Optimizing energy efficiency of LoRaWAN-based wireless underground sensor networks: A multi-agent reinforcement learning approach.
Guozheng ZhaoKaiqiang LinDavid N. ChapmanNicole MetjeTong HaoPublished in: Internet Things (2023)
Keyphrases
- sensor networks
- multi agent reinforcement learning
- energy efficiency
- wireless sensor
- wireless communication
- wireless sensor networks
- sensor nodes
- energy consumption
- energy efficient
- mac protocol
- network connectivity
- visual sensor networks
- sensor data
- mobile wireless
- multi agent
- multi hop
- data collection
- resource constrained
- learning agents
- energy saving
- data aggregation
- base station
- data streams
- high performance computing
- communication cost
- stochastic games
- multi agent learning
- mobile nodes
- routing protocol
- wifi
- multi agent systems
- wireless networks
- reinforcement learning
- cooperative
- network lifetime
- data transmission
- energy aware
- routing algorithm
- power consumption
- real time
- wireless channels
- pairwise
- ad hoc networks
- data sets
- topology control