徐立鸿, 早明华, 蔚瑞华, 林维威. 温室无线传感器网络节点发射功率自适应控制算法[J]. 农业工程学报, 2014, 30(8): 142-148. DOI: 10.3969/j.issn.1002-6819.2014.08.017
    引用本文: 徐立鸿, 早明华, 蔚瑞华, 林维威. 温室无线传感器网络节点发射功率自适应控制算法[J]. 农业工程学报, 2014, 30(8): 142-148. DOI: 10.3969/j.issn.1002-6819.2014.08.017
    Xu Lihong, Zao Minghua, Wei Ruihua, Lin Weiwei. Adaptive control algorithms of transmitting power for greenhouse WSN nodes[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2014, 30(8): 142-148. DOI: 10.3969/j.issn.1002-6819.2014.08.017
    Citation: Xu Lihong, Zao Minghua, Wei Ruihua, Lin Weiwei. Adaptive control algorithms of transmitting power for greenhouse WSN nodes[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2014, 30(8): 142-148. DOI: 10.3969/j.issn.1002-6819.2014.08.017

    温室无线传感器网络节点发射功率自适应控制算法

    Adaptive control algorithms of transmitting power for greenhouse WSN nodes

    • 摘要: 为了提高无线数据传输的可靠性,基于无线传感器网络(wireless sensor network,WSN)的温室环境数据采集系统,采用试验的方法研究温室中不同环境下WSN节点之间通信的可靠性。在通信距离为5~40 m,存在作物、温室设施等遮挡影响,相对湿度为35%~80%的情况下,对丢包率和接收信号强度指示(received signal strength indication,RSSI)的关系进行研究,通过RSSI对节点间通信可靠性进行评价。在此基础上,提出WSN节点发射功率自适应控制算法。该算法以RSSI作为通信质量的评价因子,通过增大节点的发射功率来提高通信可靠性。测试结果表明,该算法能够根据当前通信状况,自适应地设置节点的发射功率,以尽可能小的发射功率将丢包率维持在1%左右。该算法对WSN在温室中的应用具有实用价值。

       

      Abstract: Abstract: In order to improve the reliability of wireless data transmission of a greenhouse environment data acquisition system, this paper studied the reliability between WSN nodes in several cases in a greenhouse based on an experimental method. When the communication quality was affected by distance, obstacles, and high humidity, the relationship between packet loss rate and RSSI (Received Signal Strength Indication) was analyzed, and then RSSI was used to evaluate the reliability of communication. In the experiment, the distance between nodes had been set from 5 m to 40 m at intervals of 5 m, and the humidity varied from 35% RH to 80% RH at intervals of 15% RH. The obstacles included tomato plants, hanging strawberry, greenhouse facilities such as shade net, heat insulation nets, and exhaust fans. The experiment results showed that the packet loss rate increased when the distance between nodes extended or the obstacles existed while it was not affected by the humidity in the greenhouse. In these circumstances, when the transmitting power of the node had been set as 0, 4, 8, 12, or 19 dBm, both the RSSI and packet loss rate changed so that the relationship between the RSSI and packet loss rate could be studied in coordinates. The results included two situations. The first was when there was no obstacle. In those cases, we found that: 1) with the increase of the RSSI of the receiving node, the packet loss rate changed with a certain trend to decrease; 2) when the RSSI value was greater than ?58 dBm, the packet loss rate was almost zero. The second was when there were different kinds of obstacles. In those cases, we found that: 1) packet loss rate decreased when the RSSI got smaller. 2) when packet loss rate was about 1%, for different obstacles, the RSSI values varied from ?58 dBm to ?50 dBm. 3) for the same RSSI, it was the smallest when there was no obstacle. Based on this study, an adaptive transmitting power control algorithm for WSN nodes was proposed in which RSSI was used to evaluate communication quality, and transmitting power was enhanced to improve the reliability of communication. This algorithm included two steps. First, it assumed that there was no obstacle, and the transmitting node estimated the RSSI of the receiving node with its own RSSI. If the estimated value was lower than ?55 dBm, the transmitting node would increase its power while if the estimated value was far more than ?55 dBm, the node would decrease its power to save energy. Second, the algorithm compared the actual packet loss rate to the reference input, so the algorithm could be corrected, depending on the error of the two. The algorithm had been tested in the greenhouse when the communication distance was 5 m, 20 m, and 40 m, and it also had been tested when obstacles existed such as tomato plants, suspended strawberry, and exhaust fans. In the worst situation, the packet loss rate was 2.2%. In addition, a contrast experiment was conducted to show that the algorithm could set the transmitting power at a low level when the communication quality was fine. For example, when the distance was 5 m and no obstacle existed, the transmitting power was set to 0 dBm, which is the smallest one of all of the available transmit values. The research provided an approach to enhance the communication quality of WSN in greenhouse under unfavorable conditions that made progress on the application of WSN to realize wireless data collection in a greenhouse.

       

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