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针对 IEEE 802.15.4 无线传感器网络的附加载波侦听研究。

Study on additional carrier sensing for IEEE 802.15.4 wireless sensor networks.

机构信息

Department of Electrical Engineering, National Taiwan University of Science and Technology, 43 Keelung Rd., Section 4, Taipei 106, Taiwan.

出版信息

Sensors (Basel). 2010;10(7):6275-89. doi: 10.3390/s100706275. Epub 2010 Jun 24.

DOI:10.3390/s100706275
PMID:22163549
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3231146/
Abstract

Wireless sensor networks based on the IEEE 802.15.4 standard are able to achieve low-power transmissions in the guise of low-rate and short-distance wireless personal area networks (WPANs). The slotted carrier sense multiple access with collision avoidance (CSMA/CA) is used for contention mechanism. Sensor nodes perform a backoff process as soon as the clear channel assessment (CCA) detects a busy channel. In doing so they may neglect the implicit information of the failed CCA detection and further cause the redundant sensing. The blind backoff process in the slotted CSMA/CA will cause lower channel utilization. This paper proposes an additional carrier sensing (ACS) algorithm based on IEEE 802.15.4 to enhance the carrier sensing mechanism for the original slotted CSMA/CA. An analytical Markov chain model is developed to evaluate the performance of the ACS algorithm. Both analytical and simulation results show that the proposed algorithm performs better than IEEE 802.15.4, which in turn significantly improves throughput, average medium access control (MAC) delay and power consumption of CCA detection.

摘要

基于 IEEE 802.15.4 标准的无线传感器网络能够通过低速率、短距离的无线个人区域网 (WPAN) 实现低功耗传输。时隙载波侦听多址接入/冲突避免 (CSMA/CA) 用于竞争机制。一旦清晰信道评估 (CCA) 检测到繁忙信道,传感器节点就会执行回退过程。在这样做的过程中,它们可能会忽略失败的 CCA 检测的隐含信息,并进一步导致冗余感测。时隙 CSMA/CA 中的盲目回退过程会导致较低的信道利用率。本文提出了一种基于 IEEE 802.15.4 的附加载波侦听 (ACS) 算法,以增强原始时隙 CSMA/CA 的载波侦听机制。开发了一个分析马尔可夫链模型来评估 ACS 算法的性能。分析和仿真结果均表明,所提出的算法优于 IEEE 802.15.4,从而显著提高了吞吐量、平均媒质接入控制 (MAC) 延迟和 CCA 检测的功耗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/cc293d3addea/sensors-10-06275f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/90adf5475c4b/sensors-10-06275f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/2188a9cc7daf/sensors-10-06275f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/0c3c442c59ed/sensors-10-06275f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/7f1a6bc80de8/sensors-10-06275f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/52e071b7ae7e/sensors-10-06275f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/cc293d3addea/sensors-10-06275f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/90adf5475c4b/sensors-10-06275f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/2188a9cc7daf/sensors-10-06275f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/0c3c442c59ed/sensors-10-06275f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/7f1a6bc80de8/sensors-10-06275f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/52e071b7ae7e/sensors-10-06275f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b76/3231146/cc293d3addea/sensors-10-06275f6.jpg

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