Determining node duty cycle using Q-learning and linear regression for WSN  

作　　者：Han Yao HUANG Kyung Tae KIM Hee Yong YOUN 

机构地区：[1]College of Software,Sungkyunkwan University,Suwon 440-746,Korea

出　　处：《Frontiers of Computer Science》2021年第1期17-23,共7页中国计算机科学前沿（英文版）

基　　金：This work was partly supported by Institute for Information&communications Technology Promotion(IITP)grant funded by the Korea government(MSIT)(No.2016-0-00133,Research on Edge computing via collective intelligence of hyper-connection IoT nodes),Korea,under the National Program for Excellence in SW supervised by the IITP(Institute for Information&communications Technology Promotion)(2015-0-00914),Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education,Science and Technology(2016R1A6A3A11931385,Research of key technologies based on software defined wireless sensor network for real time public safety service,2017R1A2B2009095,Research on SDN-based WSN Supporting Realtime Stream Data Processing and Multi-connectivity),the second Brain Korea 21 PLUS project.

摘　　要：Wireless sensor network(WSN)is effective for monitoring the target environment,which consists of a large number of sensor nodes of limited energy.An efficient medium access control(MAC)protocol is thus imperative to maximize the energy efficiency and performance of WSN.The most existing MAC protocols are based on the scheduling of sleep and active period of the nodes,and do not consider the relationship between the load condition and performance.In this paper a novel scheme is proposed to properly determine the duty cycle of the WSN nodes according to the load,which employs the Q-leaming technique and function approximation with linear regression.This allows low-latency energy-efficient scheduling for a wide range of traffic conditions,and effectively overcomes the limitation of Q-learning with the problem of continuous state-action space.NS3 simulation reveals that the proposed scheme significantly improves the throughput,latency,and energy efficiency compared to the existing fully active scheme and S-MAC.

关 键 词：wireless sensor network media access control duty-cycle scheduling Q-leaming linear regression 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]