Toposemantic Network Clustering.

We study the problem of building an optimal network-layer clustering hierarchy, where the optimality can be defined using three potentially conflicting metrics: state, delay and bandwidth. The problem of network clustering where a node's addresses depends on the node's location (e.g. in the hierarchy) is well studied. We study a problem where network nodes are addressed by specifications that might not be tied to locations in the topology. We propose and compare several distributed clustering al- gorithms: (i) clustering based solely on topology, (ii) clustering based solely on semantics (node specifications) and (iii) a combi- nation of the above methods (toposemantic network clustering), where we specify a parameter that determines how much the clustering depends on topology and how much on semantics. We show that the toposemantic method yields the best results when we know the right parameter value for a given topology and assignment of specifications. We propose an algorithm that does not require a parameter, but nevertheless yields better results than the first two methods. 1