TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Sequential Hypothesis Testing based Polling Interval Adaptation in Wireless Sensor Networks for IoT Applications |
| 영문제목(English Title) |
Sequential Hypothesis Testing based Polling Interval Adaptation in Wireless Sensor Networks for IoT Applications |
| 저자(Author) |
Sungryoul Lee
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| 원문수록처(Citation) |
VOL 11 NO. 03 PP. 1393 ~ 1405 (2017. 03) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
It is well known that duty-cycling control by dynamically adjusting the polling interval according to the traffic loads can effectively achieve power saving in wireless sensor networks. Thus, there has been a significant research effort in developing polling interval adaptation schemes. Especially, Dynamic Low Power Listening (DLPL) scheme is one of the most widely adopted open-looping polling interval adaptation techniques in wireless sensor networks. In DLPL scheme, if consecutive idle (busy) samplings reach a given fixed threshold, the polling interval is increased (decreased). However, due to the trial-and-error based approach, it may significantly deteriorate the system performance depending on given threshold parameters. In this paper, we propose a novel DLPL scheme, called SDL (Sequential hypothesis testing based Dynamic LPL), which employs sequential hypothesis testing to decide whether to change the polling interval conforming to various traffic conditions. Simulation results show that SDL achieves substantial power saving over state-of-the-art DLPL schemes.
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| 키워드(Keyword) |
Low power listening
sequential hypothesis testing
wireless sensor networks
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| 파일첨부 |
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