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A Deadline-Aware Scheduling and Forwarding Scheme in Wireless Sensor Networks.

Thi-Nga Dao1, Seokhoon Yoon2, Jangyoung Kim3

  • 1Department of Electrical and Computer Engineering, University of Ulsan, Ulsan 680-749, Korea. daothinga.mta@gmail.com.

Sensors (Basel, Switzerland)
|January 8, 2016
PubMed
Summary
This summary is machine-generated.

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This study introduces a deadline-aware scheduling and forwarding (DASF) algorithm to maximize duty cycling in wireless sensor networks (WSNs). DASF ensures data delivery within delay constraints, improving energy efficiency and packet success rates.

Area of Science:

  • Computer Science
  • Network Engineering
  • Wireless Communication

Background:

  • Wireless sensor networks (WSNs) face a trade-off between energy conservation via duty cycling and end-to-end (E2E) packet delay.
  • Increasing duty cycle intervals reduces energy consumption but can violate strict delay bounds for data delivery.
  • Meeting delay-constrained success ratio (DCSR) requirements is critical for many WSN applications.

Purpose of the Study:

  • To develop a novel algorithm that maximizes the duty cycle in WSNs while guaranteeing a required DCSR.
  • To address the challenge of balancing energy efficiency and timely data delivery in WSNs.

Main Methods:

  • Propose the deadline-aware scheduling and forwarding (DASF) algorithm.
  • Estimate E2E delay distribution to determine the optimal duty cycle interval for achieving the target DCSR.
Keywords:
delay boundduty-cycled wireless sensor networksgeographic forwardingrouting protocol

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  • Implement a decentralized scheduling approach where nodes independently select wake-up times and forward packets to nodes within a potential forwarding set based on distance to the sink.

    • Main Results:

    • The proposed DASF algorithm successfully achieves the required DCSR.
    • DASF demonstrates superior performance compared to existing algorithms regarding E2E delay and DCSR.
    • The algorithm operates without requiring time synchronization between nodes or prior knowledge of neighboring nodes.

    Conclusions:

    • DASF effectively maximizes duty cycling in WSNs while ensuring data packets meet specified delay constraints.
    • The algorithm offers a practical solution for energy-efficient WSNs that require guaranteed data delivery timeliness.
    • DASF's decentralized nature and lack of synchronization requirements simplify deployment and enhance robustness.