Thesis
Resource allocation and fairness in complex networks: A case study of disease spread mitigation strategies
Washington State University
Master of Science (MS), Washington State University
2012
Handle:
https://hdl.handle.net/2376/103510
Abstract
We explore two issues concerning the design of strategies for mitigating disease spread. First, we develop tools for finding and visualizing the distribution of limited resources that should be provided to large-scale networks, so as to optimally retard the dynamical spread of infectious diseases. This study affords us a better understanding of the impact of network topology on optimal resource allocation, for both real network graphs of realistic size (e.g., one of the air transportation network) and for canonical graph classes (e.g., large random graphs). Furthermore, our work is a promising first step towards designing network control methodologies based on network properties alone. Next, the effect of fairness in resource distribution on disease spread mitigation is explored. It is determined that the cost of a fair allocation of resources on spread mitigation (relative to an optimal one) is strongly dependent on the characteristics of the graph representing interactions among network components (e.g., subpopulations, individuals) for the spread models. This study may also serve as a starting point for understanding the tradeoff between optimality and fairness more broadly, e.g. in linear-system control and design problems where achieving stability, robustness, and performance under constraint is of importance.
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Details
- Title
- Resource allocation and fairness in complex networks
- Creators
- Arun Vijayshankar
- Contributors
- Sandip Roy (Degree Supervisor)
- Awarding Institution
- Washington State University
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University; [Pullman, Washington] :
- Identifiers
- 99900525133001842
- Language
- English
- Resource Type
- Thesis