基于强化学习的IEEE 802.15.4网络区分服务策略

doi:10.11959/j.issn.1000-436x.2015149

Abstract

Abstract:

To provide better support in differentiated service for IEEE 802.15.4,a novel differentiated service mechanism was proposed based on BCS(back off counter scheme)and reinforcement learning.In terms of end-device,BCS backoff strategy was added to original priority-based differentiated strategy to solve the service differentiation problem under higher traffic condition.Whil “ e for the coordinator,a reinforcement learning based duty-cycle adjustment algorithm was proposed toself-learning”an optimal duty-cycle according to different application requirements and environmental changes.Simulation shows that the proposed algorithm can meet the performance requirements of high-priority service under different environments and adjust the duty-cycle when traffic is changed,which showed a strong environmental adaptability.

Key words: IEEE 802.15.4/LR-WPAN, differentiated-service, BCS, reinforcement-learning, duty-cycle

Liang QIAN,Zhi-hong QIAN,Tian-ping LI,Wei QUAN. IEEE 802.15.4 differentiated service strategy based on reinforcement-learning[J]. Journal on Communications, 2015, 36(8): 171-181.

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References 13

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二进制表示	队列占用率/%
000	0～12.5
001	12.5～25
010	25～37.5
011	37.5～50
100	50～62.5
101	62.5～75
110	75～87.5
111	87.5～100

参数		值
业务量大小/(packet·s^?1)		0.2
数据分组长度/byte		70
节点个数		7
BO(SO_max)		7
仿真时间/s		8 000
	initialEnergy	1 000
	rxPower	35.28×10^?3
能量消耗/mW	txPower	31.32×10^?3
	idlePower	712×10^?6
	sleepPower	144×10^?9
强化学习	Learning-RateExploring-Rate	0.10.1

IEEE 802.15.4 differentiated service strategy based on reinforcement-learning

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