基于强化学习的IEEE 802.15.4网络区分服务策略

钱亮; 钱志鸿; 李天平; 全薇

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

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基于强化学习的IEEE 802.15.4网络区分服务策略

学术通信 | 更新时间：2024-06-05

- 基于强化学习的IEEE 802.15.4网络区分服务策略
- IEEE 802.15.4 differentiated service strategy based on reinforcement-learning
- 通信学报 2015年36卷第8期页码：171-181
- 作者机构：
  
  吉林大学通信工程学院，吉林长春 130012
- 作者简介：
  
  [ "钱亮（1987-），男，满族，吉林四平人，吉林大学硕士生，主要研究方向为短距离无线通信技术、IEEE 802.15.4网络、射频识别技术。" ]
  [ "钱志鸿（1957-），男，吉林长春人，吉林大学教授、博士生导师，主要研究方向为近程无线网络通信技术、无线传感器网络技术、RFID（射频识别）技术、UWB （超宽带）通信技术和物联网等。" ]
  [ "李天平（1989-），男，湖北荆州人，吉林大学硕士生，主要研究方向为低速率无线个域网。" ]
  [ "全薇（1964-），女，辽宁沈阳人，吉林大学教授、硕士生导师，主要研究方向为光学信息处理。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61071073);国家自然科学基金资助项目(61371092)
- DOI：10.11959/j.issn.1000-436x.2015149
  中图分类号： TN92
- 网络出版日期：2015-08，
  
  纸质出版日期：2015-08-25
- 稿件说明：
移动端阅览
钱亮, 钱志鸿, 李天平, 等. 基于强化学习的IEEE 802.15.4网络区分服务策略[J]. 通信学报, 2015,36(8):171-181.

Liang QIAN, Zhi-hong QIAN, Tian-ping LI, et al. IEEE 802.15.4 differentiated service strategy based on reinforcement-learning[J]. Journal on communications, 2015, 36(8): 171-181.
钱亮, 钱志鸿, 李天平, 等. 基于强化学习的IEEE 802.15.4网络区分服务策略[J]. 通信学报, 2015,36(8):171-181. DOI： 10.11959/j.issn.1000-436x.2015149.

Liang QIAN, Zhi-hong QIAN, Tian-ping LI, et al. IEEE 802.15.4 differentiated service strategy based on reinforcement-learning[J]. Journal on communications, 2015, 36(8): 171-181. DOI： 10.11959/j.issn.1000-436x.2015149.

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。

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.

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Keywords

references

CALLAWAY E , GORDAY P , HESTER L . Home networking with IEEE 802.15.4:a developing standard for low-rate wireless personal area networks [J ] . IEEE Communications Magazine , 2002 , 40 ( 8 ): 70 - 77 .

OTTO C,MILENKOVIĆ A , SANDERS C . System architecture of a wireless body area sensor network for ubiquitous health monitoring [J ] . Journal of Mobile Multimedia , 2006 , 1 ( 4 ): 307 - 326 .

CAO X , CHEN J , ZHANG Y . Development of an integrated wireless sensor network micro-environmental monitoring system [J ] . ISA Transactions , 2008 , 47 ( 3 ): 247 - 255 .

IEEE 802.15.4 Standard(2003)Part 15.4:Wireless Medium Access Control(MAC)and Physical Layer(PHY)Specifications for Low-Rate Wireless Personal Area Networks(LR-WPANs) [S ] . IEEE-SA Standards Board , 2003 .

TSENG P , FENG K , LIN Y . Wireless location tracking algorithms for environments with insufficient signal sources [J ] . IEEE Transactions on Mobile Computing , 2009 , 8 ( 12 ): 1676 - 1689 .

HO C , LIN C , HWANG W . Dynamic GTS allocation scheme in IEEE 802.15.4 by multi-factor [A ] . 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing(IIH-MSP) [C ] . Piraeus , 2012 . 457 - 460 .

KOUBÂA A , ALVES M , NEFZI B . Improving the IEEE 802.15.4 slotted CSMA/CA MAC for time-critical events in wireless sensor networks [A ] . Proceedings of the Workshop on Real Time Networks(RTN ’06) [C ] . Dresden , 2006 . 270 - 277 .

KIPINS D , WILLIG A , HAUER J . The angel IEEE 802.15.4enhancement layer:coupling priority queueing and service differentiation [A ] . Wireless Conference,EW 2008.14th European [C ] . Prague , 2008 . 1 - 7 .

ROHM D , GOYAL M , HOSSEINI S. . A simulation based analysis of the impact of IEEE 802.15.4 MAC parameters on the performance under different traffic loads [J ] . Mobile Information Systems , 2009 , 5 ( 1 ): 81 - 99 .

SUTTON R , BARTO A . Reinforcement Learning:An Introduction [M ] . Massachusetts : MIT Press , 1998 .

SUTTON R , BARTO A . Introduction to Reinforcement Learning [M ] . Massachusetts : MIT Press , 1998 .

Multi-armed bandit [EB/OL ] . http://en.wikipedia.org/wiki/Multi-armed_bandit http://en.wikipedia.org/wiki/Multi-armed_bandit . 2014 .

HERNANDEZ-GARDIOL N , MAHADEVAN S . Hierarchical memory-based reinforcement learning [A ] . 14th Annual Neural Information Processing Systems Conference [C ] . 2001 . 1047 - 1053 .

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