Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10338321 | Computer Communications | 2013 | 6 Pages |
Abstract
In this work, we present an energy efficient architecture for UA-WSNs, which employs a reinforcement learning algorithm and a slotted Carrier Sensing Multiple Access (slotted CSMA) protocol. Due to the reinforcement learning algorithm, the proposed system is capable of optimising its parameters to adapt to the underwater environment after having been deployed. Simulation results show that the lifetime of the network is extended significantly with the proposed architecture by lowering the number of collisions and retransmissions of data packets.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Lu Jin, Defeng (David) Huang,