able to take advantage of the confidence information of each sensor about its decision, and thus achieves higher decision accuracy. Targeting generalized problem domains, our framework can naturally handle the scenarios where different sensor nodes observe different sets of events whose numbers of possible classes may also be different. GDA also makes no assumption about the availability level of ground truth label information, while being able to take advantage of any if present. For these reasons, our approach can be applied to a much broader spectrum of sensing scenarios. The advantages of our proposed framework are demonstrated through both theoretic analysis and extensive experiments.",
keywords = "Crowd Sensing, Decision Aggregation, Distributed Sensing System, Participatory Sensing, Social Sensing",
author = "Lu Su and Qi Li and Shaohan Hu and Shiguang Wang and Jing Gao and Hengchang Liu and Abdelzaher, {Tarek F.} and Jiawei Han and Xue Liu and Yan Gao and Lance Kaplan",
year = "2015",
month = "1",
day = "14",
doi = "10.1109/RTSS.2014.40",
language = "English (US)",
series = "Proceedings - Real-Time Systems Symposium",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "January",
pages = "1--10",
booktitle = "Proceedings - IEEE 35th Real-Time Systems Symposium, RTSS 2014",
address = "United States",
edition = "January",

}

TY - GEN

T1 - Generalized decision aggregation in distributed sensing systems

AU - Su, Lu

AU - Li, Qi

AU - Hu, Shaohan

AU - Wang, Shiguang

AU - Gao, Jing

AU - Liu, Hengchang

AU - Abdelzaher, Tarek F.

AU - Han, Jiawei

AU - Liu, Xue

AU - Gao, Yan

AU - Kaplan, Lance

PY - 2015/1/14

Y1 - 2015/1/14

N2 - In this paper, we present GDA, a generalized decision aggregation framework that integrates information from distributed sensor nodes for decision making in a resource efficient manner. Traditional approaches that target similar problems only take as input the discrete label information from individual sensors that observe the same events. Different from them, our proposed GDA framework is able to take advantage of the confidence information of each sensor about its decision, and thus achieves higher decision accuracy. Targeting generalized problem domains, our framework can naturally handle the scenarios where different sensor nodes observe different sets of events whose numbers of possible classes may also be different. GDA also makes no assumption about the availability level of ground truth label information, while being able to take advantage of any if present. For these reasons, our approach can be applied to a much broader spectrum of sensing scenarios. The advantages of our proposed framework are demonstrated through both theoretic analysis and extensive experiments.

AB - In this paper, we present GDA, a generalized decision aggregation framework that integrates information from distributed sensor nodes for decision making in a resource efficient manner. Traditional approaches that target similar problems only take as input the discrete label information from individual sensors that observe the same events. Different from them, our proposed GDA framework is able to take advantage of the confidence information of each sensor about its decision, and thus achieves higher decision accuracy. Targeting generalized problem domains, our framework can naturally handle the scenarios where different sensor nodes observe different sets of events whose numbers of possible classes may also be different. GDA also makes no assumption about the availability level of ground truth label information, while being able to take advantage of any if present. For these reasons, our approach can be applied to a much broader spectrum of sensing scenarios. The advantages of our proposed framework are demonstrated through both theoretic analysis and extensive experiments.

KW - Crowd Sensing

KW - Decision Aggregation

KW - Distributed Sensing System

KW - Participatory Sensing

KW - Social Sensing

UR - http://www.scopus.com/inward/record.url?scp=84936948171&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84936948171&partnerID=8YFLogxK

U2 - 10.1109/RTSS.2014.40

DO - 10.1109/RTSS.2014.40

M3 - Conference contribution

AN - SCOPUS:84936948171

T3 - Proceedings - Real-Time Systems Symposium

SP - 1

EP - 10

BT - Proceedings - IEEE 35th Real-Time Systems Symposium, RTSS 2014

PB - Institute of Electrical and Electronics Engineers Inc.

ER -