skip to main content
10.1145/1080885.1080896acmconferencesArticle/Chapter ViewAbstractPublication PagesdmsnConference Proceedingsconference-collections
Article

The threshold join algorithm for top-k queries in distributed sensor networks

Published: 30 August 2005 Publication History

Abstract

In this paper we present the Threshold Join Algorithm (TJA), which is an efficient TOP-k query processing algorithm for distributed sensor networks. The objective of a top-k query is to find the k highest ranked answers to a user defined similarity function. The evaluation of such a query in a sensor network environment is associated with the transfer of data over an extremely expensive communication medium. TJA uses a non-uniform threshold on the queried attribute in order to minimize the number of tuples that have to be transferred towards the querying node. Additionally, TJA resolves queries in the network rather than in a centralized fashion, which minimizes even more the consumption of bandwidth and delay. Our preliminary experimental results, using our trace driven simulator, show that TJA is both practical and efficient.

References

[1]
N. Bruno, L. Gravano and A. Marian, "Evaluating Top-k Queries Over Web Accessible Databases", In Proceedings of the 18th International Conference on Data Engineering, San Jose, CA, USA, Pages 369, 2002.
[2]
B. Babcock and C. Olston, "Distributed Top-K Monitoring", In Proceedings of the ACM SIGMOD international conference on Management of data, San Diego, CA, USA, Pages 28--39, 2003.
[3]
P. Cao and Z. Wang, "Efficient Top-K Query Calculation in Distributed Networks", In Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing, St. John's, Newfoundland, Canada, Pages 206--215, 2004.
[4]
A. Deligiannakis, Y. Kotidis, N. Roussopoulos "Hierarchical in-Network Data Aggregation with Quality Guarantees", In 9th International Conference on Extending Database Technology, Heraklion, Greece, March 14-18, Pages 658--675, 2004.
[5]
R. Fagin, "Combining Fuzzy Information from Multiple Systems", In Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems, Montreal, Quebec, Canada, Pages 216--226, 1996.
[6]
R. Fagin, A. Lotem and M. Naor, "Optimal Aggregation Algorithms For Middleware", In Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, Santa Barbara, CA, USA, Pages 102--113, 2001.
[7]
S.R. Madden, M.J. Franklin, J.M. Hellerstein, and W. Hong. "TAG: a Tiny AGgregation Service for Ad-Hoc Sensor Networks", In Proceedings of the 5th symposium on Operating systems design and implementation, Boston, MA, USA, Pages 131--146, 2002.
[8]
S.Madden, M.Franklin, J.Hellerstein, W.Hong, "The Design of an Acquisitional Query Processor for Sensor Networks", In Proceedings of the 2003 ACM SIGMOD international conference on Management of data, San Diego, CA, USA, Pages 491--502, 2003.
[9]
S. Michel, P. Triantafillou, G. Weikum "KLEE: A Framework for Distributed Top-k Query Algorithms", In 31st conference in the series of the Very Large Data Bases, Trondheim, Norway, 2005.
[10]
S. Neema, A. Mitra, A. Banerjee, W. Najjar, D. Zeinalipour-Yazti, D. Gunopulos, V. Kalogeraki, "NODES: A Novel System Design for Embedded Sensor Networks", Demo at 4th International Symposium on Information Processing in Sensor Networks, Los Angeles, CA, USA, April 25-27, 2005.
[11]
Y. Yao, J.E. Gehrke, "Query Processing in Sensor Networks", In First Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, January 5-8, 2003.
[12]
D. Zeinalipour-Yazti, S. Neema, D. Gunopulos, V. Kalogeraki and W. Najjar, "Data Acquision in Sensor Networks with Large Memories", In 1st IEEE International Workshop on Networking Meets Databases, Tokyo, Japan, April 8-9, 2005.

Cited By

View all
  • (2023)Niffler: Real-time Device-level Anomalies Detection in Smart HomeACM Transactions on the Web10.1145/358607317:3(1-27)Online publication date: 1-Mar-2023
  • (2021) Content-Based Wake-Up for Top- k Query in Wireless Sensor Networks IEEE Transactions on Green Communications and Networking10.1109/TGCN.2020.30338445:1(362-377)Online publication date: Mar-2021
  • (2020)Efficient and Robust Top-k Algorithms for Big Data IoTICC 2020 - 2020 IEEE International Conference on Communications (ICC)10.1109/ICC40277.2020.9148639(1-6)Online publication date: Jun-2020
  • Show More Cited By

Index Terms

  1. The threshold join algorithm for top-k queries in distributed sensor networks

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    DMSN '05: Proceedings of the 2nd international workshop on Data management for sensor networks
    August 2005
    76 pages
    ISBN:1595932062
    DOI:10.1145/1080885
    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]

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 30 August 2005

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. distributed systems
    2. sensor networks
    3. top-K queries

    Qualifiers

    • Article

    Acceptance Rates

    Overall Acceptance Rate 6 of 16 submissions, 38%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)2
    • Downloads (Last 6 weeks)1
    Reflects downloads up to 18 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2023)Niffler: Real-time Device-level Anomalies Detection in Smart HomeACM Transactions on the Web10.1145/358607317:3(1-27)Online publication date: 1-Mar-2023
    • (2021) Content-Based Wake-Up for Top- k Query in Wireless Sensor Networks IEEE Transactions on Green Communications and Networking10.1109/TGCN.2020.30338445:1(362-377)Online publication date: Mar-2021
    • (2020)Efficient and Robust Top-k Algorithms for Big Data IoTICC 2020 - 2020 IEEE International Conference on Communications (ICC)10.1109/ICC40277.2020.9148639(1-6)Online publication date: Jun-2020
    • (2019)Real-Time Trajectory Similarity Processing Using Longest Common Subsequence2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)10.1109/HPCC/SmartCity/DSS.2019.00194(1398-1405)Online publication date: Aug-2019
    • (2019)QBS-Tree: A Spatial Index with High Update Efficiency for Real-Time Processing System2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)10.1109/HPCC/SmartCity/DSS.2019.00179(1282-1289)Online publication date: Aug-2019
    • (2019)Distributed and parallel processing for real-time and dynamic spatio-temporal graphWorld Wide Web10.1007/s11280-019-00741-6Online publication date: 18-Nov-2019
    • (2018)Scalable Distributed Top-k Join Queries in Topic-Based Pub/Sub Systems2018 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2018.8621949(378-383)Online publication date: Dec-2018
    • (2017)Top-k Retrieval Techniques in Distributed Sensor SystemsEncyclopedia of GIS10.1007/978-3-319-17885-1_1395(2258-2267)Online publication date: 12-May-2017
    • (2016)Efficient accuracy evaluation for multi-modal sensed dataJournal of Combinatorial Optimization10.1007/s10878-015-9920-832:4(1068-1088)Online publication date: 1-Nov-2016
    • (2016)Top-k Retrieval Techniques in Distributed Sensor SystemsEncyclopedia of GIS10.1007/978-3-319-23519-6_1395-2(1-10)Online publication date: 5-Jul-2016
    • Show More Cited By

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media