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On Transient Queue-Size Distribution in a Model of WSN Node with Threshold-Type Power-Saving Algorithm.

Wojciech M Kempa1, Dariusz Kurzyk2

  • 1Department of Mathematics Applications and Methods for Artificial Intelligence, Faculty of Applied Mathematics, Silesian University of Technology, 23 Kaszubska Str., 44-100 Gliwice, Poland.

Sensors (Basel, Switzerland)
|December 11, 2022
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Summary
This summary is machine-generated.

This study introduces a queueing model for wireless sensor network (WSN) nodes using a threshold strategy. It provides a novel formula for transient queue-size distribution, crucial for optimizing WSN performance.

Keywords:
N-policypower savingqueue sizetransient statewireless sensor network

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Operations Research

Background:

  • Wireless Sensor Networks (WSNs) are critical for data collection but face operational challenges.
  • Existing queueing models often lack transient analysis for nodes with limited service access.
  • Node power management and efficient packet handling are key performance factors in WSNs.

Purpose of the Study:

  • To develop a queueing model for a WSN node employing a threshold-based activation strategy.
  • To derive a formula for the Laplace transform of the transient queue-size distribution.
  • To analyze the system's performance based on key input parameters.

Main Methods:

  • Development of a queueing model incorporating a buffer threshold for node activation.
  • Application of embedded Markov chain concepts and the formula for total probability.
  • Utilizing renewal theory and algebraic methods for analytical derivations.

Main Results:

  • A novel formula for the Laplace transform of the transient queue-size distribution was derived.
  • The formula explicitly incorporates essential system input parameters.
  • Numerical examples demonstrate the model's practical applicability.

Conclusions:

  • The proposed model and derived formula offer a new analytical tool for WSN node operation.
  • Transient analysis provides deeper insights than equilibrium analysis for WSN performance.
  • The threshold strategy is effective for managing WSN node activity and resource utilization.