Clustering Algorithms for Scale-Free Networks and Applications to Cloud Resource Management
The analysis of high-level models of a system allows users to better understand its behavior. Oftentimes users use a finite state machine model of a system where vertices represent states and the directed arcs represent transitions between states. Such models provide insights on the system dynamics, but are seldom used for the analysis of complex systems. In this paper, the authors introduce algorithms for the construction of scale-free networks and for clustering around the nerve centers, nodes with a high connectivity in scale-free networks. They argue that such overlay networks could support self-organization in a complex system like a cloud computing infrastructure and allow the implementation of optimal resource management policies.