Network Data Clustering Analysis

I need an expert in network data analysis with a focus on clustering techniques.

1. Select amount of nodes according to the rule: N = 1000 + XXX,
where XXX are the last of three numbers of your I.D. Build a network according to follow model:
The graph contain large K clusters:
K = 2 + X, where X is the last number in your I.D.
Each large cluster contains 10 + X smaller clusters.
The edge probability in the graph is 10/N
The edge probability in the Large clusters is 0.5;
The edge probability in the small clusters is 0.9;


2. Make clustering of the graph with the help of Markov algorithm
3. Investigate dependence of the clustering on the parameters of the algorithm
Find the conditions for detection of the:
a) Large clusters
b) Small clusters
4. Make comparative visualization of different results of clustering and initial (correct) clustering (both).
5. Make a report with describing of your work (in "word"), containing:
a) network pictures (at least 10);
b) detailed description of the method and results;
c) answer the question in 3
d) if some part of your code was taken from somewhere, write correspondent references;
e) Make conclusion concerning to quality of the applied method;

6. Send the report, documented code and Pajek files.