本文選題：無線傳感器網(wǎng)絡(luò)(WSN) + 節(jié)點功率��； 參考：《計算機(jī)應(yīng)用研究》2017年01期

【摘要】：針對大多數(shù)現(xiàn)有無線傳感器網(wǎng)絡(luò)目標(biāo)覆蓋方案沒有考慮傳感器功率(傳感范圍)可調(diào)的問題,提出一種基于學(xué)習(xí)自動機(jī)(learning automata,LA)和節(jié)點功率自適應(yīng)調(diào)整的WSN的目標(biāo)覆蓋方案。利用LA算法根據(jù)節(jié)點能量自適應(yīng)調(diào)整節(jié)點的發(fā)射功率,構(gòu)建能夠覆蓋所有目標(biāo)的覆蓋集,并通過精簡過程獲得最小覆蓋集,從而減低節(jié)點的能耗,提高網(wǎng)絡(luò)的生命周期。通過實驗研究了傳感器數(shù)量和目標(biāo)數(shù)量對網(wǎng)絡(luò)壽命的影響,并將該方案與基于貪婪算法、遺傳算法的方案進(jìn)行比較,結(jié)果表明,該方案能夠獲得更多的覆蓋集和更長的網(wǎng)絡(luò)壽命。
[Abstract]:In view of the fact that most existing target coverage schemes in wireless sensor networks do not consider the adjustable sensor power (sensor range), a target coverage scheme based on learning automat la and adaptive adjustment of node power for WSN is proposed. The LA algorithm adaptively adjusts the transmit power of the node according to the node energy, constructs the covering set which can cover all the targets, and obtains the minimum cover set by reducing the process, thus reducing the energy consumption of the node and increasing the lifetime of the network. The effects of the number of sensors and the number of targets on the network life are studied through experiments. The results show that the proposed scheme is compared with the scheme based on greedy algorithm and genetic algorithm. This scheme can obtain more overlay sets and longer network lifetime.
【作者單位】： 中原工學(xué)院計算機(jī)學(xué)院;武漢大學(xué)計算機(jī)學(xué)院;
【基金】：國家自然科學(xué)基金資助項目(61373169) 國家“863”計劃資助項目(2013AA122301)
【分類號】：TP212.9;TN929.5

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