A Network Equivalent-Based Algorithm for Adaptive Parameter Tuning in 802.15.4 WSNs.

A Network Equivalent-Based Algorithm for Adaptive Parameter Tuning in 802.15.4 WSNs.
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802.15.4 WSN 中基于网络等效的自适应参数调整算法

DOI:
10.3390/s18072031
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发表时间:
2018-06-25
期刊:
Sensors (Basel, Switzerland)
影响因子:
--
通讯作者:
You K
You K
中科院分区:
其他
文献类型:
--
作者:
Wang Y;Yang W;Han R;You K

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以往的研究表明,在许多无线传感器网络应用中,带有默认参数的IEEE 802.15.4载波感知多址免碰撞(CSMA/CA)机制无法保证可靠性、时间效率或能效约束。虽然提出了许多自适应参数整定算法,但其中许多算法不能正确识别网络状况的变化,无法有效地进行参数整定操作。考虑到CSMA/CA带来的随机性,对于大多数提出的算法来说,区分由网络实际变化引起的重大违规与由CSMA/CA引起的一般波动是一个挑战。本文提出了一种轻量级的网络等效自适应参数调优(NEAPT)算法。它是完全分布式的,可以在没有任何预定义信息或确认的情况下工作。NEAPT不仅将可靠性作为对网络状态的一种评价,而且提出了一个称为等效节点数的综合值,并将其作为网络状态的另一个参考。仿真结果表明,NEAPT同时考虑了可靠性和等效节点数,能够有效地识别网络变化,并在静态和动态条件下为无线传感器网络(WSNs)提供足够稳定的性能。
Previous studies have shown that in many wireless sensor network applications the IEEE 802.15.4 carrier sense multiple access with collision avoidance (CSMA/CA) mechanism with default parameters cannot guarantee the constraints of reliability, time efficiency, or energy efficiency. Although many adaptive parameter tuning algorithms have been proposed, many of them cannot correctly identify the changes of the network condition and are unable to effectively perform the parameter tuning operation. Considering the randomness that CSMA/CA brings about, for most of the proposed algorithms, it is a challenge to distinguish significant violations that were caused by actual changes of the network from the general fluctuations that were due to CSMA/CA. In this paper, we propose a lightweight algorithm called the network equivalent adaptive parameter tuning (NEAPT) algorithm. It is fully distributed and can work without any predefined information or acknowledgement. NEAPT not only takes reliability as an evaluation of a network condition, but it proposes a synthetic value, called the equivalent node number, and takes it as another reference for a network condition. Simulation results show that by taking both reliability and the equivalent node number into consideration, NEAPT can effectively identify the network changes and provide adequate and steady performances for wireless sensor networks (WSNs) in both stationary and dynamic conditions.
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