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Edge Computing of Online Bounded-Error Query for Energy-Efficient IoT Sensors.

Ray-I Chang1, Jui-Hua Tsai1, Chia-Hui Wang2

  • 1Department of Engineering Science and Ocean Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan.

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Summary

This study introduces an online bounded-error query (OBEQ) scheme for Internet of Things (IoT) sensors. OBEQ significantly cuts communication costs, extending sensor network lifespan by up to 88%.

Keywords:
bounded-erroredge computingenergy efficientinternet of thingsonline queryquery processingwireless sensor networks

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Area of Science:

  • IoT and Wireless Sensor Networks
  • Data Compression and Edge Computing
  • Communication Systems

Background:

  • Transmitting data in IoT applications consumes more power than computation, necessitating communication cost reduction for extended system lifetime.
  • IoT sensor data often contains distortions, leading to bounded-error data influenced by Quality of Sensor Service (QoS²) or Quality of Decision Making (QoD) requirements.
  • Previous work introduced Bounded-Error-pruned Sensor Data Compression (BESDC) to lower point-to-point communication costs in wireless sensor networks (WSNs).

Purpose of the Study:

  • To propose an online bounded-error query (OBEQ) scheme leveraging edge computing for efficient data retrieval in IoT applications.
  • To develop a query filter mechanism that minimizes unnecessary data requests and reduces communication overhead.
  • To ensure that the proposed scheme meets specified QoS²/QoD requirements while optimizing communication efficiency.

Main Methods:

  • Implementation of an online bounded-error query (OBEQ) scheme built upon the existing BESDC framework.
  • Integration of edge computing to manage the online query process efficiently.
  • Development and application of a query filter to pre-emptively reduce data transmission by filtering unnecessary queries.

Main Results:

  • The proposed OBEQ scheme with a query filter effectively reduces communication costs associated with requesting sensing data.
  • Experimental results using real WSN data demonstrate significant performance improvements.
  • A reduction of up to 88% in communication costs was observed compared to traditional online query methods.

Conclusions:

  • The OBEQ scheme offers a viable solution for reducing communication costs in IoT sensor networks.
  • Edge computing integration enhances the efficiency of online data querying processes.
  • The query filter is crucial for achieving substantial reductions in communication overhead, thereby improving WSN performance and longevity.