本文選題：K-means算法 + 均勻分簇　； 參考：《小型微型計(jì)算機(jī)系統(tǒng)》2017年08期

【摘要】：針對(duì)LEACH協(xié)議簇頭節(jié)點(diǎn)分布不均導(dǎo)致無(wú)線傳感網(wǎng)節(jié)點(diǎn)能量消耗不均衡等不足,提出一種結(jié)合K-means均勻分簇和數(shù)據(jù)回歸的能量均衡策略.采用優(yōu)化初始簇中心K-means算法構(gòu)建均勻分簇的分級(jí)無(wú)線傳感網(wǎng),通過(guò)獲取節(jié)點(diǎn)地理位置信息,采用K-means聚類(lèi)算法形成k個(gè)均勻分簇,再選舉簇內(nèi)節(jié)點(diǎn)剩余能量最多者當(dāng)選簇頭.該成簇算法可以使網(wǎng)絡(luò)負(fù)載均勻,延長(zhǎng)網(wǎng)絡(luò)生存周期.通過(guò)優(yōu)化初始簇中心的選擇,降低K-means算法的迭代次數(shù),使其更快收斂,成簇時(shí)間開(kāi)銷(xiāo)更少,簇與簇之間的地理分布也更均勻.在穩(wěn)定數(shù)據(jù)傳輸階段,采用數(shù)據(jù)回歸的方法來(lái)減少普通節(jié)點(diǎn)與簇首的通信量,以達(dá)到降低功耗的作用.實(shí)驗(yàn)結(jié)果表明,該策略能夠有效降低節(jié)點(diǎn)的功耗,延長(zhǎng)網(wǎng)絡(luò)的生存時(shí)間.
[Abstract]:An energy equalization strategy combining K-means uniform clustering and data regression is proposed to solve the problem that the uneven distribution of cluster heads in LEACH protocol leads to unbalanced energy consumption of wireless sensor network nodes. A hierarchical wireless sensor network with uniform clustering was constructed by optimizing the initial cluster center K-means algorithm. By obtaining the geographic location information of the nodes, the K-means clustering algorithm was used to form k uniform clusters, and then the cluster heads were elected if the most residual energy of the nodes in the cluster was the most abundant. The clustering algorithm can make the network load uniform and prolong the lifetime of the network. By optimizing the selection of initial cluster centers, the number of iterations of K-means algorithm is reduced to make it converge faster, the time cost of clustering is less, and the geographical distribution between clusters is more uniform. In the stage of stable data transmission, the method of data regression is used to reduce the communication between common nodes and cluster heads, so as to reduce the power consumption. Experimental results show that the proposed strategy can effectively reduce the power consumption and prolong the lifetime of the network.
【作者單位】： 江西師范大學(xué)計(jì)算機(jī)信息工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(61462042,61650105)資助 江西省自然科學(xué)基金項(xiàng)目(20151BAB2017007)資助 江西省教育廳科研項(xiàng)目(GJJ13229)資助
【分類(lèi)號(hào)】：TN929.5;TP212.9
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本文編號(hào)：1845676