In this study, a new Centre-Oriented Clustering Algorithm (CCP) which provides self-clustering of the network by using a method similar to the center-biased clustering method of k-means algorithm is presented and differs from literature in this respect. Proposed algorithm is compared with LEACH because it uses similar techniques as it aims to self-organize irregular distributed networks. In the experimental study, CCP and LEACH algorithms were run in randomly generated network models and the algorithms were compared in terms of the total amount of energy remaining in the network and the number of surviving nodes. The algorithms were run on 15 different WSN models, each of which was irregularly distributed with 100 nodes, and the amount of energy remaining in the network after each trial was recorded and averaged. As a result, it was observed that the energy in the network was 9.4% more efficient in CCP algorithm. In addition, when the number of surviving nodes was considered, it was observed that the average of 28.3 nodes in CCP algorithm and 18 nodes survived in the LEACH algorithm.

中文翻译：

---

分布式结构无线传感器网络的高效节能聚类算法

在这项研究中，提出了一种新的面向中心的聚类算法（CCP），该算法通过使用与k-means算法的中心偏置聚类方法相似的方法提供网络的自聚类，并且在这方面与文献不同。提议的算法与LEACH进行了比较，因为它使用了类似的技术，因为它旨在自组织不规则的分布式网络。在实验研究中，CCP和LEACH算法在随机生成的网络模型中运行，并根据网络中剩余的能量总量和存活节点数对算法进行了比较。该算法在15种不同的WSN模型上运行，每种模型不规则地分布有100个节点，并且记录每次试验后网络中剩余的能量并取平均值。结果是，据观察，在CCP算法中，网络中的能量效率高9.4％。另外，当考虑存活节点数时，观察到CCP算法中平均有28.3个节点，LEACH算法中平均有18个节点。