Maximizing network capacity with optimal source selection: A network science perspective

C Jiang, Y Chen, Y Ren, KJR Liu - IEEE Signal Processing …, 2014 - ieeexplore.ieee.org
IEEE Signal Processing Letters, 2014ieeexplore.ieee.org
How to enhance the network capacity is one of the most important issues. To achieve this,
the existing works have focused on improving either the network structure or routing
strategies with a common assumption of uniformly distributing the replicas of information
among the nodes in the network. The nodes associated with information replicas are
considered as source nodes (or server). However, for many networks such as the Internet,
some nodes have much more traffics than the others, exhibiting an asymmetric …
How to enhance the network capacity is one of the most important issues. To achieve this, the existing works have focused on improving either the network structure or routing strategies with a common assumption of uniformly distributing the replicas of information among the nodes in the network. The nodes associated with information replicas are considered as source nodes (or server). However, for many networks such as the Internet, some nodes have much more traffics than the others, exhibiting an asymmetric phenomenon. In this letter, we study the optimal source selection strategy to enhance the network capacity, where an optimization model is proposed to find the optimal source selection probability distribution. Simulation results show that in homogeneous networks, most of the nodes can be the sources. While in heterogeneous networks such as the scale-free networks, only a small number of the nodes can be the sources. Moreover, an interesting phenomenon is observed that the optimal proportion of source nodes in Erdös-Rényi random network and Barabási-Albert scale-free network exhibits a power law relationship with the network size.
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