基于無(wú)線傳感器網(wǎng)絡(luò)的K均值算法研究

　　傳統(tǒng)無(wú)線傳感網(wǎng)一般由大量密集的傳感器節(jié)點(diǎn)構(gòu)成，存在節(jié)點(diǎn)計(jì)算能力、能源和帶寬都非常有限的缺點(diǎn)，為了有效節(jié)能、延長(zhǎng)網(wǎng)絡(luò)壽命，介紹了基于聚類的K均值算法。該算法通過生成的簇頭節(jié)點(diǎn)散播到網(wǎng)絡(luò)的各個(gè)區(qū)域中，減少了每個(gè)區(qū)域內(nèi)通信的能耗和可能會(huì)出現(xiàn)的一般節(jié)點(diǎn)過早死亡的情況，從而避免了網(wǎng)絡(luò)對(duì)該區(qū)域提早失去監(jiān)控。實(shí)驗(yàn)證明，該算法對(duì)各節(jié)點(diǎn)位置確定的無(wú)線傳感器網(wǎng)絡(luò)有低能耗、高穩(wěn)定性特點(diǎn)，能較好的對(duì)無(wú)線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)拓?fù)浣Y(jié)構(gòu)進(jìn)行優(yōu)化，達(dá)到能量均衡的目的。

　　Abstract:

　　Traditional wireless sensor network was consisted of a large number of dense sensor nodes generally， which has the disadvantage that the node’s computing power， energy and bandwidth are very limited. In order to save energy effectively and prolong the network lifetime， the K-means algorithm based on clustering was introduced. By interspersing generated cluster head nodes to each area of network， the algorithm reduced the communication consumption of each area and the possible condition of common nodes’ premature death. Thus it avoid the network prematurely losing control to the region. The experiment results show that for the wireless sensor networks that each node has determinate location， the algorithm has the features of low energy consumption and high stability. It can preferably optimize the topology of wireless sensor network nodes， and achieve the purpose of energy equilibrium.