arXiv subjects

Dhairya Patel

Publications and source records attributed to Dhairya Patel.

3 recordsLinked to original sources

arXiv2026

Risk-Aware Control of Systems with Quasi-Cone-Bounded Nonlinearities

We develop a tractable, rigorous approach to risk-aware control for a class of nonlinear systems. While many classical control methods reduce uncertainty to a simple average or a worst-case outcome, risk-aware control aims to equip systems with a refined awareness of uncertainty. Efficient methods for risk-aware control of linear systems are available, but there is a paucity of tools for tractable, risk-aware control of nonlinear systems. To bridge this gap, we develop an analytical, suboptimal controller with respect to a risk-aware performance criterion for systems with nonlinearities characterized by cone-like bounds. Numerical examples demonstrate benefits of the characterization of nonlinearities and risk that we consider.

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arXiv2024

Navigating Fog Federation: Classifying Current Research and Identifying Challenges

Fog computing has gained significant attention for its potential to enhance resource management and service delivery by bringing computation closer to the network edge.While numerous surveys have explored various aspects of fog computing, there is a distinct gap in the literature when it comes to fog federation, a crucial extension that enables collaboration and resource sharing across multiple fog environments, enhancing scalability, service availability, and resource optimization.This paper provides a comprehensive survey of the existing work on fog federation, classifying the contributions from its inception to the present.We analyze the various approaches, architectures, and methodologies proposed for fog federation and identify the primary challenges addressed in this field.In addition, we explore the simulation tools and platforms utilized in evaluating fog federation systems.Our survey uniquely contributes to the literature by addressing the specific topic of fog federation, offering insights into the current state of the art and highlighting open research gaps and future directions.

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arXiv2024

Risk-Aware Finite-Horizon Social Optimal Control of Mean-Field Coupled Linear-Quadratic Subsystems

We formulate and solve an optimal control problem with cooperative, mean-field coupled linear-quadratic subsystems and additional risk-aware costs depending on the covariance and skew of the disturbance. This problem quantifies the variability of the subsystem state energy rather than merely its expectation. In contrast to related work, we develop an alternative approach that illuminates a family of matrices with many analytical properties, which are useful for effectively extracting the mean-field coupled solution from a standard LQR solution.

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