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Energy-Aware Control of Error Correction Rate for Solar-Powered Wireless Sensor Networks.

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This summary is machine-generated.

This study introduces an adaptive forward error correction (FEC) scheme for solar-powered wireless sensor networks (WSNs). It dynamically adjusts parity length to optimize data collection while managing energy consumption based on harvesting rates.

Keywords:
Reed–Solomonblackout timeenergy-awareforward error correctionsolar-poweredthroughputwireless sensor network

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Wireless Communication

Background:

  • Wireless sensor networks (WSNs) face frequent transmission errors, necessitating reliable data transfer.
  • Forward error correction (FEC) enhances reliability but increases energy consumption with longer parity.
  • Solar-powered WSNs have variable energy availability due to environmental factors.

Purpose of the Study:

  • To propose an adaptive FEC scheme for solar-powered WSNs that balances error correction capability with energy constraints.
  • To ensure reliable data transmission without compromising network operational time (blackout time).

Main Methods:

  • The proposed scheme adaptively adjusts the parity length of FEC based on the node's available energy budget.
  • Energy consumption is controlled in accordance with the energy harvesting rate.
  • Simulations were conducted to evaluate the performance of the adaptive scheme.

Main Results:

  • The adaptive FEC scheme successfully adjusts parity length to match energy harvesting rates.
  • Error recovery rates are maximized within energy budget constraints, preventing premature network shutdown.
  • The proposed scheme demonstrated improved overall data collection in various simulated environments compared to existing methods.

Conclusions:

  • Adaptive parity length adjustment in FEC is an effective strategy for energy-constrained WSNs.
  • This approach optimizes data reliability and network longevity in solar-powered WSNs.
  • The findings suggest a practical method for enhancing WSN performance in dynamic energy conditions.