摘要
为了弥补IEEE 802.15.4协议原有区分服务机制的不足,提出了一种基于BCS(backoff counter scheme)与强化学习的区分服务策略。从终端节点出发,在原优先级区分服务策略的基础上增加BCS退避策略以解决流量较大场合业务区分问题;针对协调器节点,提出了基于强化学习的占空比调整策略,该策略能根据不同应用需求和环境变化自适应调整占空比。仿真结果表明,提出算法能针对不同环境满足高优先级业务性能需求,并能根据流量变化进行占空比调整,具有极强环境适应性。
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. While for the coordinator, a reinforcement learning based duty-cycle adjustment algorithm was proposed to ＂self-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.
出处
《通信学报》
EI
CSCD
北大核心
2015年第8期171-181,共11页
Journal on Communications
基金
国家自然科学基金资助项目(61071073
61371092)~~
