Balancing Energy Expenditure in WSNs through Reinforcement Learning : A Study

@inproceedings{Frster2008BalancingEE,
  title={Balancing Energy Expenditure in WSNs through Reinforcement Learning : A Study},
  author={Anna F{\"o}rster},
  year={2008}
}
This work describes a study of applying reinforcement learning to balance energy expenditure in wireless sensor networks, contributing both with a protocol and a novel observation regarding exploration in reinforcement learning. Our starting point is FROMS, our own multi-source multi-sink routing protocol which exploits learning to identify the lowest cost paths for data delivery. The primary modification here is an extension of the cost function to consider node battery levels in addition to… CONTINUE READING

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Application of machine learning (reinforcement learning) for routing in Wireless Sensor Networks (WSNs)

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