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Analysis of Discrete Load Balancing on Heterogeneous Networks (ADLON)

Subject Area Theoretical Computer Science
Term from 2014 to 2019
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 223438688
 
Final Report Year 2019

Final Report Abstract

Load balancing is an important prerequisite for the efficient usage of large parallel networks. In the typical theoretical abstraction, processors are represented by nodes of a graph, links are represented by edges, and loads are represented by vertex weights. Within this project, we have studied iterative algorithms to distribute the load on heterogeneous networks. Regarding network models, we focused on various models of deterministic and random scale-free graphs. For the Chung-Lu random graph model we proved that load-balancing can be done in double-logarithmic time, which is not achievable on homogeneous networks. We also developed a framework to systematically evaluate generative network models regarding how well they represent real-world networks.

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