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Algorithmic performance of large-scale distributed networks
A spectral method approach
Engleski
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Complex networks like the Internet, peer-to-peer systems, and emerging sensor and ad-hoc networks are large distributed decentralized communication systems arising repeatedly in today's technology. In such networks it is critical to characterize network performance as the size of the network scales. The focus of this work is to relate basic network performance metrics to structural characteristics of underlying network topologies, and to develop protocols that reinforce and exploit desired structural characteristics. We have used the notions of conductance and spectral analysis to study the structural characteristics of complex communication networks. These graph-theoretic notions are directly related to the performance of basic communication tasks performed on the graph of the network, including routing congestion, searching, and crawling. They can be also used to quantify and measure the presence of groups of nodes that connect preferentially with each other, which is also referred as clustering.
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