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Sampling Based \(\delta \)-Approximate Data Aggregation in Sensor Equipped IoT Networks

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Wireless Algorithms, Systems, and Applications (WASA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10874))

Abstract

Emerging needs in data sensing applications result in the usage of IoT networks. These networks are widely deployed and exploited for various efficient data transfer. Wireless sensors can be incorporated in IoT networks to reduce the deployment costs and maintenance costs. One of the critical problems in sensor equipped IoT devices is to design an energy efficient data aggregation method that processes the maximum value query and distinct set query. Therefore, in this paper, we propose two approximate algorithms to process the maximum queries and distinct-set queries in wireless sensor networks. These two algorithms are based on uniform sampling. Solid theoretical proofs are offered which can make sure the proposed algorithms can return correct query results with a given probability. Simulation results show that both \(\delta \)-approximate maximum value and \(\delta \)-approximate distinct set algorithms perform significantly better than a simple distributed algorithm in terms of energy consumption.

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Acknowledgment

This work is partly supported by the NSF under grant No. 1741277, No. 1741279, No. 1741287, No. 1741338 and the National Natural Science Foundation of China under Grant NO. 61632010, 61502116, U1509216, 61370217.

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Authors and Affiliations

  1. Department of Computer Science, Georgia State University, Atlanta, GA, 30303, USA

    Ji Li, Madhuri Siddula & Yingshu Li

  2. Department of Computer Science, The George Washington University, Washington, D.C., 20052, USA

    Xiuzhen Cheng

  3. Department of Computer Science, Virginia Commonwealth University, Richmond, VA, 23284, USA

    Wei Cheng

  4. Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, 22030, USA

    Zhi Tian

Authors
  1. Ji Li
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  2. Madhuri Siddula
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  3. Xiuzhen Cheng
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  4. Wei Cheng
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  5. Zhi Tian
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  6. Yingshu Li
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Corresponding author

Correspondence to Yingshu Li .

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Editors and Affiliations

  1. University of South Florida, Tampa, Florida, USA

    Sriram Chellappan

  2. Virginia Commonwealth University, Richmond, Virginia, USA

    Wei Cheng

  3. Georgia State University, Atlanta, Georgia, USA

    Wei Li

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Li, J., Siddula, M., Cheng, X., Cheng, W., Tian, Z., Li, Y. (2018). Sampling Based \(\delta \)-Approximate Data Aggregation in Sensor Equipped IoT Networks. In: Chellappan, S., Cheng, W., Li, W. (eds) Wireless Algorithms, Systems, and Applications. WASA 2018. Lecture Notes in Computer Science(), vol 10874. Springer, Cham. https://doi.org/10.1007/978-3-319-94268-1_21

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  • DOI: https://doi.org/10.1007/978-3-319-94268-1_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94267-4

  • Online ISBN: 978-3-319-94268-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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