Histogram Based Live Streaming in Peer to Peer Dynamic Balancing & Clustering
M. Kavita, T. V. U. Kirankumar · 2013
We made a preliminary clustering analysis of an inv estiga measure research within Planet Lab. The application was an Internet architecture. Our clustering is inspired by the Reg ularity. Such approach was already demonstrated in appeared to be a powerful tool. Live streaming res ult suggests that the nodes of a large enough grap h can be partitioned in few clusters in such a way that link distribution between most of the pairs look like r andom. Our main goal is to stud y what this type of clustering can tell us about p2 p systems using our investigational system as sourc e of data. We searched clustering’s of clustering typ e by using max like hood as leadership. Our graph i s directed and weighted. The link direction design ates a client server relation and the value is the proportion of all chunks obtained from such a link during the whole experimentation. We think that the first results are motivating. Mos t of the cluster pairs have very great patterns of link distribution , organizing peers effectively. The values of weights between clusters and their patterns. We end up with cluster pairs