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Abstract
In a wireless sensor network (WSN) environment with frequent errors, forward error correction (FEC) is usually employed at the link layer to achieve reliable transmission. In the FEC scheme, the error correction rate varies depending on the length of parity used for the recovery of broken data. The longer the parity length, the higher the possible error correction rate. However, this also means that the energy consumption increases. Meanwhile, in a solar-powered WSN, the energy of each node can be periodically collected, but the amount of collected energy varies drastically depending on the harvesting environment, including factors such as the weather, season and time of day. Therefore, each node must control energy consumption according to the energy harvesting rate. The scheme proposed in this study executes this control by adaptively adjusting the parity length of FEC according to the given energy budget of a node for the next period. This means that the error recovery rate can be increased as much as possible without adversely affecting the blackout time. Simulation results show that the proposed scheme improves the amount of data collected from the entire network for each environment compared with previous schemes.
Highlights
Wireless sensor nodes consume limited hardware resources and have a short lifetime, especially owing to small battery capacities
RS(36, 32) uses only four symbols (32 bits) as parity bits for the error recovery of 32 data symbols (256 bits) in an RS block. This RS(36, 32) enjoys the advantage of the amount of energy used in the forward error correction (FEC) being small, but the drawback is that the data recovery rate is low
The two-level RS scheme is similar to energy-aware RS (EA-RS), in that the parity length is dynamically determined according to the energy state
Summary
Wireless sensor nodes consume limited hardware resources and have a short lifetime, especially owing to small battery capacities. For this reason, many studies are actively being conducted in order to overcome the problems of restricted energy in wireless sensor networks (WSNs). Because the amount of solar energy that can be harvested varies dynamically depending on the environment (e.g., time of day, weather, season and location), the energy consumption of a node must be carefully controlled with the consideration of the following objectives: . Because the energy harvested in one day can vary owing to environmental conditions, a node should adapt its power consumption rate to match the harvested energy for eternal operations
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