Title :
RL-based superframe order adaptation algorithm for IEEE 802.15.4 networks
Author :
Jianlin, Mao ; Fenghong, Xiang ; Hua, Lai
Author_Institution :
Kunming Univ. of Sci. & Technol., Kunming, China
Abstract :
In wireless sensor networks, it is an important problem to adjust the work time window in each working/sleeping period to save energy under light network loads and decrease the packet delay under heavy network loads. In this paper, we introduce reinforcement learning method into this problem. We discuss the algorithm design method in a simple IEEE 802.15.4 network, where an RL-based adaptive algorithm is proposed. Simulation results show that this RL-based algorithm can adapt to the change of data flow and make a good tradeoff between the energy-saving performance and the packet delay performance.
Keywords :
learning (artificial intelligence); telecommunication computing; wireless sensor networks; IEEE 802.15.4 network; RL-based superframe order adaptation algorithm; network load; packet delay performance; reinforcement learning method; wireless sensor network; Adaptive algorithm; Algorithm design and analysis; Delay effects; Learning; Media Access Protocol; Monitoring; Scheduling; Telecommunication traffic; Traffic control; Wireless sensor networks; IEEE 802.15.4; Reinforcement learning; Superframe Order; Wireless Sensor Networks;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5194820