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Approximate Holistic Aggregation in Wireless Sensor Networks

Authors:

Chaokun Wang, and

Yingshu LiAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 13, Issue 2

Article No.: 11, Pages 1 - 24

https://doi.org/10.1145/3027488

Published: 19 April 2017 Publication History

Abstract

Holistic aggregations are popular queries for users to obtain detailed summary information from Wireless Sensor Networks. An aggregation operation is holistic if there is no constant bound on the size of the storage needed to describe a sub-aggregation. Since holistic aggregation cannot be distributable, it requires that all the sensory data should be sent to the sink in order to obtain the exact holistic aggregation results, which costs lots of energy. However, in most applications, exact holistic aggregation results are not necessary; instead, approximate results are acceptable. To save energy as much as possible, we study the approximated holistic aggregation algorithms based on uniform sampling. In this article, four holistic aggregation operations, frequency, distinct-count, rank, and quantile, are investigated. The mathematical methods to construct their estimators and determine optional sample size are proposed, and the correctness of these methods are proved. Four corresponding distributed holistic algorithms to derive (ϵ, δ)-approximate aggregation results are given. The solid theoretical analysis and extensive simulation results show that all the proposed algorithms have high performance on the aspects of accuracy and energy consumption.

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Fan XWang YHuo YTian Z(2023)1-Bit Compressive Sensing for Efficient Federated Learning Over the AirIEEE Transactions on Wireless Communications10.1109/TWC.2022.320919022:3(2139-2155)Online publication date: Mar-2023
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Index Terms

Approximate Holistic Aggregation in Wireless Sensor Networks
1. Networks
  1. Network types
    1. Cyber-physical networks
      1. Sensor networks

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Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 13, Issue 2

May 2017

235 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/3081318

Editor:
Chenyang Lu
Department of Computer Science and Engineering / School of Engineering and Applied Sciences / Washington University / 1 Brookings Drive / St. Louis, MO 63130

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Copyright © 2017 ACM.

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Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 19 April 2017

Accepted: 01 December 2016

Revised: 01 December 2016

Received: 01 May 2015

Published in TOSN Volume 13, Issue 2

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Funding Sources

Key Program of the National Natural Science Foundation of China
Research Fund for the Doctoral Program of Higher Education of China
National Science Foundation (NSF)
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities

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Fan XWang YHuo YTian Z(2023)1-Bit Compressive Sensing for Efficient Federated Learning Over the AirIEEE Transactions on Wireless Communications10.1109/TWC.2022.320919022:3(2139-2155)Online publication date: Mar-2023
https://doi.org/10.1109/TWC.2022.3209190
Zheng XTian LCai Z(2023)A Fair and Rational Data Sharing Strategy Toward Two-Stage Industrial Internet of ThingsIEEE Transactions on Industrial Informatics10.1109/TII.2022.317936119:1(1088-1096)Online publication date: Jan-2023
https://doi.org/10.1109/TII.2022.3179361
Yang XGuan XWang NLiu YWu HZhang Y(2023)Cloud-Edge-End Intelligence for Fault-Tolerant Renewable Energy Accommodation in Smart GridIEEE Transactions on Cloud Computing10.1109/TCC.2021.313354011:2(1144-1156)Online publication date: 1-Apr-2023
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Cai ZChen QShi TZhu TChen KLi Y(2023)Battery-Free Wireless Sensor Networks: A Comprehensive SurveyIEEE Internet of Things Journal10.1109/JIOT.2022.322238610:6(5543-5570)Online publication date: 15-Mar-2023
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Chen ZWang JXu BXiao LLong J(2023)A Density Routing Algorithm in Wireless Sensor Networks for Dangerous Chemicals Monitoring2023 12th International Conference of Information and Communication Technology (ICTech)10.1109/ICTech58362.2023.00105(537-544)Online publication date: Apr-2023
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Sheeja Rani SSankar K(2023)Improved buffalo optimized deep feed forward neural learning based multipath routing for energy efficient data aggregation in WSNMeasurement: Sensors10.1016/j.measen.2022.10066227(100662)Online publication date: Jun-2023
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Gotfryd KCichoń J(2023)On distributed data aggregation and the precision of approximate histogramsJournal of Parallel and Distributed Computing10.1016/j.jpdc.2023.104722180:COnline publication date: 1-Oct-2023
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Bomnale AMore A(2023)Node utilization index-based data routing and aggregation protocol for energy-efficient wireless sensor networksThe Journal of Supercomputing10.1007/s11227-023-05800-480:7(9220-9252)Online publication date: 6-Dec-2023
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Hong YLuo CLi DChen ZWang X(2022)Lifetime-Maximized Strong Barrier Coverage of 3D Camera Sensor NetworksWireless Communications & Mobile Computing10.1155/2022/26599012022Online publication date: 1-Jan-2022
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