A Comparative Study of Hierarchical Clustering in Heterogeneous Environment

Abstract

— In this project, the Hierarchical clustering is one of the most popular clustering methods that can find hierarchical structure hidden in input data for data analysis. To perform this method, one needs to define the notion of distance between two clusters. The inter-cluster distance is defined as that the distance between the shortest line connecting two clusters, for connecting single linkage. For the full linkage, the inter-cluster distance is defined as that the longest straight line between the two clusters. For the average linkage, the inter-cluster distance is defined as that the distance between the cluster members. For the centroid linkage, the inter-cluster distance is defined as that the distance between the centers of the two clusters. Maintaining the inter-cluster distance globally, is the challenging one in the wireless network for sharing large data packets. In a wireless network, the large number of flows can cause congestion. Therefore, a flow control mechanism is required that the amount of data inside the network. In a wireless networks, the bandwidth is a shared resources. The common assumption is that the bandwidth available to a node is shared within the interference range of the node, this affects the available bandwidth inside a network. The estimation of bandwidth in a network results in reducing the overhead of the data transmission. The difficulties in the wireless network is that are Interferences, Absorption and reflection, Multipath fading, Hidden node problem, Resource sharing problem, Capacity, Channel, Network, Safety, etc.

Authors and Affiliations

Nehru Revathi

Keywords

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  • EP ID EP642804
  • DOI -
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How To Cite

Nehru Revathi (2016). A Comparative Study of Hierarchical Clustering in Heterogeneous Environment. International Journal of Linguistics and Computational Applications, 3(2), 43-46. https://europub.co.uk/articles/-A-642804