@article{hu_doshi_eun_2024, title={Minimizing File Transfer Time in Opportunistic Spectrum Access Model}, volume={23}, ISSN={["1558-0660"]}, url={https://doi.org/10.1109/TMC.2022.3212926}, DOI={10.1109/TMC.2022.3212926}, abstractNote={We study the file transfer problem in opportunistic spectrum access (OSA) model, which has been widely studied in throughput-oriented applications for max-throughput strategies and in delay-related works that commonly assume identical channel rates and fixed file sizes. Our work explicitly considers minimizing the file transfer time for a given file in a set of heterogeneous-rate Bernoulli channels, showing that max-throughput policy doesn't minimize file transfer time in general. We formulate a mathematical framework for static extend to dynamic policies by mapping our file transfer problem to a stochastic shortest path problem. We analyze the performance of our proposed static and dynamic optimal policies over the max-throughput policy. We propose a mixed-integer programming formulation as an efficient alternative way to obtain the dynamic optimal policy and show a huge reduction in computation time. Then, we propose a heuristic policy that takes into account the performance-complexity tradeoff and consider the online implementation with unknown channel parameters. Furthermore, we present numerical simulations to support our analytical results and discuss the effect of switching delay on different policies. Finally, we extend the file transfer problem to Markovian channels and demonstrate the impact of the correlation of each channel.}, number={1}, journal={IEEE TRANSACTIONS ON MOBILE COMPUTING}, author={Hu, Jie and Doshi, Vishwaraj and Eun, Do Young}, year={2024}, month={Jan}, pages={630–644} }
 @article{doshi_mallick_eun_2023, title={Convergence of Bi-Virus Epidemic Models With Non-Linear Rates on Networks-A Monotone Dynamical Systems Approach}, volume={31}, ISSN={["1558-2566"]}, DOI={10.1109/TNET.2022.3213015}, abstractNote={We study convergence properties of competing epidemic models of the Susceptible-Infected-Susceptible ( $SIS$ ) type. The SIS epidemic model has seen widespread popularity in modelling the spreading dynamics of contagions such as viruses, infectious diseases, or even rumors/opinions over contact networks (graphs). We analyze the case of two such viruses spreading on overlaid graphs, with non-linear rates of infection spread and recovery. We call this the non-linear bi-virus model and, building upon recent results, obtain precise conditions for global convergence of the solutions to a trichotomy of possible outcomes: a virus-free state, a single-virus state, and to a coexistence state. Our techniques are based on the theory of monotone dynamical systems (MDS), in contrast to Lyapunov based techniques that have only seen partial success in determining convergence properties in the setting of competing epidemics. We demonstrate how the existing works have been unsuccessful in characterizing a large subset of the model parameter space for bi-virus epidemics, including all scenarios leading to coexistence of the epidemics. To the best of our knowledge, our results are the first in providing complete convergence analysis for the bi-virus system with non-linear infection and recovery rates on general graphs.}, number={3}, journal={IEEE-ACM TRANSACTIONS ON NETWORKING}, author={Doshi, Vishwaraj and Mallick, Shailaja and Eun, Do Young}, year={2023}, month={Jun}, pages={1187–1201} }
 @article{doshi_hu_eun_2022, title={Bi-SIS Epidemics on Graphs - Quantitative Analysis of Coexistence Equilibria}, ISSN={["2576-2370"]}, DOI={10.1109/CDC51059.2022.9992411}, abstractNote={We consider a system in which two viruses of the Susceptible-Infected-Susceptible (SIS) type compete over general, overlaid graphs. While such systems have been the focus of many recent works, they have mostly been studied in the sense of convergence analysis, with no existing results quantifying the non-trivial coexistence equilibria (CE) - that is, when both competing viruses maintain long term presence over the network. In this paper, we prove monotonicity of the CE with respect to effective infection rates of the two viruses, and provide the first quantitative analysis of such equilibria in the form of upper bounds involving spectral radii of the underlying graphs, as well as positive equilibria of related single-virus systems. Our results provide deeper insight into how the long term infection probabilities are affected by system parameters, which we further highlight via numerical results.}, journal={2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC)}, author={Doshi, Vishwaraj and Hu, Jie and Eun, Do Young}, year={2022}, pages={5608–5613} }
 @article{doshi_mallick_eun_2021, title={Competing Epidemics on Graphs - Global Convergence and Coexistence}, ISSN={["0743-166X"]}, DOI={10.1109/INFOCOM42981.2021.9488828}, abstractNote={The dynamics of the spread of contagions such as viruses, infectious diseases or even rumors/opinions over contact networks (graphs) have effectively been captured by the well known Susceptible-Infected-Susceptible (SIS) epidemic model in recent years. When it comes to competition between two such contagions spreading on overlaid graphs, their propagation is captured by so-called bi-virus epidemic models. Analysis of such dynamical systems involve the identification of equilibrium points and its convergence properties, which determine whether either of the viruses dies out, or both survive together. We demonstrate how the existing works are unsuccessful in characterizing a large subset of the model parameter space, including all parameters for which the competitiveness of the bi-virus system is significant enough to attain coexistence of the epidemics. In this paper, we fill in this void and obtain convergence results for the entirety of the model parameter space; giving precise conditions (necessary and sufficient) under which the system globally converges to a trichotomy of possible outcomes: a virus-free state, a single-virus state, and to a coexistence state – the first such result.}, journal={IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (IEEE INFOCOM 2021)}, author={Doshi, Vishwaraj and Mallick, Shailaja and Eun, Do Young}, year={2021} }