Study and Comparison of Partitioning Clustering Algorithms

Clustering is one of the main operations in data mining and its aim is to group similar objects in clusters. This technique seeks to discover structure of dataset by considering similarities or differences between data. Clustering algorithms can be divided into several categories including partitioning clustering algorithms، hierarchical algorithms and density based algorithms. In this paper we investigate some partitioning algorithms and consider them in term of some important parameters and finally compare them1. Keywords — delay/fault-tolerant mobile sensor network، delivery delay، delivery probability، DFT-MSN، erasure coding، pervasive information gathering، queuing theory، replication، transmission overhead