Kosunalp, Selahattin; Chu, Yi; Mitchell, Paul D.; Grace, David; Clarke, Tim

This paper studies the potential of a novel approach to ensure more efficient and intelligent assignment of capacity through medium access control (MAC) in practical wireless sensor networks. Q-Learning is employed as an intelligent transmission strategy. We review the existing MAC protocols in the context of Q-learning. A recently-proposed, ALOHA and Q-Learning based MAC scheme, ALOHA-Q, is considered which improves the channel performance significantly with a key benefit of simplicity. Practical implementation issues of ALOHA-Q are studied. We demonstrate the performance of the ALOHA-Q through extensive simulations and evaluations in various testbeds. A new exploration/exploitation method is proposed to strengthen the merits of the ALOHA-Q against dynamic the channel and environment conditions.

AtıfScopus41·WoS29·OpenAlex37

İncele

Kosunalp, Selahattin; Mitchell, Paul Daniel; Grace, David; Clarke, Tim

This paper presents the description, practical implementation, and stability analysis of a recently proposed, energy-efficient, medium access control protocol for wireless sensor networks, ALOHA-Q, which employs a reinforcement-learning framework as an intelligent transmission strategy. The channel performance is evaluated through a simulation and experiments conducted using a real-world test-bed. The stability of the system against possible changes in the environment and changing channel conditions is studied with a discussion on the resilience level of the system. A Markov model is derived to represent the system behavior and estimate the time in which the system loses its operation. A novel scheme is also proposed to protect the lifetime of the system when the environment and channel conditions do not sufficiently maintain the system operation.

AtıfScopus7·WoS3·OpenAlex8

İncele