Abstract
The next-generation network is modeled as an ecosystem of heterogeneous networks with multiservice traffic. Despite the presence of admission control, resource competition is inevitable and certain flows are disadvantaged over others. This chapter presents an ecologically inspired theory for resource distribution in such an environment. Optimal resources required for stable coexistence can be accurately predicted by the proposed theory. Next, we apply this algorithm for mobility load-balancing optimization in a long-term evolution network to enable self-organizing networking. The underlying algorithm uses an ecologically inspired graphical theory for equitable resource/load distribution in a multiresource, multiclass environment. Optimal load levels required for the stability of the eNodeB could be accurately estimated by the proposed eco-inspired graphical theory. Analytical proof and simulation results are provided for supporting the above argument.
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